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Journal articles on the topic 'Smith Predictor'

Author: Grafiati

Published: 4 June 2021

Last updated: 6 February 2022

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1

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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2

Yamada, Kou, Nghia Thi Mai, Yoshinori Ando, Takaaki Hagiwara, Iwanori Murakami, and Tatsuya Hoshikawa. "A Design Method for Stabilizing Modified Smith Predictors for Multiple-Input/Multiple-Output Time-Delay Plants." Key Engineering Materials 459 (December 2010): 221–33. http://dx.doi.org/10.4028/www.scientific.net/kem.459.221.

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The modified Smith predictor is well known as an effective time-delay compensator for a plant with large time-delays, and several papers on the modified Smith predictor have been published. The parameterization of all stabilizing modified Smith predictors for single-input/single-output time-delay plants is obtained by Yamada et al. However, they do not examine the parameterization of all stabilizing modified Smith predictors for multiple-input/multiple-output time-delay plants. The purpose of this paper is to expand the result by Yamada et al. and to propose the parameterization of all stabilizing modified Smith predictors for multiple-input/multiple-output time-delay plants. Control characteristics of the control system using obtained parameterization of all stabilizing modified Smith predictors are also given. Finally, a numerical example is illustrated to show the effectiveness of proposed parameterization of all stabilizing modified Smith predictors.

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3

Mai, Nghia Thi, Kou Yamada, Yoshinori Ando, Iwanori Murakami, and Tatsuya Hoshikawa. "A Design Method for Two-Degree-of-Freedom Modified Smith Predictors for Multiple-Input/Multiple-Output Time-Delay Plants." Key Engineering Materials 497 (December 2011): 221–33. http://dx.doi.org/10.4028/www.scientific.net/kem.497.221.

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The modified Smith predictor is well known as an effective time-delay compensator fora plant with large time-delays, and several papers on the modified Smith predictor have been published.Recently, the parameterization of all stabilizing modified Smith predictors for time-delay plantswas obtained by Yamada et al. But, their method cannot specify the input-output characteristic andthe feedback characteristic separately. From the practical point of view, it is desirable that the inputoutputcharacteristic and the feedback characteristic are specified separately. In this paper, we proposethe parameterization of all stabilizing two-degree-of-freedom modified Smith predictors for multipleinput/multiple-output time-delay plants.

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4

Dumitrache, Ion, and Ioana Mihu. "Rule-Based Smith Predictor Controller." IFAC Proceedings Volumes 33, no. 25 (September 2000): 329–33. http://dx.doi.org/10.1016/s1474-6670(17)39361-8.

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5

Sourdille, Pauline, and Aidan O’Dwyer. "New modified smith predictor designs." IFAC Proceedings Volumes 36, no. 19 (September 2003): 77–82. http://dx.doi.org/10.1016/s1474-6670(17)33305-0.

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6

Zhang, Haitao, and Zhen Li. "Fuzzy Immune Control Based Smith Predictor for Networked Control Systems." International Journal of Engineering and Technology 3, no. 1 (2011): 81–84. http://dx.doi.org/10.7763/ijet.2011.v3.204.

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7

Li, Shu De, Yi Chen, and Cai Xia Liu. "Smith Predictor Based on Predicting Induced-Delay." Advanced Materials Research 201-203 (February 2011): 2003–6. http://dx.doi.org/10.4028/www.scientific.net/amr.201-203.2003.

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Since communication network is introduced into control system, induced-delay appears. Because of the delay, the performance of networked control system becomes bad, even unsteady. Conventional Smith predictor is sensitive to error in object model and needs delay’s value in advance. Regarding random delay, its application is limited. In this paper, we propose a method based on induced-delay predicted by BP neural network, which use two historical delay values to predict the next one. Smith predictor adjusts its parameters according to that value in time. The simulating results indicate that the precision of delay-predicting can be ensured and the performance of networked control system has been improved.

