Journal articles: 'Plant model with time delays'

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Tufa, Lemma Dendena. "Direct Synthesis Controller Identification." Advanced Materials Research 622-623 (December 2012): 1498–502. http://dx.doi.org/10.4028/www.scientific.net/amr.622-623.1498.

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Direct synthesis controller design approach has serious limitations when it is applied to plant models that have more complex models and models involving time delays. In such cases the design becomes more cumbersome and the time delay appears in the denominator making it difficult to realize. In order to get simple realizable controllers approximations of plant model and time delays are done. This leads to controllers with non-optimal parameters. In this paper, a new approach for designing the controller by combining direct synthesis approach and system identification is presented. The controller is identified from the plant model and the desired closed-loop without the need for approximating the plant model and the time delay and ensures that the controller parameters are optimal.

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Yang, Xianqiang, Weili Xiong, Zeyuan Wang, and Xin Liu. "Parameter identification of nonlinear multirate time-delay system with uncertain output delays." Transactions of the Institute of Measurement and Control 40, no. 12 (October 16, 2017): 3498–506. http://dx.doi.org/10.1177/0142331217733326.

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The joint parameter and time-delay estimation problems for a class of nonlinear multirate time-delay system with uncertain output delays are addressed in this paper. The practical process typically has time-delay properties and the process data are often multirate, sampled with output data inevitably corrupted by uncertain delays. The linear parameter varying (LPV) finite impulse response (FIR) multirate time-delay model is initially built to describe the considered system. The problems of over-parameterization and the existence of both continuous model parameters and discrete time-delays have made the conventional maximum likelihood difficult to solve the considered problems. In order to handle these problems, the joint parameter and time-delay estimation for the LPV FIR multirate time-delay model are formulated in the expectation-maximization scheme, and the algorithm to estimate the model parameters and time-delays is derived, simultaneously based on multirate process data. The efficacy of the proposed method is verified through a numerical simulation and a practical chemical plant.

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Yamalova, Diana, Alexander Churilov, and Alexander Medvedev. "Finite-Dimensional Hybrid Observer for Delayed Impulsive Model of Testosterone Regulation." Mathematical Problems in Engineering 2015 (2015): 1–12. http://dx.doi.org/10.1155/2015/190463.

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The paper deals with the model-based estimation of hormone concentrations that are inaccessible for direct measurement in the blood stream. Previous research demonstrated that the dynamics of nonbasal endocrine regulation can be closely captured by linear continuous models with time delays under a pulse-modulated feedback. The presence of continuous time delays is inevitable in such a model due to transport phenomena and the time necessary for an endocrine gland to produce a certain hormone quantity. Yet, thanks to the finite-dimensional reducibility of the linear time-delay part of the system, a finite-dimensional model can be used to reconstruct both the continuous and discrete states of the hybrid time-delay plant. A hybrid observer exploiting this possibility is suggested and analyzed by means of a discrete impulse-to-impulse mapping.

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Mirkin, Boris M., and Per-Olof Gutman. "Output-Feedback Model Reference Adaptive Control for Continuous State Delay Systems." Journal of Dynamic Systems, Measurement, and Control 125, no. 2 (June 1, 2003): 257–61. http://dx.doi.org/10.1115/1.1570856.

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This paper develops a new approach for the output model reference adaptive control of linear continuous-time plants with state delays. The main idea is to include into the control law a feedforward component that compensates for the delayed states, in addition to output feedback. The feedforward is formed by special adaptively adjusted prefilters as a function of the delayed state of the reference model. The output feedback component is designed as for a plant without delay, but applied to the time-delay plant. Such a controller structure containing adaptive output feedback and adaptive prefilters from the delayed reference model makes it possible to solve the problem of adaptive exact asymptotic output tracking under parametric uncertainties. The stability is analyzed using the Lyapunov-Krasovskii functional method. A simulated example illustrates the new controller.

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Zayed, Tarek M., and Ibrahim A. Nosair. "Cost management for concrete batch plant using stochastic mathematical models." Canadian Journal of Civil Engineering 33, no. 8 (August 1, 2006): 1065–74. http://dx.doi.org/10.1139/l06-051.

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Assessing productivity, cost, and delays are essential to manage any construction operation, particularly the concrete batch plant (CBP) operation. This paper focuses on assessing the above-mentioned items for the CBP using stochastic mathematical models. It aims at (i) identifying the potential sources of delay in the CBP operation; (ii) assessing their influence on production, efficiency, time, and cost; and (iii) determining each factor share in inflating the CBP concrete unit expense. Stochastic mathematical models were designed to accomplish the aforementioned objectives. Data were collected from five CBP sites in Indiana, USA, to implement and verify the designed models. Results show that delays due to management conditions have the highest probability of occurrence (0.43), expected value of delay percent (62.54% out of total delays), and relative delay percent. The expected value of efficiency for all plants is 86.53%; however, the average total expense is US$15.56/m3 (all currency are in US$). In addition, the expected value of effective expenses (EE) is $18.03/m3, resulting in extra expenses (XE) of $2.47/m3. This research is relevant to both industry practitioners and researchers. It develops models to determine the effect of delays on concrete unit cost. They are also beneficial to the CBP management.Key words: concrete batch plant, delays, management conditions, cost models, cost management, stochastic mathematical models.

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Lu, Ningyun, Bin Jiang, Lei Wang, Jianhua Lu, and Xi Chen. "A Fault Prognosis Strategy Based on Time-Delayed Digraph Model and Principal Component Analysis." Mathematical Problems in Engineering 2012 (2012): 1–17. http://dx.doi.org/10.1155/2012/937196.

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Because of the interlinking of process equipments in process industry, event information may propagate through the plant and affect a lot of downstream process variables. Specifying the causality and estimating the time delays among process variables are critically important for data-driven fault prognosis. They are not only helpful to find the root cause when a plant-wide disturbance occurs, but to reveal the evolution of an abnormal event propagating through the plant. This paper concerns with the information flow directionality and time-delay estimation problems in process industry and presents an information synchronization technique to assist fault prognosis. Time-delayed mutual information (TDMI) is used for both causality analysis and time-delay estimation. To represent causality structure of high-dimensional process variables, a time-delayed signed digraph (TD-SDG) model is developed. Then, a general fault prognosis strategy is developed based on the TD-SDG model and principle component analysis (PCA). The proposed method is applied to an air separation unit and has achieved satisfying results in predicting the frequently occurred “nitrogen-block” fault.

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Naghavi, S. Vahid, A. A. Safavi, Mohammad Hassan Khooban, S. Pourdehi, and Valiollah Ghaffari. "A robust control strategy for a class of distributed network with transmission delays." COMPEL - The international journal for computation and mathematics in electrical and electronic engineering 35, no. 5 (September 5, 2016): 1786–813. http://dx.doi.org/10.1108/compel-08-2015-0287.

