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Journal articles on the topic 'Non minimum phase plant'

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Published: 4 June 2021
Last updated: 17 February 2022

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1

Antić, D., and S. Dimitrijević. "Non-minimum phase plant control using fuzzy sliding mode." Electronics Letters 34, no. 11 (1998): 1156. http://dx.doi.org/10.1049/el:19980827.

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2

Freeman, C., P. Lewin, and E. Rogers. "Phase-Lead Based Iterative Learning Control Implemented on a Non-Minimum Phase Plant." IFAC Proceedings Volumes 37, no. 14 (September 2004): 187–92. http://dx.doi.org/10.1016/s1474-6670(17)31102-3.

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3

TSAI, TE-PING, and TE-SHING WANG. "Optimal design of non-minimum-phase control systems with large plant uncertainty." International Journal of Control 45, no. 6 (June 1987): 2147–59. http://dx.doi.org/10.1080/00207178708933872.

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4

Mai, Nghia Thi, Kou Yamada, Takayuki Moki, Takaaki Hagiwara, and Fuminori Kanno. "Study on the Model Feedback Control System for a Class of Non-Minimum Phase Systems." Key Engineering Materials 497 (December 2011): 234–45. http://dx.doi.org/10.4028/www.scientific.net/kem.497.234.

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In the present paper, we examine model feedback control systems (MFCSs). Because MFCSis simple, the MFCS has been applied in many applications such as the trajectory control of robotmanipulators, serially connected water tanks, etc. The control structure of the MFCS is limited, butYamada and Moki reported about whether or not MFCS can represent all of the stabilizing controllersof a minimum phase plant. However, no research has been reported whether or not MFCS can representall of the stabilizing controllers of a non-minimum phase plant. The purpose of the present paper isto give a solution to the question as to whether or not all of the stabilizing controllers for a plantare expressible in the MFCS structure. The relation between MFCS and the parameterization of allstabilizing controllers for a class of non-minimum phase plants is shown. A simple design method tospecify control characteristics is also presented.
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5

BAKHTIAR, T. "PERFORMANCE LIMITATION OF SYSTEMS UNDER SIGNAL-TO-NOISE CONSTRAINED CHANNEL." Journal of Mathematics and Its Applications 5, no. 2 (December 1, 2006): 1. http://dx.doi.org/10.29244/jmap.5.2.1-12.

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This paper re-discusses [1] and [11], where the prob- lems of feedback stabilization over a signal-to-noise ratio (SNR) constrained channel are studied. The first paper considers both continuous and discrete-time minimum phase systems, while the second extends the results to non-minimum phase ones and pro- poses a linear time-varying feedback strategies to eliminate the effect of non-minimum phase zeros in SNR limited stabilization. In general, the limitations on the ability to stabilize a plant over an SNR constrained channel are imposed mainly by unstable poles and non-minimum phase zeros of the plant.
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6

Murakami, Iwanori, Nghia Thi Mai, Kou Yamada, Takaaki Hagiwara, Yoshinori Ando, and Hideharu Yamamoto. "A Design Method for Modified Smith Predictors for Non-Minimum-Phase Time-Delay Plants with Multiple Feedback-Connected Time-Delays." Applied Mechanics and Materials 36 (October 2010): 253–62. http://dx.doi.org/10.4028/www.scientific.net/amm.36.253.

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In this paper, we examine a design method for modified Smith predictors for non-minimum-phase time-delay plants with multiple feedback-connected time-delays. The Smith predictor is proposed by Smith to overcome time-delay and known as an effective time-delay compensator for a plant with large time-delay. The Smith predictor by Smith cannot be used for plants having an integral mode, because a step disturbance will result in a steady state error. Several papers considered the problem to design modified Smith predictors for unstable plants. However, no paper examines a design method for modified Smith predictors for non-minimum-phase time-delay plants with multiple feedback-connected time-delays. In this paper, we examine a design method for modified Smith predictors for non-minimum-phase time-delay plants with multiple feedback-connected time-delays.
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7

Hagiwara, Takaaki, Kou Yamada, Tatsuya Hoshikawa, Yuuto Karasawa, and Fuminori Kanno. "A Study on the Class of Model Feedback Controllers Formultiple-Input/Multiple-Output Non-Minimum Phase System." Key Engineering Materials 534 (January 2013): 182–94. http://dx.doi.org/10.4028/www.scientific.net/kem.534.182.

