Multivariable self-tuning regulators

Wong, K.Y.; Bayoumi, M.M.

doi:10.1109/cdc.1981.269361

Cited by 9 publications

(4 citation statements)

References 8 publications

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“…Although early papers were based on the restrictive assumption that each input-output pair had the same time delay, more recently developed design methods can accommodate arbitrary time delays for each pair (Morris et al, 1981(Morris et al, , 1982Tanttu and Koivo, 1983;Chien et al, 1984aChien et al, , 1985aDugard et al, 1984). A few design methods permit different numbers of inputs and outputs ( Wong and Bayoumi, 1981;Favier and Hassani, 1982;Grimble et al, 1982;Toivonen, 1983b) or a different sampling rate for each output variable (Morris et al, 1981(Morris et al, , 1982Chien et al, 1983;Costin and Buchner, 1983). Some multivariable self-tuners are applicable to plants that are either open-loop and unstable or nonminimum-phase (McDermott and Mellichamp, 1983;Grimble and Moir, 1983).…”

Section: Multivariable Control Problemsmentioning

confidence: 98%

“…Multivariable extensions of the Clarke-Gawthrop self-tuning controller have been developed by several research groups (Koivo, 1980;Lu and Yuan, 1980;Keviczky and Kumar, 1981;Bayoumi et al, 1981;Wong and Bayoumi, 1981;Grimble and Moir, 1983;Chien et al, 1983Chien et al, , 1984bChien et al, , 1985a. Like the original Clarke-Gawthrop STC, these methods allow cost function penalties to be placed on the manipulated input u and are applicable to nonminimum phase systems.…”

Section: Multivariable Control Problemsmentioning

confidence: 99%

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Adaptive control strategies for process control: A survey

1986

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In recent years there has been extensive interest in feedback control systems that automatically adjust their controller settings to compensate for changes in the process or the enviornment. Such systems are referred to as adaptive controllers. This survey paper reviews the current state of the art in adaptive control from a process control perspective and describes leading design techniques. Potential operating problems associated with adaptive control schemes are considered. A survey of experimental applications of adaptive control systems to process control problems is also included. SCOPEProcess control systems inevitably include adjustable controller settings that facilitate process operation over a wide range of conditions. Typically, controller settings are tuned after the control system has been installed using time-consuming, trial-and-error procedures. If process conditions change significantly, then the controller must be retuned in order to obtain satisfactory control.In recent years, there has been extensive interest in adaptive control systems that automatically adjust the controller settings to compensate for unanticipated changes in the process or the environment. Adaptive control schemes provide systematic, flexible approaches for dealing with uncertainties, nonlinearities, and time-varying process parameters. Consequently, adaptive control systems offer significant potential benefits for difficult process control problems where the process is poorly understood andlor changes in unpredictable ways. The practical benefits of adaptive control have been documented in a wide variety of successful industrial applications.Although adaptive control has been a reputable research area for about thirty years, it is only in the last decade that it has achieved prominence as one of the

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Section: Multivariable Control Problemsmentioning

confidence: 98%

Section: Multivariable Control Problemsmentioning

confidence: 99%

Adaptive control strategies for process control: A survey

1986

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“…The above structure, from which it may be possible to obtain estimates of Hand G for a desired T polynomial (closed-loop poles) was suggested by Gong (1983). The analysis given here shows that the input-output sequences of the system under c1osed-loop control are indeed related by (28).…”

Section: Na+q-(kp-i)mb=tmentioning

confidence: 83%

Implicit pole-assignment self-tuning algorithm

Allidina¹,

Khosrowshahi

Hughes

1990

International Journal of Control

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Implicit pole-assignment self-tuning algorithms are treated where the controller parameters are directly estimated from input-output data. Most algorithms based on pole-assignment are explicit schemes involving a parameter estimation and synthesisstage to obtain controller parameters. The object of the work reported here is to have an algorithm that has the robustness of pole-assignmentand the simplicity of the implicit approach.

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“…The optimal control law which minimizes the cost function in (2) is derived in Appendix A following the method of Wong and Bayoumi( 1981). This control law can be expressed as ?…”

Section: T ~~ 'mentioning

confidence: 99%

Self-tuning controller design for systems with arbitrary time delays Part 2. Algorithms and simulation examples

Tadé¹,

Bayoumi²,

Bacon³

1988

International Journal of Systems Science

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Recent theoretical developments in the self-tuning control of multivariable systems with arbitrary time delays have been considered in Part 1 of this work (Tade et al. 1988) and a simple time delay extraction procedure has been proposed. In this paper, that procedure is used to derive an adaptive controller based on the generalized minimum variance criterion. The computation count for the proposed self-tuning control algorithm is compared with those for two other algorithms, one proposed by Prager and Wellstead (1981) and the other by Dugard et al (1984). Assuming that all computation requirements for other stages of the implementation of these algorithms are equal, the results indicate that the proposed algorithm requires less computational effort for updating the control action at each sampling interval. Simulation examples are presented to demonstrate the performance of the proposed algorithm.

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Multivariable self-tuning regulators

Cited by 9 publications

References 8 publications

Adaptive control strategies for process control: A survey

Adaptive control strategies for process control: A survey

Implicit pole-assignment self-tuning algorithm

Self-tuning controller design for systems with arbitrary time delays Part 2. Algorithms and simulation examples

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