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8

Tao, Laihua, Shian Chen, Guisheng Fang, and Guanghao Zu. "Smith Predictor-Taylor Series-Based LQG Control for Time Delay Compensation of Vehicle Semiactive Suspension." Shock and Vibration 2019 (June 12, 2019): 1–12. http://dx.doi.org/10.1155/2019/3476826.

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A Smith predictor-Taylor series-based LQG (STLQG) control to compensate time delay of a semiactive suspension system is newly presented. This control consists of a Taylor series-based LQG (TLQG) control and a Smith predictor based on the TLQG. The TLQG control compensates one half of time delay to decrease magnification from whole time delay compensation. The Smith predictor based on the TLQG compensates the other half to decrease horizontal shift from whole time delay compensation using the Smith predictor-based LQG. Finally, a practical case illustrates advantages of the STLQG control.

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9

Zhang, Fei, Li Feng Ye, Wen Quan Sun, and Xiao Huai Ren. "Research of Smith Monitor AGC Based on Active Disturbance Rejection Control." Advanced Materials Research 572 (October 2012): 49–54. http://dx.doi.org/10.4028/www.scientific.net/amr.572.49.

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In response to the characteristics of large time delay, nonlinear, various disturbances in Monitor AGC system for cold rolling mill, a control strategy combining Smith predictor with Active Disturbance Rejection Control (ADRC) is proposed. Approximation ability of Extended State Observer (ESO) to estimate unknown parts of controlled plant model is promoted by model compensated ADRC. Aimed at a 4-high cold rolling mill, simulation analysis for classical Smith predictor monitor AGC and ADRC-Smith predictor Monitor AGC is used. The results indicate that ADRC-Smith predictor Monitor AGC has better performance on robustness and capacity of anti-disturbance.

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10

Sang, Shiqing, and Pengcheng Nie. "Modified Smith Predictor Based on H 2 and Predictive PI Control Strategy." Mathematical Problems in Engineering 2021 (August 9, 2021): 1–17. http://dx.doi.org/10.1155/2021/7228637.

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In this paper, a new type of modified Smith predictor based on the H 2 and predictive PI control strategy is proposed. The modified Smith predictor not only has H 2 robust performance but also has a similar predictive PI control structure. By introducing a time delay term, the modified Smith predictor controller overcomes the shortcoming that the conventional control algorithm can only use the low-order approximation of time delay term to design the control algorithm. The modified Smith predictor controller’s output is related to the current system error and related to the output in a period before the controller. Simultaneously, the modified Smith predictor controller is applied to conventional process systems based on dynamic optimization estimation in the case study to show absolute superiority over the nonpredictive control method (such as the classical PID control method).

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11

Léonard, F. "Tuning of a Modified Smith Predictor." IFAC Proceedings Volumes 31, no. 18 (July 1998): 539–42. http://dx.doi.org/10.1016/s1474-6670(17)42047-7.

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12

Habermayer, M. "Robustness Properties of Smith Predictor Control." IFAC Proceedings Volumes 24, no. 3 (July 1991): 1173–78. http://dx.doi.org/10.1016/s1474-6670(17)52509-4.

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13

Hung, Shih-Bo, Cheng-Ching Yu, and Yu-Chang Cheng. "A Smith Predictor Enhanced PID Controller." IFAC Proceedings Volumes 37, no. 9 (July 2004): 661–66. http://dx.doi.org/10.1016/s1474-6670(17)31885-2.

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14

Miall, R. C., D. J. Weir, D. M. Wolpert, and J. F. Stein. "Is the Cerebellum a Smith Predictor?" Journal of Motor Behavior 25, no. 3 (September 1993): 203–16. http://dx.doi.org/10.1080/00222895.1993.9942050.

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15

LAUGHLIN, DANIEL L., DANIEL E. RIVERA, and MANFRED MORARI. "Smith predictor design for robust performance." International Journal of Control 46, no. 2 (August 1987): 477–504. http://dx.doi.org/10.1080/00207178708933912.

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16

Sigurd Skogestad, Chriss Grimholt. "Should we forget the Smith Predictor?" IFAC-PapersOnLine 51, no. 4 (2018): 769–74. http://dx.doi.org/10.1016/j.ifacol.2018.06.203.