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In the present paper, we examine model feedback control systems (MFCSs). BecauseMFCS is simple, the MFCS has been applied in many applications such as the trajectorycontrol of robot manipulators, serially connected water tanks, etc. The control structure of theMFCS is limited, but Yamada and Moki reported about whether or not MFCS can representall stabilizing controllers of a minimum phase plant. However, no research has been reportedwhether or not MFCS can represent all stabilizing controllers of a non-minimum phase plant.The purpose of the present paper is to give a solution to the question as to whether or not allstabilizing controllers for a plant are expressible in the MFCS structure. The relation betweenMFCS and the parameterization of all stabilizing controllers for a class of non-minimum phasemultiple-input/multiple-output plants is shown. A simple design method to specify controlcharacteristics is also presented.
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8

Yuan, Jing. "Improving an adaptive controller for non-minimum phase plants." Automatica 38, no. 5 (May 2002): 869–73. http://dx.doi.org/10.1016/s0005-1098(01)00258-8.

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9

Campestrini, L., D. Eckhard, M. Gevers, and A. S. Bazanella. "Virtual Reference Feedback Tuning for non-minimum phase plants." Automatica 47, no. 8 (August 2011): 1778–84. http://dx.doi.org/10.1016/j.automatica.2011.04.002.

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10

OKAJIMA, Hiroshi, Gou ICHIMASA, and Nobutomo MATSUNAGA. "Design of Model Error Compensator for Non-minimum Phase Plants." Transactions of the Society of Instrument and Control Engineers 51, no. 11 (2015): 794–801. http://dx.doi.org/10.9746/sicetr.51.794.

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11

Jacobsen, Elling W. "On the dynamics of integrated plants—non-minimum phase behavior." Journal of Process Control 9, no. 5 (October 1999): 439–51. http://dx.doi.org/10.1016/s0959-1524(99)00007-4.

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12

TSYPKIN, YA Z. "Synthesis of optimal control systems for non-minimum phase plants." International Journal of Systems Science 23, no. 2 (February 1992): 291–96. http://dx.doi.org/10.1080/00207729208949207.

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13

HOROWITZ, ISAAC. "The singular-G method for unstable non-minimum-phase plants†." International Journal of Control 44, no. 2 (August 1986): 533–41. http://dx.doi.org/10.1080/00207178608933616.

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14

Goncalves da Silva, Gustavo R., Luciola Campestrini, and Alexandre S. Bazanella. "Multivariable Virtual Reference Feedback Tuning for Non-Minimum Phase Plants." IEEE Control Systems Letters 2, no. 1 (January 2018): 121–26. http://dx.doi.org/10.1109/lcsys.2017.2763824.

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15

Cai, Zhonglun, Chris T. Freeman, Paul L. Lewin, and Eric Rogers. "Iterative learning control for a non-minimum phase plant based on a reference shift algorithm." Control Engineering Practice 16, no. 6 (June 2008): 633–43. http://dx.doi.org/10.1016/j.conengprac.2007.07.001.

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16

Bucz, Štefan, Alena Kozáková, and Vojtech Veselý. "Robust guaranteed performance PID controller design for non-minimum phase plants." Journal of Electrical Engineering 69, no. 2 (March 1, 2018): 117–27. http://dx.doi.org/10.2478/jee-2018-0015.

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AbstractThe paper presents a new original robust PID design method for non-minimum phase plants to achieve closed-loop performance prescribed by the process technologist in terms of settling time and maximum overshoot, respectively. The proposed design procedure has two steps: first, the uncertain system is identified using external harmonic excitation signal with frequency, second, the controller of the nominal system is designed for specified gain margin. A couple of parameters is obtained from the time domain performance specification using quadratic regression curves, the so-called performance Bparabolas so, as to simultaneously satisfy robust closed-loop stability conditions. The main benefits of the proposed method are universal applicability for systems with both fast and slow dominant dynamics as well as performance specification using time domain criteria. The proposed PID design method has been verified on a set of benchmark systems.
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17

Chen, Wen-Hua, and Donald J. Ballance. "QFT design for uncertain non-minimum phase and unstable plants revisited." International Journal of Control 74, no. 9 (January 2001): 957–65. http://dx.doi.org/10.1080/00207170110044346.