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Purpose The purpose of this paper is to concern the design of a robust model predictive controller for distributed networked systems with transmission delays. Design/methodology/approach The overall system is composed of a number of interconnected nonlinear subsystems with time-varying transmission delays. A distributed networked system with transmission delays is modeled as a nonlinear system with a time-varying delay. Time delays appear in distributed systems due to the information transmission in the communication network or transport of material between the sub-plants. In real applications, the states may not be available directly and it could be a challenge to address the control problem in interconnected systems using a centralized architecture because of the constraints on the computational capabilities and the communication bandwidth. The controller design is characterized as an optimization problem of a “worst-case” objective function over an infinite moving horizon. Findings The aim is to propose control synthesis approach that depends on nonlinearity and time varying delay characteristics. The MPC problem is represented in a time varying delayed state feedback structure. Then the synthesis sufficient condition is provided in the form of a linear matrix inequality (LMI) optimization and is solved online at each time instant. In the rest, an LMI-based decentralized observer-based robust model predictive control strategy is proposed. Originality/value The authors develop RMPC strategies for a class of distributed networked systems with transmission delays using LMI-Based technique. To evaluate the applicability of the developed approach, the control design of a networked chemical reactor plant with two sub-plants is studied. The simulation results show the effectiveness of the proposed method.

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Shen, Gang, and Yu Cao. "A Gaussian Process Based Model Predictive Controller for Nonlinear Systems with Uncertain Input-Output Delay." Applied Mechanics and Materials 433-435 (October 2013): 1015–20. http://dx.doi.org/10.4028/www.scientific.net/amm.433-435.1015.

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In this paper, we propose a Model Predictive Controller (MPC) based on Gaussian process for nonlinear systems with uncertain delays and external Gaussian disturbances. We investigate the ability of Gaussian process based MPC on handling the variable delay that follows a Gaussian distribution through a properly selected observation horizon. To test the effectiveness of this approach, comparisons are made for the proposed Gaussian process based MPC and RBF (Radial Basis Function) neural networks by analyzing the time complexity and control performance. In simulations, two experiments are designed to verify the results of different systems, including a first-order nonlinear plant and a second-order nonlinear plant with variable delays and Gaussian noises. It is demonstrated that the proposed approach may achieve the desired results.

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Wang, Pu, and Qing-peng Zhang. "Train delay analysis and prediction based on big data fusion." Transportation Safety and Environment 1, no. 1 (February 4, 2019): 79–88. http://dx.doi.org/10.1093/tse/tdy001.

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Abstract Despite the fact that punctuality is an advantage of rail travel compared with other long-distance transport, train delays often occur. For this study, a three-month dataset of weather, train delay and train schedule records was collected and analysed in order to understand the patterns of train delays and to predict train delay time. We found that in severe weather train delays are determined mainly by the type of bad weather, while in ordinary weather the delays are determined mainly by the historical delay time and delay frequency of trains. Identifying the factors closely correlated with train delays, we developed a machine-learning model to predict the delay time of each train at each station. The prediction model is useful not only for passengers wishing to plan their journeys more reliably, but also for railway operators developing more efficient train schedules and more reasonable pricing plans.

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BASHER, A. M. HASANUL, and RANGASWAMY MUKUNDAN. "Model reference control of uncertain systems with time delays in plant state and control." International Journal of Systems Science 18, no. 9 (January 1987): 1609–26. http://dx.doi.org/10.1080/00207728708967139.

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Ma, Suqi. "Application of Extended Geometrical Criterion to Population Model with Two Time Delays." Journal of Mathematics Research 10, no. 3 (April 16, 2018): 63. http://dx.doi.org/10.5539/jmr.v10n3p63.

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Geometrical criterion is a flexible method to be applied to a type of delay differential equations with delay dependent coefficient. The criterion is used to solve roots attribution of the related characteristic equation in complex plane effectively by introducing a new parameter skillfully. An extended geometrical criterion is developed to compute the stability of DDEs with two time delays. It is found that stability switching phenomena arise while equilibrium solution loses its stability and becomes unstable, then retrieve its stability again. Hopf bifurcation and the bifurcating periodic solution is analyzed by applying central manifold reduction method. The novel dynamical behaviors such as periodical solution bifurcating to chaos are discovered by using numerical simulation method.

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Liu, Junli, and Tailei Zhang. "Stability and Hopf Bifurcation Analysis of a Plant Virus Propagation Model with Two Delays." Discrete Dynamics in Nature and Society 2018 (2018): 1–12. http://dx.doi.org/10.1155/2018/7126135.

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To understand the interaction between the insects and the plants, a system of delay differential equations is proposed and studied. We prove that if R0≤1, the disease-free equilibrium is globally asymptotically stable for any length of time delays by constructing a Lyapunov functional, and the system admits a unique endemic equilibrium if R0>1. We establish the sufficient conditions for the stability of the endemic equilibrium and existence of Hopf bifurcation. Using the normal form theory and center manifold theorem, the explicit formulae which determine the stability, direction, and other properties of bifurcating periodic solutions are derived. Some numerical simulations are given to confirm our analytic results.

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ZHANG, SHU, KWOK-WAI CHUNG, and JIAN XU. "STABILITY SWITCH BOUNDARIES IN AN INTERNET CONGESTION CONTROL MODEL WITH DIVERSE TIME DELAYS." International Journal of Bifurcation and Chaos 23, no. 05 (May 2013): 1330016. http://dx.doi.org/10.1142/s0218127413300164.

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For a two-dimensional congestion control model with diverse time delays, this paper provides a detailed study on the geometrical properties of stability switch boundaries in the plane of time delays. Conditions for stability switch boundaries to arise as vertical spiral-like curves, horizontal spiral-like curves, diagonal spiral-like curves and closed-loops are obtained on the system parameters other than time delays. The boundary curves may self-intersect or intersect with one another. Some of these intersections are identified as tangent double Hopf bifurcation with codimension three. It is found that double Hopf bifurcation point exists in the plane of time delays regardless of the values of the other system parameters.

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Li, Liu, Tao Yao, Chunjie Zhou, Fei Liu, Dianli Hou, and Hongyong Yang. "Modeling and filtering for a stochastic uncertain system in a complex scenario." Thermal Science 25, no. 2 Part B (2021): 1411–24. http://dx.doi.org/10.2298/tsci191201041l.

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This paper presents a new approach to filter signals for discrete-time physical problems with stochastic uncertain in the presence of random data transmission delays, out-of-order packets and correlated noise. To deal with the packet disorder, the system model synthesizing the transmission delays and out-of-order packets from the plant to the filter is established by utilizing signal reconstruction schemes based on the zero-order-holder and logic zero-order-holder. A robust finite horizon Kalman filter is proposed by augmenting the state-space model and minimizing the error covariance. To further improve the filtering performance, a linear estimation-based delay compensation strategy is proposed by employing the reorganized time-stamped measurements. Moreover, for solving the missing measurement problem whilst reducing the computational costs, an artificial delay compensation approach is established using an one-step prediction approach. Simulation results show the effectiveness of the proposed method.