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17

Tian, Zi De. "Algorithm and Implementation of Smith Predictive Control." Applied Mechanics and Materials 687-691 (November 2014): 60–63. http://dx.doi.org/10.4028/www.scientific.net/amm.687-691.60.

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With invariable time delay theoretically,Smith predictor is deeply studied,the fact that the Smith predictor depends on the math model of the system is found ,and so it is very difficult to control the time-varying delay system well. Therefore,it is necessary to take an effective method--using PID controller with the digital Smith predictor,and studying its control algorithm,and doing the simulation in the lab of micro-computer control. Simulation results have proved the efficiency of the algorithm and the validity.

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18

Xie, Yu Dong, Yan Jun Liu, and Yong Wang. "Design of Cascade-Smith Hybrid Control Structure for Pressure Control." Key Engineering Materials 419-420 (October 2009): 797–800. http://dx.doi.org/10.4028/www.scientific.net/kem.419-420.797.

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A new hybrid-control structure for the compensation of the volume-delay negative effect in the mixed-gas pressure control is designed. The volume-delay mechanism is discussed. A Smith predictor is used in the primary loop of a cascade control system where the secondary loop has a negligible delay while the primary loop has a significant and variant delay. To deal with the sensitivity of Smith predictor to modeling error, the gas pipe model for the Smith predictor can be updated by measuring the gas pressure and choosing the model characteristics through a lookup table. The results show that the proposed control structure brings together the best merits of a cascade control and the Smith predictor structure, and it can provide a better performance than the traditional cascade control.

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19

Chen, Guangda, Dejun Liu, Yongxin Mu, Jinfei Xu, and Yanming Cheng. "A Novel Smith Predictive Linear Active Disturbance Rejection Control Strategy for the First-Order Time-Delay Inertial System." Mathematical Problems in Engineering 2021 (March 24, 2021): 1–13. http://dx.doi.org/10.1155/2021/5560123.

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The control strategy research of the time-delay system is a focused issue in the control field. In order to furthermore improve the performance of the first-order time-delay inertial system, firstly, a new Smith predictor structure is proposed, which solves the constraint that the conventional Smith predictor needs to match the actual object model. Secondly, the performance and parameter function of the new Smith predictor are discussed in theory to provide the basis for parameter tuning. Finally, a new Smith predictor combined with linear active disturbance rejection control (LADRC) is proposed to solve the problem that the two input signals of the linear extended state observer (LESO) are not synchronized on the time scale, and the stability of the new Smith + LADRC time-delay control system is proved theoretically for known and unknown controlled complex objects. Simulation analysis is conducted to verify the robustness of the proposed strategy under the condition of the different parameters. The results indicate that the proposed strategy has better performance than the conventional method in response speed, overshoot, adjustment time, and stability.

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20

Hu, Qiuping, Jian-Xin Xu, and Tong Heng Lee. "Iterative learning control design for Smith predictor." Systems & Control Letters 44, no. 3 (October 2001): 201–10. http://dx.doi.org/10.1016/s0167-6911(01)00142-6.

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21

Guanghui, Zhang, Qian Feng, and Shao Huihe. "Robust tuning method for modified smith predictor." Journal of Systems Engineering and Electronics 18, no. 1 (March 2007): 89–94. http://dx.doi.org/10.1016/s1004-4132(07)60057-7.

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22

Hwang, Su-Hwan, Keum-Shik Hong, and Kyung-Tae Hong. "Modified Smith Predictor Design for a Reclaimer." IFAC Proceedings Volumes 36, no. 24 (October 2003): 169–74. http://dx.doi.org/10.1016/s1474-6670(17)37623-1.

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23

Deltour, Jean-Luc, and Franck Sanfilippo. "Introduction of Smith Predictor into Dynamic Regulation." Journal of Irrigation and Drainage Engineering 124, no. 1 (January 1998): 47–52. http://dx.doi.org/10.1061/(asce)0733-9437(1998)124:1(47).