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18

Sidi, Marcel. "Gain-bandwidth limitations of feedback systems with non-minimum-phase plants." International Journal of Control 67, no. 5 (January 1997): 731–44. http://dx.doi.org/10.1080/002071797223974.

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19

Zhou, Ya Li, Yi Xin Yin, Qi Zhi Zhang, and Woon Seng Gan. "Active Transient Vibration Control Using a Novel Repetitive Algorithm." Applied Mechanics and Materials 160 (March 2012): 258–62. http://dx.doi.org/10.4028/www.scientific.net/amm.160.258.

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In this paper, active control of periodic transient vibration based on repetitive control (RC) algorithm is studied. According to the stability condition of an active vibration control (AVC) system, a novel non-causal stable inversion approach combined with an optimal criterion is used to design the RC controller for an AVC system with a non-minimum phase secondary path. Computer simulations have been carried out to validate the effectiveness of the proposed algorithm. The plant model used in the computer simulations is obtained from a practical AVC system in our laboratory. Simulation results show that the proposed scheme can significantly reduce periodic transient vibration and the convergence rate is acceptable for a non-minimum phase plant.
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20

Matsuo, Ryota, Kazuhiro Yubai, Daisuke Yashiro, and Junji Hirai. "Data-driven Controller Tuning for Non-minimum Phase Plants with Stability Constraints." IEEJ Transactions on Electronics, Information and Systems 134, no. 12 (2014): 1802–8. http://dx.doi.org/10.1541/ieejeiss.134.1802.

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21

Porter, B., and A. H. Jones. "Time-Domain Identification of Non-Minimum Phase Characteristics of Linear Multivariable Plants." IFAC Proceedings Volumes 18, no. 5 (July 1985): 1743–46. http://dx.doi.org/10.1016/s1474-6670(17)60821-8.

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22

Freeman *, C. T., P. L. Lewin, and E. Rogers. "Experimental evaluation of iterative learning control algorithms for non-minimum phase plants." International Journal of Control 78, no. 11 (July 20, 2005): 826–46. http://dx.doi.org/10.1080/00207170500158565.

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23

Freeman, C., P. Lewin, and E. Rogers. "Experimental Evaluation of Simple Structure ILC Algorithms for Non-Minimum Phase Plants." IFAC Proceedings Volumes 37, no. 14 (September 2004): 199–204. http://dx.doi.org/10.1016/s1474-6670(17)31104-7.

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24

Zhu, Q. M., and K. Warwick. "A neural network enhanced generalized minimum variance self-tuning proportional, integral and derivative control algorithm for complex dynamic systems." Proceedings of the Institution of Mechanical Engineers, Part I: Journal of Systems and Control Engineering 216, no. 3 (May 1, 2002): 265–73. http://dx.doi.org/10.1177/095965180221600305.

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A neural network enhanced proportional, integral and derivative (PID) controller is presented that combines the attributes of neural network learning with a generalized minimum-variance self-tuning control (STC) strategy. The neuro PID controller is structured with plant model identification and PID parameter tuning. The plants to be controlled are approximated by an equivalent model composed of a simple linear submodel to approximate plant dynamics around operating points, plus an error agent to accommodate the errors induced by linear submodel inaccuracy due to non-linearities and other complexities. A generalized recursive least-squares algorithm is used to identify the linear submodel, and a layered neural network is used to detect the error agent in which the weights are updated on the basis of the error between the plant output and the output from the linear submodel. The procedure for controller design is based on the equivalent model, and therefore the error agent is naturally functioned within the control law. In this way the controller can deal not only with a wide range of linear dynamic plants but also with those complex plants characterized by severe non-linearity, uncertainties and non-minimum phase behaviours. Two simulation studies are provided to demonstrate the effectiveness of the controller design procedure.
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25

Ishihara, Tadashi, and Takahiko Ono. "Design of Critical Control Systems for Non-Minimum Phase Plants via LTR Technique." IEEJ Transactions on Electronics, Information and Systems 127, no. 5 (2007): 733–40. http://dx.doi.org/10.1541/ieejeiss.127.733.

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26

Saeki, Masami. "Loop recovery via ℋ∞-modified complementary sensitivity recovery for non-minimum phase plants." International Journal of Robust and Nonlinear Control 5, no. 7 (1995): 615–25. http://dx.doi.org/10.1002/rnc.4590050703.