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Li, Zheng, and Steven X. Ding. "Optimal Control of Time-Varying Systems with Multiple Delays for Servo Appplications." Applied Mechanics and Materials 496-500 (January 2014): 1556–59. http://dx.doi.org/10.4028/www.scientific.net/amm.496-500.1556.

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We study the problem of optimal control of linear time-varying systems for servo applications and develop a generalized minimum variance controller for a multi-input and multi-output controlled autoregressive moving average model with multiple delays. The controller is applicable to a large class of stochastic linear time-varying systems regardless variation speed in plant parameters.

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Benítez-Pérez, H., Jorge Ortega-Arjona, Jared A. Rojas-Vargas, and A. Durán-Chavesti. "Design of a Fuzzy Networked Control Systems. Priority Exchange Scheduling Algorithm." International Journal of Computers Communications & Control 11, no. 2 (January 26, 2016): 179. http://dx.doi.org/10.15837/ijccc.2016.2.2440.

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This work presents a supervisory control strategy for Networked Control Systems (NCSs). This shows the identification and control of the plant using fuzzy theory. The fuzzy model incorporates the delay dynamics within the fuzzy rules based upon a real-time hierarchical scheduling strategy. A hierarchical scheduling Priority Exchange algorithm is used based upon codesign strategy following mutual correlation among control and network algorithms in order to bounded time delays. A system of magnetic levitation is presented as a case study.

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Liu, Wei, Xiaoning Zhu, and Liujiang Kang. "Real-Time Track Reallocation for Emergency Incidents at Large Railway Stations." Mathematical Problems in Engineering 2015 (2015): 1–11. http://dx.doi.org/10.1155/2015/296394.

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After track capacity breakdowns at a railway station, train dispatchers need to generate appropriate track reallocation plans to recover the impacted train schedule and minimize the expected total train delay time under stochastic scenarios. This paper focuses on the real-time track reallocation problem when tracks break down at large railway stations. To represent these cases, virtual trains are introduced and activated to occupy the accident tracks. A mathematical programming model is developed, which aims at minimizing the total occupation time of station bottleneck sections to avoid train delays. In addition, a hybrid algorithm between the genetic algorithm and the simulated annealing algorithm is designed. The case study from the Baoji railway station in China verifies the efficiency of the proposed model and the algorithm. Numerical results indicate that, during a daily and shift transport plan from 8:00 to 8:30, if five tracks break down simultaneously, this will disturb train schedules (result in train arrival and departure delays).

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Deng, Mingcong. "Model output following control based on CGT approach for plants with time delays." International Journal of Systems Science 30, no. 1 (January 1999): 69–75. http://dx.doi.org/10.1080/002077299292687.

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Jin, QB, and BY Jiang. "Pseudo-feed-forward decoupling internal model control for singularity plants with time delays." Transactions of the Institute of Measurement and Control 36, no. 4 (December 5, 2013): 565–76. http://dx.doi.org/10.1177/0142331213507078.

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Srikanth, Kavirayani, and Gundavarapu Nagesh. "Naturally Inspired Firefly Controller For Stabilization Of Double Inverted Pendulum." Technological Engineering 12, no. 2 (December 1, 2015): 14–17. http://dx.doi.org/10.1515/teen-2015-0011.

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Abstract A double inverted pendulum plant as an established model that is analyzed as part of this work was tested under the influence of time delay, where the controller was fine tuned using a firefly algorithm taking into considering the fitness function of variation of the cart position and to minimize the cart position displacement and still stabilize it effectively. The naturally inspired algorithm which imitates the fireflies definitely is an energy efficient method owing to the inherent logic of the way the fireflies respond collectively and has shown that critical time delays makes the system healthy.

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Barnes, Ethann R., Stevan Z. Knezevic, Nevin C. Lawrence, Suat Irmak, Oscar Rodriguez, and Amit J. Jhala. "Preemergence herbicide delays the critical time of weed removal in popcorn." Weed Technology 33, no. 6 (July 31, 2019): 785–93. http://dx.doi.org/10.1017/wet.2019.58.

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AbstractUnderstanding the critical time of weed removal (CTWR) is necessary for designing effective weed management programs in popcorn production that do not result in yield reduction. The objective of this study was to determine the CTWR in popcorn with and without a premix of atrazine and S-metolachlor applied PRE. Field experiments were conducted at the University of Nebraska–Lincoln, South Central Agricultural Laboratory near Clay Center, NE in 2017 and 2018. The experiment was laid out in a split-plot design with PRE herbicide as the main plot and weed removal timing as the subplot. Main plots included no herbicide or atrazine/S-metolachlor applied PRE. Subplot treatments included a weed-free control, a non-treated control, and weed removal timing at V3, V6, V9, V15, and R1 popcorn growth stages and then kept weed free throughout the season. A four-parameter log-logistic function was fitted to percentage popcorn yield loss and growing degree days separately to each main plot. The number of growing degree days, when 5% yield loss was achieved, was extracted from the model and compared between main plots. The CTWR was from the V4 to V5 popcorn growth stage in absence of PRE herbicide. With atrazine/S-metolachlor applied PRE, the CTWR was delayed until V10 to V15. It is concluded that, to avoid yield loss, weeds must be controlled before the V4 popcorn growth stage when no PRE herbicide is applied, and PRE herbicide, such as atrazine/S-metolachlor in this study, can delay the CTWR until the V10 growth stage.

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Nwanya, Stephen C., and Celestine N. Achebe. "Balancing a multistage vehicle number plate production line using effective cycle time model." Jurnal Sistem dan Manajemen Industri 4, no. 1 (July 12, 2020): 1–12. http://dx.doi.org/10.30656/jsmi.v4i1.2118.

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Shortest product cycle time is a key criterion for job sequencing and measuring competitiveness among entrepreneurial-based firms. Now, the long waiting time of job orders constitutes a deterministic production line problem in vehicle number plate production plants in Nigeria. Case studies were conducted on those plants, confidentially identified in this paper as A, B, C, and D. Delays caused by non-value-adding work processes are major culprits among other contributors to the long queues at these plants. The value stream mapping technique was applied to identify non-value adding activities before the production line was balanced using an effective cycle time model. The index cases to a balanced line, as shown in the results, are increases in process rate by 41 %, 59 %, 42 %, and 71 % for A, B, C, and D, respectively, and overall line efficiency. Next, the system capacities correspondingly increased with the elimination of wastages. These increments imply that bottleneck activities have been minimized, and we have a balanced production line. The devised solution procedure is reliable and recommended to other line manufacturing concerns that experience delays and bottleneck problems.

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Liou, Luen-Woei, and Asok Ray. "A Stochastic Regulator for Integrated Communication and Control Systems: Part I—Formulation of Control Law." Journal of Dynamic Systems, Measurement, and Control 113, no. 4 (December 1, 1991): 604–11. http://dx.doi.org/10.1115/1.2896464.