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24

Miya, Hassan Sabo, Rosdiazli Bin Ibrahim, Nordin Bin Saad, Vijanth Sagayan Asirvadam, and Tran Duc Chung. "WirelessHART Process Control with Smith Predictor Compensator." Advanced Science Letters 22, no. 10 (October 1, 2016): 2676–80. http://dx.doi.org/10.1166/asl.2016.7003.

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25

Bazhanov, V. L. "Smith predictor in digital feedback control systems." Automation and Remote Control 71, no. 8 (August 2010): 1695–704. http://dx.doi.org/10.1134/s0005117910080175.

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26

Smith, L. "Modified Smith predictor for extruded diameter control." Computing & Control Engineering Journal 10, no. 2 (April 1, 1999): 57–62. http://dx.doi.org/10.1049/cce:19990204.

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27

Hang, C. C., and B. W. Chong. "A Dual-Rate Adaptive Digital Smith Predictor." IFAC Proceedings Volumes 20, no. 5 (July 1987): 115–20. http://dx.doi.org/10.1016/s1474-6670(17)55487-7.

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28

Habermayer, M. "Quality Investigation of an Adaptive Smith Predictor." IFAC Proceedings Volumes 20, no. 12 (September 1987): 211–15. http://dx.doi.org/10.1016/s1474-6670(17)55632-3.

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29

Nortcliffe, Anne, and Jonathan Love. "Varying time delay Smith predictor process controller." ISA Transactions 43, no. 1 (January 2004): 61–71. http://dx.doi.org/10.1016/s0019-0578(07)60020-2.

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30

Blanchini, Franco, Daniele Casagrande, Stefano Miani, and Umberto Viaro. "Stable LPV realisation of the Smith predictor." International Journal of Systems Science 47, no. 10 (February 16, 2015): 2393–401. http://dx.doi.org/10.1080/00207721.2014.998319.

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31

Hang, C. C., K. W. Lim, and B. W. Chong. "A dual-rate adaptive digital smith predictor." Automatica 25, no. 1 (January 1989): 1–16. http://dx.doi.org/10.1016/0005-1098(89)90115-5.

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32

Tan, Yonghong, and Achiel Van Cauwenberghe. "Nonlinear neural controller with neural Smith predictor." Neural Processing Letters 1, no. 2 (June 1994): 24–27. http://dx.doi.org/10.1007/bf02310939.

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33

Xie, Pei Zhang, and Xing Peng Zhou. "Research on Chlorine Dosing Control Based on Adaptive Generalized Predictive Control." Applied Mechanics and Materials 415 (September 2013): 89–94. http://dx.doi.org/10.4028/www.scientific.net/amm.415.89.

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Chlorine dosing is a complicated system with time delay, time-varying, non-linear and coupling. In this paper, multivariable adaptive generalized predictive controller based on Smith predictor is proposed. Instead of the optimal predictor, the Smith predictor with adaptive identifying parameters can increase the robustness of the MIMO system. Simulation and application in water-works at Suzhou (China) shows that the algorithm can overcome time-varying, time delay and disturbance.

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34

Huba, Mikuláš, and Igor Bélai. "Limits of a simplified controller design based on integral plus dead time models." Proceedings of the Institution of Mechanical Engineers, Part I: Journal of Systems and Control Engineering 232, no. 6 (February 28, 2018): 728–41. http://dx.doi.org/10.1177/0959651818755957.

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This article presents design and evaluation of filtered proportional–integral controllers and filtered Smith predictor–inspired constrained dead time compensators. Both are based on the integral plus dead time and on the first-order time delayed plant models. They are compared as for tuning simplicity, robustness and noise attenuation. Such a comparison, which presents a robustness test regarding the importance of the internal plant feedback approximation, may be carried out by performance measures built on deviations of the input and output transient responses from their ideal shapes. When combined with integral of absolute error measures of both solution types with the disturbance responses set as nearly equivalent, we can see that the filtered Smith predictor setpoint responses may be significantly faster than the filtered proportional–integral controller responses, more robust and, using higher-order filters, also sufficiently smooth. Furthermore, tuning of the possibly higher-order filters for filtered Smith predictor is simpler. Its overall design is more transparent and straightforward with respect to the control constraints, where the filtered Smith predictor requires some additional anti-windup measures.