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27

Ishihara, T., and H. J. Guo. "Partial LTR Design of Optimal Output Disturbance Cancellation Controllers for Non-Minimum Phase Plants." IFAC Proceedings Volumes 44, no. 1 (January 2011): 7903–8. http://dx.doi.org/10.3182/20110828-6-it-1002.01267.

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28

Song, Jay-Wook, and S. Jayasuriya. "Synthesis of Compensators for Robust Non-overshooting Step Responses in Uncertain, Minimum Phase Plants." IFAC Proceedings Volumes 26, no. 2 (July 1993): 543–46. http://dx.doi.org/10.1016/s1474-6670(17)49001-x.

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29

ISHIHARA, Tadashi. "Loop Transfer Recovery Techniques for Discrete-Time Non-Minimum Phase Plants with Feedback Delays." Interdisciplinary Information Sciences 2, no. 1 (1996): 47–62. http://dx.doi.org/10.4036/iis.1996.47.

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30

HOROWITZ, ISAAC, and ODED YANIV. "Quantitative design for SISO non-minimum-phase unstable plants by the singular-G method." International Journal of Control 46, no. 1 (July 1987): 281–94. http://dx.doi.org/10.1080/00207178708933898.

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31

Ishihara, Tadashi, Hai-Jiao Guo, and Hiroshi Takeda. "Integral controller design based on disturbance cancellation: Partial LTR approach for non-minimum phase plants." Automatica 41, no. 12 (December 2005): 2083–89. http://dx.doi.org/10.1016/j.automatica.2005.06.009.

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32

Amanatidou, E., G. Samiotis, E. Trikoilidou, G. Pekridis, and L. Tsikritzis. "Complete solids retention activated sludge process." Water Science and Technology 73, no. 6 (December 1, 2015): 1364–70. http://dx.doi.org/10.2166/wst.2015.614.

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In a slaughterhouse's full-scale extended aeration activated sludge wastewater treatment plant (WWTP), operating under complete solids retention time, the evolution of mixed liquor suspended solids (MLSS) and mixed liquor volatile suspended solids (MLVSS) concentration, food to micro-organisms ratio (F/M) and substrate utilization rate (SUR) were studied for over a year. Biomass growth phases in correlation to sludge biological and morphological characteristics were studied. Three distinguished growth phases were observed during the 425 days of monitoring. The imposed operational conditions led the process to extended biomass starvation conditions, minimum F/M, minimum SUR and predator species growth. MLSS and MLVSS reached a stabilization phase (plateau phase) where almost zero sludge accumulation was observed. The concept of degradation of the considered non-biodegradable particulate compounds in influent and in biomass (cell debris) was also studied. Comparison of evolution of observed sludge yields (Yobs) in the WWTP with Yobs predictions by activated sludge models verified the degradation concept for the considered non-biodegradable compounds. Control of the sedimentation process was achieved, by predicting the solids loading rate critical point using state point analysis and stirred/unstirred settling velocity tests and by applying a high return activated sludge rate. The nitrogen gas related sedimentation problems were taken into consideration.
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33

ISHII, Yuki, and Shiro MASUDA. "Fictitious Reference Iterative Tuning for Disturbance Attenuation Based on Variance Evaluation for Non-minimum Phase Plants." Transactions of the Society of Instrument and Control Engineers 52, no. 5 (2016): 249–56. http://dx.doi.org/10.9746/sicetr.52.249.

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34

GUO, Hai-Jiao, Tadashi ISHIHARA, and Hiroshi TAKEDA. "A Design of Discrete-Time Integral Controllers for Non-Minimum Phase Plants Using Partial LTR Technique." Transactions of the Society of Instrument and Control Engineers 31, no. 7 (1995): 844–52. http://dx.doi.org/10.9746/sicetr1965.31.844.

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35

Freeman, C., P. L. Lewin, and E. Rogers. "Further results on the experimental evaluation of iterative learning control algorithms for non-minimum phase plants." International Journal of Control 80, no. 4 (April 2007): 569–82. http://dx.doi.org/10.1080/00207170601136726.

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36

Salt, Julian, A. Sala, and Pedro Albertos. "A Transfer-Function Approach to Dual-Rate Controller Design for Unstable and Non-Minimum-Phase Plants." IEEE Transactions on Control Systems Technology 19, no. 5 (September 2011): 1186–94. http://dx.doi.org/10.1109/tcst.2010.2076386.