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Integrated Communication and Control Systems (ICCS), recently introduced and analyzed in a series of papers [1–7], are applicable to complex dynamical processes like advanced aircraft, spacecraft, automotive, and manufacturing processes. Time-division-multiplexed computer networks are employed in ICCS for exchange of information between spatially distributed plant components as well as for coordination of the diverse control and decision-making functions. Unfortunately, an ICCS network introduces randomly varying, distributed delays within the feedback loops in addition to the digital sampling and data processing delays. These network-induced delays degrade the system dynamic performance, and are a source of potential instability. This two-part paper presents the synthesis and performance evaluation of a stochastic optimal control law for ICCS. In this paper, which is the first of two parts, a state feedback control law for ICCS has been formulated by using the dynamic programming and optimality principle on a finite-time horizon. The control law is derived on the basis of a stochastic model of the plant which is augmented in state space to take into account the effects of randomly varying delays in the feedback loop. The second part [8] presents numerical analysis of the control law and its performance evaluation by simulation of the flight dynamic model of an advanced aircraft.

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Zhang, Qi, and Bin Liu. "Switching Stabilization for Nonlinear Networked Control Systems with Delays and Packet Losses." Information Technology And Control 49, no. 2 (June 16, 2020): 302–16. http://dx.doi.org/10.5755/j01.itc.49.2.24612.

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This paper studies the stabilization problem for nonlinear NCSs(NNCSs) with bilateral network-induced random delay and packet dropout. T-S fuzzy model is employed to represent the nonlinear controlled plant. Based on the T-S model, a discrete-time fuzzy switched system model with uncertain parameters is established by means of the uncertain method and switching system method. Furthermore, the exponential stability condition for the state of the fuzzy switched system is obtained by using the combination of slow switching model-dependent average dwell time (MDADT) method and fast switching MDADT method. Finally, a series of rotary inverted pendulum experiments are provided to illustrates the effectiveness of the proposed method and prove that the proposed fuzzy controller based on T-S fuzzy model can balance the rotary inverted pendulum in a greater state range rather than the linear controller based on linearization

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Androjić, Ivica, and Zlata Dolaček Alduk. "Analysis of energy consumption in the production of hot mix asphalt (batch mix plant)." Canadian Journal of Civil Engineering 43, no. 12 (December 2016): 1044–51. http://dx.doi.org/10.1139/cjce-2016-0277.

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This paper describes tests in which influencing factors that affect energy consumption in the rotary drum were monitored. The monitored influencing factors are moisture, delays in daily production, hourly production capacity, and temperature of produced hot mix asphalt (HMA). The tests include the production of 88 079 t of HMA of continuous and discontinuous gradation on a cyclic asphalt plant in the Republic of Croatia. In 2014, 182 production terms were monitored (155 observed), whereas the moisture content was tested using the same number of input mineral mixture samples. The temperature of the produced asphalt mixture was measured using approximately 67 753 samples during the entire production period. Delays in work and hourly production capacity were measured during production by recording the duration of working time and delays. The final result of this study is the creation of a regression model of the correlation between energy consumption and temperature of the asphalt mixture and the hourly capacity and moisture in the mineral aggregate.

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Wang, Yujia, Dejun Fan, and Junjie Wei. "Stability and Bifurcation Analysis in a Predator–Prey Model with Age Structure and Two Delays." International Journal of Bifurcation and Chaos 31, no. 02 (February 2021): 2150024. http://dx.doi.org/10.1142/s0218127421500243.

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In this paper, a predator–prey model with age structure, Beddington–DeAngelis functional response and time delays is considered. Using a geometric method for studying transcendental equation with two delays, we conduct detailed analysis on the distribution of the roots for the characteristic equation of the model. Then, applying the integrated semigroup theory and the Hopf bifurcation theorem for an abstract Cauchy problem within a nondense domain, we proved the existence of Hopf bifurcation for the model. Stability switches can also occur, as the two time delays pass through a continuous curve in the parameter plane. To illustrate the theoretical results, numerical simulations are presented.

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MIYAMOTO, Shin-ichi, Seiichi SHIN, and Shigenori OKUBO. "Continuous-Time Model Reference Adaptive Control Based on Weighting Functions for Plants with Multiple Time Delays in Control." Transactions of the Society of Instrument and Control Engineers 23, no. 8 (1987): 864–66. http://dx.doi.org/10.9746/sicetr1965.23.864.

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Liu, Li, Aolei Yang, Wenju Zhou, Wasif Naeem, Gang Wang, and Hua Wang. "Modelling and Estimation for Uncertain Systems with Transmission Delays, Packet Dropouts, and Out-of-Order Packets." Complexity 2018 (October 18, 2018): 1–15. http://dx.doi.org/10.1155/2018/7531547.

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The study focuses on the modelling and estimation of a class of discrete-time uncertain systems, including network-induced random delays, packet dropouts, and out-of-order packets during the data transmission from the plant to the estimator. In order to improve system performance, event-triggered signal selection method is used to establish the system model. Based on this model, a distributed measurement and centralized fusion estimation scheme is designed using a robust finite horizon Kalman-type filter. Since the phenomena caused by the network-induced deteriorate estimation accuracy, a time-based reorganization measurement is employed to design a linear delay compensation strategy based on estimation. Moreover, in order to obtain the optimal linear estimation, weighted fusion estimation approach is used to perform information collaboration through the error cross-covariance matrix. Simulation results demonstrate that the proposed method has higher estimation performance than the existing methods in this study.

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Zeng, Zhiyong, Xiaoliang Jin, and Rongxiang Zhao. "Small-signal discrete-time modeling of digitally controlled three-phase PWM boost rectifier under balanced voltage." COMPEL - The international journal for computation and mathematics in electrical and electronic engineering 36, no. 1 (January 3, 2017): 18–47. http://dx.doi.org/10.1108/compel-03-2016-0113.