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35

Li, Shi Zhe, Yong Guang Ma, and Zheng Zhao. "Simulation and Analysis to Control Algorithms of the Large Time-Delay System Based on Simulink." Advanced Materials Research 532-533 (June 2012): 654–58. http://dx.doi.org/10.4028/www.scientific.net/amr.532-533.654.

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Because of the universal existence of time-delay phenomenon in industrial process control, this paper analyzes the characteristics of two kinds of control methods, discusses the relations between general control algorithm and Smith predictor compensation, and simulated studies the mismatch of model, the change of delay time and the effect of the disturbance to the system. Simulation results show that: improved Smith predictor controller has the advantages of fast response and low overshoot. Especially in the case of the mismatch of model, it has better robustness and stronger anti-interference ability. The improved Smith predictor brings a good quality, which has little sensitivity to the model parameters. It provides a kind of method to overcome the time delay.

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36

Tolu, Silvia, Marie Claire Capolei, Lorenzo Vannucci, Cecilia Laschi, Egidio Falotico, and Mauricio Vanegas Hernández. "A Cerebellum-Inspired Learning Approach for Adaptive and Anticipatory Control." International Journal of Neural Systems 30, no. 01 (November 27, 2019): 1950028. http://dx.doi.org/10.1142/s012906571950028x.

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The cerebellum, which is responsible for motor control and learning, has been suggested to act as a Smith predictor for compensation of time-delays by means of internal forward models. However, insights about how forward model predictions are integrated in the Smith predictor have not yet been unveiled. To fill this gap, a novel bio-inspired modular control architecture that merges a recurrent cerebellar-like loop for adaptive control and a Smith predictor controller is proposed. The goal is to provide accurate anticipatory corrections to the generation of the motor commands in spite of sensory delays and to validate the robustness of the proposed control method to input and physical dynamic changes. The outcome of the proposed architecture with other two control schemes that do not include the Smith control strategy or the cerebellar-like corrections are compared. The results obtained on four sets of experiments confirm that the cerebellum-like circuit provides more effective corrections when only the Smith strategy is adopted and that minor tuning in the parameters, fast adaptation and reproducible configuration are enabled.

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37

Nguyen, Tai Trong, and Thanh Van Dao. "Study of adaptive Fuzzy Smith control for time-delay systems." Science and Technology Development Journal 18, no. 3 (August 30, 2015): 143–49. http://dx.doi.org/10.32508/stdj.v18i3.895.

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In this paper, an adaptive Fuzzy Smith control method is presented to control the varying time delay systems. Based on the online parameter estimation, Smith predictor can be updated online which can eliminate the time delay element. This method overcame the shortcomings that control effect of conventional Smith predictor will be worse when the parameters of time delay systems change. Furthermore, an adaptive fuzzy controller adjusts online the PID control parameters to improve the control performance. Simulation results show the effectiveness of the proposed method.

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38

Yang, Zhi Gang, and Jun Lei Qian. "PID Neural Network Smith Predictive Control for a Control System with Time Delay." Applied Mechanics and Materials 300-301 (February 2013): 1533–39. http://dx.doi.org/10.4028/www.scientific.net/amm.300-301.1533.

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According to the time delay in industrial control objects, the PID neural network control method and Smith predictor compensation principle are combined to form the PIDNN-Smith control algorithm. Namely, in Smith predictor compensation control system, the PIDNN as the controller, using the PIDNN neural network on-line self-learning function to tune weight value, make the implicit layers of proportion, integral and differential neurons to achieve the best combination, thus overcome disadvantages of the conventional PID algorithm that does not adapt to the control of large delay system and conventional Smith algorithm depended too much on model precision of the defect. Simulation results show strong robustness and good control quality of this algorithm.