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37

Cajamarca, Byron, Óscar Camacho Quintero, Danilo Chávez, Paulo Leica, and Marcelo Pozo. "Sliding Mode Control Based on Internal Model for a Non-minimum phase Buck and Boost Converter." Enfoque UTE 10, no. 1 (March 29, 2019): 41–53. http://dx.doi.org/10.29019/enfoqueute.v10n1.442.

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This work presents the application of different schemes to control a non-minimum phase Buck-Boost converter. Three control schemes are used. The first controller presented is a PI controller, the second one is Sliding Mode Control and the third one is a combination of two control schemes, Internal Model Control and Sliding Mode Control. The controllers are designed from a Right-Half Plane Zero (RHPZ) reduced order model. The RHPZ model is converted, using Taylor approximation, in a First Order Plus Dead Time (FOPDT) model and after that, the controllers are obtained. The performance of the SMC-IMC is compared against to a PI controller and a SMC. The simulation results show that SMC-IMC improves the converter response, reducing the chattering and presenting better robustness for load changes
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38

Young, Jieh-Shian. "Synthesis of decoupling controller for non-minimum phase plants of different pole numbers on RHP within uncertainties." International Journal of Systems Science 42, no. 6 (June 2011): 939–50. http://dx.doi.org/10.1080/00207720903260184.

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39

Wang, Liuping, Chris T. Freeman, Eric Rogers, and David H. Owens. "Experimentally validated continuous-time repetitive control of non-minimum phase plants with a prescribed degree of stability." Control Engineering Practice 18, no. 10 (October 2010): 1158–65. http://dx.doi.org/10.1016/j.conengprac.2010.06.004.

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40

Kim, Wonhee, and Sangmin Suh. "Optimal Disturbance Observer Design for High Tracking Performance in Motion Control Systems." Mathematics 8, no. 9 (September 21, 2020): 1633. http://dx.doi.org/10.3390/math8091633.

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In this paper, a stability-driven optimal disturbance observer (DO) is proposed. The proposed method does not require any plant inverse dynamics to detect introduced disturbances or a stabilizing Q filter. It does not require additional compensators to resolve causality problems, due to the relative degree, or filters to solve instability problems of non-minimum phase plants. Using this method enables wideband and narrowband disturbances to be attenuated by simply multiplying the corresponding peak filters by the baseline weight function. Furthermore, the proposed DO guarantees the stability of closed-loop systems because the already designed outer-loop systems are considered as a target plant to be stabilized and because of the Lyapunov stability-based H∞ control. In the application example, it was confirmed that the proposed method is effective, and the position error signals were improved by 20.9% in commercial hard disk drives and 36.6% in optical image stabilization systems.
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41

Shaheed, M. H., H. Poerwanto, and M. O. Tokhi. "Adaptive Inverse-Dynamic and Neuro-Inverse-Dynamic Active Vibration Control of a Single-Link Flexible Manipulator." Proceedings of the Institution of Mechanical Engineers, Part I: Journal of Systems and Control Engineering 219, no. 6 (September 1, 2005): 431–48. http://dx.doi.org/10.1243/095965105x33554.

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This paper presents investigations into the development of adaptive inverse-dynamic and neuro-inverse-dynamic control strategies for a flexible manipulator system employing a combined collocated and non-collocated control structure. Collocated control is utilized to track the position of the system while the non-collocated inverse and neuro-inverse control are utilized to reduce the vibration of the system. The controllers are developed in two phases: a collocated position control loop using proportional-derivative feedback control is developed and combined first with an adaptive inverse non-collocated control loop using a recursive least-squares algorithm and then with a neuro-inverse model using a multi-layered perceptron neural network. The problem of instability of the non-collocated control loop arising from the non-minimum phase characteristics of the plant is solved in the former case by reflecting the non-invertible plant zeros into the stability region. In the case of the neuro-inverse model, the problem of instability of the control loop is accounted for through the neuro-inverse learning process. The performances of both the proposed control strategies are assessed within a simulation environment of a single-link flexible manipulator and it is demonstrated that a significant reduction in the level of structural vibration of the system is achieved with both techniques. The significance of the neuro-inverse model approach in achieving stable control is demonstrated.
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42

Horn, Joseph. "Non-Linear Dynamic Inversion Control Design for Rotorcraft." Aerospace 6, no. 3 (March 18, 2019): 38. http://dx.doi.org/10.3390/aerospace6030038.