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Purpose The model for digitally controlled three-phase pulse width modulation (PWM) boost rectifiers is a sampled data model, which is different from the continuous time domain models presented in previous studies. The controller, which is tuned according to the model in continuous time domain and discretized by approximation methods, may exhibit some unpredictable performances and even result in unstable systems under some extreme situations. Consequently, a small-signal discrete-time model of digitally controlled three-phase PWM boost rectifier is required. The purpose of this paper is to provide a simple but accurate small-signal discrete-time model of digital controlled three-phase PWM boost rectifier, which explains the effect of the sampling period, modulator and time delays on system dynamic and improves the control performance. Design/methodology/approach Based on the Laplace domain analysis and the waveforms of up-down-count modulator, the small signal model of digital pulse width modulation (DPWM) in the Laplace domain is presented. With a combination of state-space average and a discrete-time modeling technique, a simplified large signal discrete time model is developed. With rotation transformation and feed-forward decoupling, the large-signal model is decoupled into a single input single output system with rotation transformation. Then, an integrated small signal model in the Laplace domain is constructed that included the time delay and modulation effect. Implementing the modified z-transform, a small-signal discrete-time model is derived from the integrated small signal model. Findings In a digital control system, besides the circuit parameters, the location of pole of open-loop transfer function is also related to system sampling time, affecting the system stability, and the time delay determines the location of the zero of open-loop transfer function, affecting the system dynamic. In addition to the circuit parameters discussed in previous literature, the right half plane (RHP) zero is also determined by the sampling period and the time delay. Furthermore, the corner frequency of the RHP zero is mainly determined by the sampling period. Originality/value The model developed in this paper, accounting for the effect of the sampling period, modulator and time delays on the system dynamic, give a sufficient insight into the behavior of the digitally controlled three-phase PWM rectifier. It can also explain the effect of sampling period and control delay time on system dynamic, accurately predict the system stability boundary and determine the oscillation frequency of the current loop in critical stable. The experimental results verify that the model is a simple and accurate control-oriented small-signal discrete-time model for the digitally controlled three-phase PWM boost rectifier.

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Bahaaldin, Karzan, Ryan Fries, Parth Bhavsar, and Plaban Das. "A Case Study on the Impacts of Connected Vehicle Technology on No-Notice Evacuation Clearance Time." Journal of Advanced Transportation 2017 (2017): 1–9. http://dx.doi.org/10.1155/2017/6357415.

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No-notice evacuations of metropolitan areas can place significant demands on transportation infrastructure. Connected vehicle (CV) technology, with real-time vehicle to vehicle and vehicle to infrastructure communications, can help emergency managers to develop efficient and cost-effective traffic management plans for such events. The objectives of this research were to evaluate the impacts of CVs on no-notice evacuations using a case study of a downtown metropolitan area. The microsimulation software VISSIM was used to model the roadway network and the evacuation traffic. The model was built, calibrated, and validated for studying the performance of traffic during the evacuation. The researchers evaluated system performance with different CV penetration rates (from 0 to 30 percent CVs) and measured average speed, average delays, and total delays. The findings suggest significant reductions in total delays when CVs reached a penetration rate of 30 percent, albeit increases in delays during the beginning of the evacuation. Additionally, the benefits could be greater for evacuations that last longer and with higher proportions of CVs in the vehicle stream.

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Jerome, Norman F., and W. H. Ray. "Model-predictive control of linear multivariable systems having time delays and right-half-plane zeros." Chemical Engineering Science 47, no. 4 (1992): 763–85. http://dx.doi.org/10.1016/0009-2509(92)80267-g.

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Choi, Taihun, and Yoonho Seo. "A Real-Time Physical Progress Measurement Method for Schedule Performance Control Using Vision, an AR Marker and Machine Learning in a Ship Block Assembly Process." Sensors 20, no. 18 (September 20, 2020): 5386. http://dx.doi.org/10.3390/s20185386.

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Progress control is a key technology for successfully carrying out a project by predicting possible problems, particularly production delays, and establishing measures to avoid them (decision-making). However, shipyard progress management is still dependent on the empirical judgment of the manager, and this has led to delays in delivery, which raises ship production costs. Therefore, this paper proposes a methodology for shipyard ship block assembly plants that enables objective process progress measurement based on real-time work performance data, rather than the empirical judgment of a site manager. In particular, an IoT-based physical progress measurement method that can automatically measure work performance without human intervention is presented for the mounting and welding activities of ship block assembly work. Both an augmented reality (AR) marker-based image analysis system and a welding machine time-series data-based machine learning model are presented for measuring the performances of the mounting and welding activities. In addition, the physical progress measurement method proposed in this study was applied to the ship block assembly plant of shipyard H to verify its validity.

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Wu, Wei, Ling Huang, and Ronghua Du. "Simultaneous Optimization of Vehicle Arrival Time and Signal Timings within a Connected Vehicle Environment." Sensors 20, no. 1 (December 29, 2019): 191. http://dx.doi.org/10.3390/s20010191.

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Most existing signal timing plans are optimized given vehicles’ arrival time (i.e., the time for the upcoming vehicles to arrive at the stop line) as exogenous input. In this paper, based on the connected vehicle (CV) technique, vehicles can be regarded as moving sensors, and their arrival time can be dynamically adjusted by speed guidance according to the current signal status and traffic conditions. Therefore, an integrated traffic control model is proposed in this study to optimize vehicle arrival time (or travel speed) and signal timing simultaneously. “Speed guidance model at a red light” and “speed guidance model at a green light” are presented to model the influences between travel speed and signal timing. Then, the methods to model the vehicle arrival time, vehicle delay, and number of stops are proposed. The total delay, which includes the control delay, queuing delay, and signal delay, is used as the objective of the proposed model. The decision variables consist of vehicle arrival time, starting time of green, and duration of green for each phase. The sliding time window is adopted to dynamically tackle the problems. Compared with the results optimized by the classical actuated signal control method and the fixed-time-based speed guidance model, the proposed model can significantly decrease travel delays as well as improve the flexibility and mobility of traffic control. The sensitivity analysis with the communication distance, the market penetration of connected vehicles, and the compliance rate of speed guidance further demonstrates the potential of the proposed model to be applied in various traffic conditions.

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Signes-Pont, Maria Teresa, José Juan Cortés-Plana, and Higinio Mora-Mora. "An Epidemic Grid Model to Address the Spread of Covid-19: A Comparison between Italy, Germany and France." Mathematical and Computational Applications 26, no. 1 (February 8, 2021): 14. http://dx.doi.org/10.3390/mca26010014.

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This paper presents a discrete compartmental Susceptible–Exposed–Infected–Recovered/Dead (SEIR/D) model to address the expansion of Covid-19. This model is based on a grid. As time passes, the status of the cells updates by means of binary rules following a neighborhood and a delay pattern. This model has already been analyzed in previous works and successfully compared with the corresponding continuous models solved by ordinary differential equations (ODE), with the intention of finding the homologous parameters between both approaches. Thus, it has been possible to prove that the combination neighborhood-update rule is responsible for the rate of expansion and recovering/death of the disease. The delays (between Susceptible and Asymptomatic, Asymptomatic and Infected, Infected and Recovered/Dead) may have a crucial impact on both height and timing of the peak of Infected and the Recovery/Death rate. This theoretical model has been successfully tested in the case of the dissemination of information through mobile social networks and in the case of plant pests.

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Rahmani, Behrooz. "Variable selective control for networked systems: A switched quadratic Lyapunov functional approach." Transactions of the Institute of Measurement and Control 39, no. 4 (October 13, 2015): 494–504. http://dx.doi.org/10.1177/0142331215607957.