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39

Rodríguez, C., J. E. Normey-Rico, J. L. Guzmán, and M. Berenguel. "On the filtered Smith predictor with feedforward compensation." Journal of Process Control 41 (May 2016): 35–46. http://dx.doi.org/10.1016/j.jprocont.2016.02.005.

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40

Hadjiski, Mincho, and Ekaterina Ivanova. "Rules Based Autotuning Approach of Conventional Smith Predictor." IFAC Proceedings Volumes 37, no. 19 (October 2004): 217–22. http://dx.doi.org/10.1016/s1474-6670(17)30686-9.

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41

Zhang, Weidong, and Xiaoming Xu. "Analytical design and analysis of mismatched Smith predictor." ISA Transactions 40, no. 2 (April 2001): 133–38. http://dx.doi.org/10.1016/s0019-0578(00)00045-8.

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42

Zhong, Qing-Chang. "Unified Smith predictor for dead-time systems 1." IFAC Proceedings Volumes 36, no. 19 (September 2003): 83–86. http://dx.doi.org/10.1016/s1474-6670(17)33306-2.

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43

Mendes, P. R. C., J. E. Normey-Rico, V. João, and D. M. Cruz. "A filtered Smith predictor based subspace predictive controller." IFAC Proceedings Volumes 47, no. 3 (2014): 1011–16. http://dx.doi.org/10.3182/20140824-6-za-1003.01339.

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44

Mirkin, Leonid. "The Modified Smith Predictor is L1 -Optimal Too*." IFAC Proceedings Volumes 39, no. 9 (2006): 650–54. http://dx.doi.org/10.3182/20060705-3-fr-2907.00111.

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45

Jih-Jenn Huang and D. B. DeBra. "Automatic Smith-predictor tuning using optimal parameter mismatch." IEEE Transactions on Control Systems Technology 10, no. 3 (May 2002): 447–59. http://dx.doi.org/10.1109/87.998035.

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46

Lee, T. H., Q. G. Wang, and K. K. Tan. "Robust Smith-predictor controller for uncertain delay systems." AIChE Journal 42, no. 4 (April 1996): 1033–40. http://dx.doi.org/10.1002/aic.690420415.

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47

Karthikeyan, R., C. Bhargav, Karthik Koneru, G. Syam, and Shikha Tripathi. "Enhanced Model Reference Adaptive Control Using Smith Predictor." Applied Mechanics and Materials 367 (August 2013): 363–68. http://dx.doi.org/10.4028/www.scientific.net/amm.367.363.

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The main aim of a control system is to repress the instabilities caused by nonlinearities of the system. Dead time is considered to be one of the most significant nonlinearities of a system. Dead time compensators play a vital role in reducing the dead time effects on the processes only to a minute extent. This paper proposes a method to overcome this problem by using Enhanced Model Reference Adaptive Control (MRAC) incorporating Smith Predictor. MRAC belongs to class of adaptive servo system in which desired performance is expressed with the help of a reference model. Enhanced MRAC consists of a fuzzy logic controller which provides adaptation gain to MRAC without human interference. A dead time compensator incorporated in the enhanced MRAC solves the problem of instabilities caused by dead time to a greater extent.

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48

Giraldo, Sergio A. Castaño, Rodolfo C. C. Flesch, and Julio E. Normey-Rico. "Multivariable Greenhouse Control Using the Filtered Smith Predictor." Journal of Control, Automation and Electrical Systems 27, no. 4 (May 11, 2016): 349–58. http://dx.doi.org/10.1007/s40313-016-0250-6.

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49

Zhou, Han-Qin, Qing-Guo Wang, and Liu Min. "Modified Smith predictor design for periodic disturbance rejection." ISA Transactions 46, no. 4 (October 2007): 493–503. http://dx.doi.org/10.1016/j.isatra.2007.03.007.

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50

Rong, Hui-gui, Hui Zheng, Zheng-qiang Li, and Yu-xiang Xia. "Tuning of fuzzy PID controller for Smith predictor." Journal of Central South University of Technology 17, no. 3 (June 2010): 566–71. http://dx.doi.org/10.1007/s11771-010-0524-2.

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