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Flight control design for rotorcraft is challenging due to high-order dynamics, cross-coupling effects, and inherent instability of the flight dynamics. Dynamic inversion design offers a desirable solution to rotorcraft flight control as it effectively decouples the plant model and effectively handles non-linearity. However, the method has limitations for rotorcraft due to the requirement for full-state feedback and issues with non-minimum phase zeros. A control design study is performed using dynamic inversion with reduced order models of the rotorcraft dynamics, which alleviates the full-state feedback requirement. The design is analyzed using full order linear analysis and non-linear simulations of a utility helicopter. Simulation results show desired command tracking when the controller is applied to the full-order system. Classical stability margin analysis is used to achieve desired tradeoffs in robust stability and disturbance rejection. Results indicate the feasibility of applying dynamic inversion to rotorcraft control design, as long as full order linear analysis is applied to ensure stability and adequate modelling of low-frequency dynamics.
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43

Sadigh, Mohammad Jafar, and Saeed Mansouri. "Application of phase-plane method in generating minimum time solution for stable walking of biped robot with specified pattern of motion." Robotica 31, no. 6 (February 21, 2013): 837–51. http://dx.doi.org/10.1017/s0263574713000039.

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SUMMARYWalking with a maximum speed is an interesting subject in the field of biped motion. Giving an answer to the question of “what is the maximum achievable speed of a certain biped walking with a physically acceptable pattern?” is the main objective of this work. In this paper, minimum time motion of biped was studied during one step that consists of single support phase (SSP) and double support phase (DSP). The minimum time problem is formulated with stability and non-slip conditions along with actuator limits expressed as some inequality constraints. In addition, certain kinematic constraints in terms of hip joint position are considered that ensure an acceptable walking pattern. A phase-plane technique is used to find the minimum time solution. A numerical simulation is given to shed some light on how the proposed method works. Validity and effectiveness of the method are verified by comparing the results with those of other researches.
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44

Liu, Liang Yih, and Hsiung Cheng Lin. "Achieving Passive Integral Control Using Feedback and Output Redefinition." Applied Mechanics and Materials 284-287 (January 2013): 2199–204. http://dx.doi.org/10.4028/www.scientific.net/amm.284-287.2199.

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There exist an infinite number of right-half plane zeros in the transfer function relating the joint torque input to the tip contact force output for a constrained single-link flexible arm. Since the non-minimum phase nature is the cause of instability or stability but caused the smaller control bandwidth. In order to overcome the inherent limitations caused by the non-minimum phase nature, a new input induced by the measurement of joint angular acceleration and a output generated using the measurements of contact force and root shear force are defined. A necessary and sufficient condition is derived such that all poles and zeros of the new transfer function lie on the imaginary axis. The passive integral control is designed to accomplish the regulation of the contact force. The excellent performance of the passive integral controller is verified through numerical simulations.
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45

Robnik, Jakob, and Uroš Seljak. "Matched filtering with non-Gaussian noise for planet transit detections." Monthly Notices of the Royal Astronomical Society 504, no. 4 (April 26, 2021): 5829–39. http://dx.doi.org/10.1093/mnras/stab1178.

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ABSTRACT We develop a method for planet detection in transit data, which is based on the matched filter technique, combined with the Gaussianization of the noise outliers. The method is based on Fourier transforms and is as fast as the existing methods for planet searches. The Gaussianized matched filter (GMF) method significantly outperforms the standard baseline methods in terms of the false positive rate, enabling planet detections at up to 30 per cent lower transit amplitudes. Moreover, the method extracts all the main planet transit parameters, amplitude, period, phase, and duration. By comparison to the state-of-the-art Gaussian process methods on both simulations and real data, we show that all the transit parameters are determined with an optimal accuracy (no bias and minimum variance), meaning that the GMF method can be used for both the initial planet detection and the follow-up planet parameter analysis.
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46

Quan, Qian Qian. "The Design and Simulation of Predictive Control Algorithm Achieved by the DCS Algorithm Module Combination." Applied Mechanics and Materials 130-134 (October 2011): 175–78. http://dx.doi.org/10.4028/www.scientific.net/amm.130-134.175.