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This paper presents a new method for control of linear networked systems by combining the predictive control and the variable sampling period approaches. In this way, event-driven sensors are implemented, i.e. by construction the sensors are triggered to sample the outputs of the plant, when new control input signals are received by the actuators. In light of this formulation, at each sampling instant, total control loop delay will be equal to the sampling period which is unknown. In order to deal with the network effects associated with a range of pre-specified time delays, appropriate step invariant discrete-time models of the networked plant are calculated offline. Based on these, some stabilizing control signals are constructed online. The control signals are then packed in the control-side packet, transmitted back to the plant side and received by a time delay compensator module. A less conservative class of Lyapunov functions, called switched quadratic Lyapunov, is used here for stability analysis and stabilizing controller design. Simulation studies on well-known benchmark problems demonstrate the effectiveness of the proposed method.

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RODRIGUEZ ALVARADO, LISAURA WALKIRIA, MIGUEL ANGEL MARTINEZ GARCIA, JESUS LOYO QUIJADA, MARIANA HERNANDEZ GONZALEZ, JESUS VICENTE GONZALEZ SOSA, and MIGUEL ANGEL LOPEZ ONTIVEROS. "DYNAMIC MODELING OF THE SUPPLY PROCESS AND LOAD DISTRIBUTION IN A CLEANING PRODUCTS FACTORY." DYNA MANAGEMENT 7, no. 1 (June 14, 2021): [12 p.]. http://dx.doi.org/10.6036/mn8975.

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Abstract In the present work a dynamic model is evaluated, the process of transfer of cleaning products in the expedition warehouse, the delay times present in the process and the adequacy of the flow of load and discharge with the rhythm of production. production of four different plants. This evaluation allows to determine the availability of the transport units according to the production requirement and to avoid the accumulation of the trips. As you can see, from the study of the times, 58.47% time is the product and 41.53% the time lost in the delays, on the other hand, it is considered feedback between the production plan and the process of transfer of finished product in the transport units, allows to determine in the complete system: production - loading and unloading of the stages of the process to hinder the continuous flow of the product and likewise to determine the real capacity of the transport units required. The main contribution of the present work is to determine by means of the simulation the percentage of compliance of the units of transport from the product requirement and analysis of the current capacity; this contributes to the decision making to implement improvement solutions, in this case, evaluated in two proposals: eliminate idle time and feed back the system for the availability of transport units with the requirement of the production program. Keywords: Process, system dynamics, production, delays, scenarios, improvement solutions, distribution

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Lin, Kuan-Yi, Tung-Sheng Chiang, Chian-Song Chiu, Wen-Fong Hu, and Peter Liu. "Observer-Based H ∞ Fuzzy Synchronization and Output Tracking Control of Time-Varying Delayed Chaotic Systems." Journal of Mathematics 2021 (September 15, 2021): 1–21. http://dx.doi.org/10.1155/2021/5918268.

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Tracking control for the output using an observer-based H ∞ fuzzy synchronization of time-varying delayed discrete- and continuous-time chaotic systems is proposed in this paper. First, from a practical point of view, the chaotic systems here consider the influence of time-varying delays, disturbances, and immeasurable states. Then, to facilitate a uniform control design approach for both discrete- and continuous-time chaotic systems, the dynamic models along with time-varying delays and disturbances are reformulated using the T-S (Takagi–Sugeno) fuzzy representation. For control design considering immeasurable states, a fuzzy observer achieves master-slave synchronization. Third, combining both a fuzzy observer for state estimation and a controller (solved from generalized kinematic constraints) output tracking can be achieved. To make the design more practical, we also consider differences of antecedent variables between the plant, observer, and controller. Finally, using Lyapunov’s stability approach, the results are sufficient conditions represented as LMIs (linear matrix inequalities). The contributions of the method proposed are threefold: (i) systemic and unified problem formulation of master-slave synchronization and tracking control for both discrete and continuous chaotic systems; (ii) practical consideration of time-varying delay, immeasurable state, different antecedent variables (of plant, observer, and controller), and disturbance in the control problem; and (iii) sufficient conditions from Lyapunov’s stability analysis represented as LMIs which are numerically solvable observer and controller gains from LMIs. We carry out numerical simulations on a chaotic three-dimensional discrete-time system and continuous-time Chua’s circuit. Satisfactory numerical results further show the validity of the theoretical derivations.

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Alanis, Alma Y., Jorge D. Rios, Javier Gomez-Avila, Pavel Zuniga, and Francisco Jurado. "Discrete-Time Neural Control of Quantized Nonlinear Systems with Delays: Applied to a Three-Phase Linear Induction Motor." Electronics 9, no. 8 (August 7, 2020): 1274. http://dx.doi.org/10.3390/electronics9081274.

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This work introduces a neural-feedback control scheme for discrete-time quantized nonlinear systems with time delay. Traditionally, a feedback controller is designed under ideal assumptions that are unrealistic for real-work problems. Among these assumptions, they consider a perfect communication channel for controller inputs and outputs; such a perfect channel does not consider delays, or noise introduced by the sensors and actuators even if such undesired phenomena are well-known sources of bad performance in the systems. Moreover, traditional controllers are also designed based on an ideal plant model without considering uncertainties, disturbances, sensors, actuators, and other unmodeled dynamics, which for real-life applications are effects that are constantly present and should be considered. Furthermore, control system design implemented with digital processors implies sampling and holding processes that can affect the performance; considering and compensating quantization effects of measured signals is a problem that has attracted the attention of control system researchers. In this paper, a neural controller is proposed to overcome the problems mentioned above. This controller is designed based on a neural model using an inverse optimal approach. The neural model is obtained from available measurements of the state variables and system outputs; therefore, uncertainties, disturbances, and unmodeled dynamics can be implicitly considered from the available measurements. This paper shows the performance and effectiveness of the proposed controller presenting real-time results obtained on a linear induction motor prototype. Also, this work includes stability proof for the whole scheme using the Lyapunov approach.

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Cunniffe, N. J., R. O. J. H. Stutt, F. van den Bosch, and C. A. Gilligan. "Time-Dependent Infectivity and Flexible Latent and Infectious Periods in Compartmental Models of Plant Disease." Phytopathology® 102, no. 4 (April 2012): 365–80. http://dx.doi.org/10.1094/phyto-12-10-0338.