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This paper proposes a design method and parameter tuning method for how only using the DCS configuration control software module to combine and achieve generalized predictive control algorithm in a complicated controlled plant case. In order to show the effectiveness of the control algorithm using the DCS layer control software module to achieve model predictive, two types of complex objects are considered as example to do simulation : non-minimum phase process and the complex process with recycling and pure delay. The simulation results show that the proposed control algorithm can provide similar control performance of GPC.
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47

Jones, J. C. Peyton, and D. P. Atherton. "Root Locus Diagrams and the Effect of Zeros on System Response." International Journal of Electrical Engineering & Education 34, no. 1 (January 1997): 48–69. http://dx.doi.org/10.1177/002072099703400106.

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New expressions, and a graphical notation are introduced to quantify the effect of zeros on step response characteristics. The expressions, which also hold for non-minimum phase systems, are illustrated geometrically in the s-plane, and give a more accurate insight into a concept of pole dominance than the standard ‘pure-pole’ approximations.
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48

Ali, A., T. Khalik, and A. Ahmad. "Response of Leaf Area Index, Vegetative and Reproductive Phases of Two Cotton (Gossypium Hirsutum L.) Cultivars at Different Regimes of Irrigation Scheduling." Cercetari Agronomice in Moldova 47, no. 1 (March 1, 2014): 31–37. http://dx.doi.org/10.2478/cerce-2014-0004.

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ABSTRACT The experiment was conducted to investigate the effects of different regimes of irrigation schedule on various vegetative and reproductive stages of cotton crop. The results showed that irrigation effect was non significant for number of plants m-2, while I4 treatment produced maximum number of monopodial branches 2.18, but statistically it was at par with I3, I5. I4 treatment showed maximum number of sympodial branches (20.43), followed by I3 (18.63). F.H-900 showed statistically higher sympodial branches (18.34) than the F.H-901 (17.08). Maximum number of flowers per plant was formed in the I4 treatment (101.00), followed by I3 (96.31) and 15 (92.23). Significantly higher number of flowers and boll drops was recorded in treatment I1, followed by I2. Flowers and boll drop per plant decrease with increase in irrigations applied to crop. Minimum number of flowers (60.45) and bolls (16.98) dropped per plant were in I4 and 13 (65.0 and 22.72, respectively).
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49

Wu, Jie, Xi-Sheng Zhan, Xian-He Zhang, Tao Han, and Hong-Liang Gao. "Performance limitation of networked systems with controller and communication filter co-design." Transactions of the Institute of Measurement and Control 40, no. 4 (November 30, 2016): 1167–76. http://dx.doi.org/10.1177/0142331216678314.

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This paper addresses the performance limitation problem of networked systems by co-designing the controller and communication filter. The tracking performance index is measured by the energy of the error signal. Explicit expressions of the performance limitation are obtained by applying the controller and communication filter co-design, and the optimal network filter is obtained by applying the frequency domain method. It is shown that the performance limitation is closely related to the unstable poles and the non-minimum phase zeros of a given plant under the one-parameter compensator structure, whereas, under the two-parameter compensator structure, the performance limitation is unrelated to the unstable poles of a given plant. It is also demonstrated that the performance limitation can be improved and the effect of the channel noise can be eliminated by using the controller and communication filter co-design. Finally, some typical examples are presented to illustrate the theoretical results.
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50

Lee, Young Sup. "Effect of Integral Feedback Control Forbeam Tip Pointing." Advanced Materials Research 717 (July 2013): 541–45. http://dx.doi.org/10.4028/www.scientific.net/amr.717.541.

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This paper presents the effect of an integral feedback controller for minimizing the pointing error at the tip of a very flexible and slender cantilever beam to follow a command signal. A piezoeletric PZT actuator patch isbonded on near the clamped end of the cantilever beam. Also it is considered that a position sensor is located near the tip of the beam but it is not attached on the beam. The beam is designed to be lightly damped and its step response withoutcontrol is quite long. But because of the non-collocation of the sensor and actuator, the plant response is non-minimum phase. After an intensive computer simulation, it is noted that the integral controller can reduce the settling time with proper stability and control gains. Also an analysis and comparison of the integral controller with a proportional-integral controller for the pointing error minimization of the very flexible and slender beam is described in detail.
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