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Compartmental models have become the dominant theoretical paradigm in mechanistic modeling of plant disease and offer well-known advantages in terms of analytic tractability, ease of simulation, and extensibility. However, underlying assumptions of constant rates of infection and of exponentially distributed latent and infectious periods are difficult to justify. Although alternative approaches, including van der Plank's seminal discrete time model and models based on the integro-differential formulation of Kermack and McKendrick's model, have been suggested for plant disease and relax these unrealistic assumptions, they are challenging to implement and to analyze. Here, we propose an extension to the susceptible, exposed, infected, and removed (SEIR) compartmental model, splitting the latent and infection compartments and thereby allowing time-varying infection rates and more realistic distributions of latent and infectious periods to be represented. Although the model is, in fact, more general, we specifically target plant disease by demonstrating how it can represent both the van der Plank model and the most commonly used variant of the Kermack and McKendrick (K & M) model (in which the infectivity response is delay Gamma distributed). We show how our reformulation retains the numeric and analytic tractability of SEIR models, and how it can be used to replicate earlier analyses of the van der Plank and K & M models. Our reformulation has the advantage of using elementary mathematical techniques, making implementation easier for the nonspecialist. We show a practical implication of these results for disease control. By taking advantage of the easy extensibility characteristic of compartmental models, we also investigate the effects of including additional biological realism. As an example, we show how the more realistic infection responses we consider interact with host demography and lead to divergent invasion thresholds when compared with the “standard” SEIR model. An ever-increasing number of analyses purportedly extract more biologically realistic invasion thresholds by adding additional biological detail to the SEIR model framework; we contend that our results demonstrate that extending a model that has such a simplistic representation of the infection dynamics may not, in fact, lead to more accurate results. Therefore, we suggest that modelers should carefully consider the underlying assumptions of the simplest compartmental models in their future work.

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Youcef-Toumi, K., and J. Bobbett. "Stability of Uncertain Linear Systems With Time Delay." Journal of Dynamic Systems, Measurement, and Control 113, no. 4 (December 1, 1991): 558–67. http://dx.doi.org/10.1115/1.2896458.

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The control of systems with uncertain dynamics and unpredictable disturbances has raised some challenging problems. This is particularly important when high system performance is to be guaranteed at all times. Recently, Time Delay Control has been suggested as an alternative control scheme. The proposed control system does not require an explicit plant model nor does it depend on the estimation of specific plant parameters. Rather, it combines adaptation with past observations to directly estimate the effect of the plant dynamics. This paper outlines the Time Delay Control law for a class of linear dynamic systems and then presents a sufficient condition for stability of linear uncertain systems with time delay. The ideas of Nyquist and Kharitonov are used in the development of a sufficient condition, which does not resort to using approximations for time delay. Like Nyquist, the condition depends on maps of the Nyquist path and, like Kharitonov, stability depends on four functions each yielding a stable system. In this paper we combine these ideas to determine the stability of systems where the Time Delay Controller is applied to single input single output, linear time-invariant plants whose coefficients are known to vary within certain defined intervals. The development is carried out in the context of Time Delay Control but it can be applied in more general cases. Two examples will illustrate the approach and the usefulness of the technique.

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Feliu-Batlle, Vicente, and Raul Rivas-Perez. "Smith predictor based fractional-order integral controller for robust temperature control in a steel slab reheating furnace." Transactions of the Institute of Measurement and Control 41, no. 16 (July 23, 2019): 4521–34. http://dx.doi.org/10.1177/0142331219862978.

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In this paper, a new strategy for robust control of temperature in a steel slab reheating furnace with large time delay uncertainty based on fractional-order controllers combined with a Smith predictor is proposed. A time delay model of the preheating zone of this process is used, obtained from an identification procedure applied in a real industrial furnace. It is shown that this process experiences very large time delay changes. A fractional-order integral controller embedded in a Smith predictor structure (FI-SP) is designed, which is robust to changes in such time delay. Simulated results of a standard Proportinal Integral Derivative (PID) controller, a PID controller embedded in a Smith predictor and the proposed FI-SP controller are compared. Six performance indexes have been used in this comparison. The analysis of these indexes shows that the designed FI-SP controller exhibits the most robust behavior (lowest indexes averaged in all the range of time delay variation) for ranges that include large time delays. Then the robustness features of the FI-SP controller outperform the other integer order controllers in the time responses both to set-point changes and to step disturbances. Therefore, this controller guarantees the best accuracy of temperature control. The designed FI-SP guarantees system stability and robust performance for a high range of plant time delay uncertainties.

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Kobayashi, Takahiro, and Tetsuji Tani. "Application of Cooperative Control to Petroleum Plants Using Fuzzy Supervisory Control and Model Predictive Multi-variable Control." Journal of Advanced Computational Intelligence and Intelligent Informatics 5, no. 6 (November 20, 2001): 333–37. http://dx.doi.org/10.20965/jaciii.2001.p0333.

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This paper describes hierarchical control with fuzzy supervisory control and model predictive multivariable control (MPC) in a petroleum plant. MPC is effective in time delay, interference, and handling constraints. Fuzzy logic controllers are effective for plants with large time delay and non-linearity. Our proposed hierarchical control combines their advantages. Fuzzy supervisory control, which determines set points for MPC, consists of an estimation block and a compensation block. We use a statistical model with multi-regression analysis for the estimation block to estimate parameters of plant operation, and fuzzy logic for the compensation block to correct output of the statistical model. Hierarchical control has been applied to an actual plant in an oil refinery, and showed satisfactory performance.

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Herve, SAMBA Aime, Yeremou Tamtsia Aurelien, and Nneme Nneme Leandre. "Performance evaluation of industrial ethernet protocols for real-time fault detection based adaptive observer in networked control systems with network communication constraints." IAES International Journal of Robotics and Automation (IJRA) 10, no. 3 (September 1, 2021): 261. http://dx.doi.org/10.11591/ijra.v10i3.pp261-274.

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<p>In this paper, the performance evaluation of industrial ethernet (EtherNet/IP, EtherCAT and PROFINET IRT) networks has been studied for choosing the right protocol in real-time fault detection based adaptive sliding mode observer in networked control systems (NCSs) under time network-induced delays, stochastic packet losses, access constraints and bounded disturbances. An adaptive sliding-mode observer based fault detection is presented. The dynamic hydroelectric power plant model is used to verify the effectiveness of the proposed method based on TrueTime and Matlab/ Simulink, corroborated our predictions that an ethernet for control automation technology (EtherCAT) protocol would be more appropriate to reduce the false alarm rate and increasing the efficiency of the remote control of industrial hydroelectric power plant.</p>

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Isukapati, Isaac K., Hana Rudová, Gregory J. Barlow, and Stephen F. Smith. "Analysis of Trends in Data on Transit Bus Dwell Times." Transportation Research Record: Journal of the Transportation Research Board 2619, no. 1 (January 2017): 64–74. http://dx.doi.org/10.3141/2619-07.

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Transit vehicles create special challenges for urban traffic signal control. Signal timing plans are typically designed for the flow of passenger vehicles, but transit vehicles—with frequent stops and uncertain dwell times—may have different flow patterns that fail to match those plans. Transit vehicles stopping on urban streets can also restrict or block other traffic on the road. This situation results in increased overall wait times and delays throughout the system for transit vehicles and other traffic. Transit signal priority (TSP) systems are often used to mitigate some of these issues, primarily by addressing delay to the transit vehicles. However, existing TSP strategies give unconditional priority to transit vehicles, exacerbating quality of service for other modes. In networks for which transit vehicles have significant effects on traffic congestion, particularly urban areas, the use of more-realistic models of transit behavior in adaptive traffic signal control could reduce delay for all modes. Estimating the arrival time of a transit vehicle at an intersection requires an accurate model of dwell times at transit stops. As a first step toward developing a model for predicting bus arrival times, this paper analyzes trends in automatic vehicle location data collected over 2 years and allows several inferences to be drawn about the statistical nature of dwell times, particularly for use in real-time control and TSP. On the basis of this trend analysis, the authors argue that an effective predictive dwell time distribution model must treat independent variables as random or stochastic regressors.

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Sadalla, Talar, Dariusz Horla, Wojciech Giernacki, and Piotr Kozierski. "Influence of time delay on fractional-order PI-controlled system for a second-order oscillatory plant model with time delay." Archives of Electrical Engineering 66, no. 4 (December 20, 2017): 693–704. http://dx.doi.org/10.1515/aee-2017-0052.

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Abstract The paper aims at presenting the influence of an open-loop time delay on the stability and tracking performance of a second-order open-loop system and continuoustime fractional-order PI controller. The tuning method of this controller is based on Hermite- Biehler and Pontryagin theorems, and the tracking performance is evaluated on the basis of two integral performance indices, namely IAE and ISE. The paper extends the results and methodology presented in previous work of the authors to analysis of the influence of time delay on the closed-loop system taking its destabilizing properties into account, as well as concerning possible application of the presented results and used models.

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Mirkin, Boris, and Per-Olof Gutman. "Robust Output-Feedback Model Reference Adaptive Control of SISO Plants With Multiple Uncertain, Time-Varying State Delays." IEEE Transactions on Automatic Control 53, no. 10 (November 2008): 2414–19. http://dx.doi.org/10.1109/tac.2008.2007534.

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Rieger, L., J. Alex, W. Gujer, and H. Siegrist. "Modelling of aeration systems at wastewater treatment plants." Water Science and Technology 53, no. 4-5 (February 1, 2006): 439–47. http://dx.doi.org/10.2166/wst.2006.100.

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A model for the response time of aeration systems at WWTPs is proposed. It includes the delays caused by the air supply system (consisting of blowers, throttles and pipes), the rise time of the air bubbles and all control loops except the master DO controller. Beside a description of the required step-change experiments, different approaches for model calibration are given depending on the available data. Moreover, the parameters for the oxygen transfer and the response time of the aeration system model are not clearly identifiable. The model can be used for simulation studies which compare different types of controllers under changing loading and process conditions. The results from full-scale experiments at three different plants show that the response times of the aeration systems are in the range of 4–5 min. Taking all processes and time constants into account, some 30 min are needed to reach a new steady state after a step change of the airflow rate.

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Lukasse, L. J. S., K. J. Keesman, A. Klapwijk, and G. van Straten. "A comparison of NH4/NO3 control strategies for alternating activated sludge processes." Water Science and Technology 39, no. 4 (February 1, 1999): 93–102. http://dx.doi.org/10.2166/wst.1999.0194.

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Four control strategies for N-removal in alternating activated sludge plants (ASP's) are compared: 1. timer-based, 2. switching the aeration on/off when depletion of nitrate/ammonium is detected, 3. switching the aeration on/off when ammonium crosses an upper/lower-bound, 4. the newly developed adaptive receding horizon optimal controller (ARHOC) as presented in Lukasse et al. (1997). The comparison is made by simulating the controllers' application to an alternating continuously-mixed activated sludge reactor preceded by a small anoxic reactor for predenitrification. The biological processes in the reactors are modelled by the activated sludge model no. 1. Realistic influent patterns, measured at a full-scale wastewater treatment plant, are used. The results show that three totally different controllers (timer-based, NH4-bounds based and ARHOC) can achieve a more or less equal effluent quality, if tuned optimally. The difference mainly occurs in the sensitivity to suboptimal tunings. The timer-based strategy has a higher aeration demand. The sensitivity of the ARHOC controller to sub-optimal tuning, known measurement time delays and changing plant loads is significantly less than that of the other controllers. Also its tuning is more natural and explicit.

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Chen, Weiwei, Peng Wang, Dan Wang, Min Shi, Yan Xia, Qiao He, Jiangbo Dang, Qigao Guo, Danlong Jing, and Guolu Liang. "EjFRI, FRIGIDA (FRI) Ortholog from Eriobotrya japonica, Delays Flowering in Arabidopsis." International Journal of Molecular Sciences 21, no. 3 (February 6, 2020): 1087. http://dx.doi.org/10.3390/ijms21031087.

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In the model species Arabidopsis thaliana, FRIGIDA (FRI) is a key regulator of flowering time and can inhibit flowering without vernalization. However, little information is available on the function in the Rosaceae family. Loquat (Eriobotrya japonica) belongs to the family Rosaceae and is a distinctive species, in which flowering can be induced without vernalization, followed by blooming in late-autumn or winter. To investigate the functional roles of FRI orthologs in this non-vernalization species, we isolated an FRI ortholog, dubbed as EjFRI, from loquat. Analyses of the phylogenetic tree and protein sequence alignment showed that EjFRI is assigned to eurosids I FRI lineage. Expression analysis revealed that the highest expression level of EjFRI was after flower initiation. Meanwhile, EjFRI was widely expressed in different tissues. Subcellular localization of EjFRI was only detected to be in the nucleus. Ectopic expression of EjFRI in wild-type Arabidopsis delayed flowering time. The expression levels of EjFRI in transgenic wild-type Arabidopsis were significantly higher than those of nontransgenic wild-type lines. However, the expression levels of AtFRI showed no significant difference between transgenic and nontransgenic wild-type lines. Furthermore, the upregulated AtFLC expression in the transgenic lines indicated that EjFRI functioned similarly to the AtFRI of the model plant Arabidopsis. Our study provides a foundation to further explore the characterization of EjFRI, and also contributes to illuminating the molecular mechanism about flowering in loquat.

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Chang, Pyung H., Jeong W. Lee, and Suk H. Park. "Time Delay Observer: A Robust Observer for Nonlinear Plants." Journal of Dynamic Systems, Measurement, and Control 119, no. 3 (September 1, 1997): 521–27. http://dx.doi.org/10.1115/1.2801288.

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Motivated by the idea of the time delay estimation used in the Time Delay Control, Time Delay Observer (TDO) has been constructed. Owing to this idea, TDO does not require a model, and hence is easy to design for nonlinear systems in the phase variable form, even when the plant dynamics is not well known. Not including a model, TDO turned out to be robust to parameter variations and computationally efficient; yet achieved better accuracy. For this observer, the convergence property and the sensitivity to sensor noise have been analyzed. Then, in a simulation with a nonlinear plant, and in an experiment with a robot, TDO achieved an accuracy level similar to sliding observer and better than a Kalman filter. In an experiment on a pneumatic cylinder control, TDO reconstructed states much better than a numerical differentiator with low-pass filtering.

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Journal articles on the topic 'Plant model with time delays'

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