An Overview of Control Theory Applicable to Process Industries

Abstract In this paper we present an overview of some recent trends and results in selected topics in control theory which are deemed to have most relevance to the control of processes which are commonly used in the petroleum, petrochemical, and desalination industries. Judicious approximations and simplifications are commonplace, so that the resulting mathematical models for the processes necessarily involve idealizations leading to discrepancies between the real systems and the models. These processes are usually distributed in nature so that partial differential equations are more appropriate than ordinary differential equations to describe them. Finally, the computation of controls are usually computer-aided by necessity. We give an overview of recent results on the synthesis of robust controllers for linear time-invariant plants.Next we given an overview of several methods for the control of distributed parameter systems. Finally we briefly describe some trends in computer-aided design and engineering relevant to process control.

[1]  G. Zames,et al.  On H ∞ -optimal sensitivity theory for SISO feedback systems , 1984 .

[2]  Charles A. Desoer,et al.  Design of multivariable feedback systems with simple unstable plant , 1984 .

[3]  Mark J. Balas,et al.  Linear distributed parameter systems: Closed-loop exponential stability with a finite-dimensional controller , 1984, Autom..

[4]  Karl Johan Åström,et al.  Computer aided modeling, analysis and design of control systems - A perspective , 1983 .

[5]  Yoshikazu Nishikawa,et al.  A method for auto-tuning of PID control parameters , 1981, Autom..

[6]  Spyros G. Tzafestas,et al.  Recent advances in the study of distributed parameter systems , 1983 .

[7]  Y. Hung,et al.  Robust stability of additively perturbed interconnected systems , 1984 .

[8]  John C. Doyle Analysis of Feedback Systems with Structured Uncertainty , 1982 .

[9]  A. Laub,et al.  Numerical linear algebra aspects of control design computations , 1985, IEEE Transactions on Automatic Control.

[10]  George Zames,et al.  A new approach to classical frequency methods: Feedback and minimax sensitivity , 1981, 1981 20th IEEE Conference on Decision and Control including the Symposium on Adaptive Processes.

[11]  C. Desoer,et al.  Algebraic theory of linear multivariable feedback systems , 1984 .

[12]  Mathukumalli Vidyasagar,et al.  Robust controllers for uncertain linear multivariable systems , 1984, Autom..

[13]  P. Khargonekar,et al.  Non-Euclidian metrics and the robust stabilization of systems with parameter uncertainty , 1985 .

[14]  A. G. Butkovskiy,et al.  Some New Results in Distributed Parameter System Control (A Review) , 1983 .

[15]  George Stephanopoulos,et al.  Multiobjective analysis in modeling the petrochemical industry , 1980 .

[16]  E. Polak,et al.  Delight. MIMO: An interactive, optimization-based multivariable control system design package , 1982, IEEE Control Systems Magazine.

[17]  Carlos S. Kubrusly,et al.  Sensors and controllers location in distributed systems - A survey , 1985, Autom..

[18]  Dante C. Youla,et al.  Modern Wiener--Hopf design of optimal controllers Part I: The single-input-output case , 1976 .

[19]  S. G. Tzafestas Adaptive control of stochastic distributed parameter systems: a survey , 1984 .

[20]  G. Stein,et al.  Multivariable feedback design: Concepts for a classical/modern synthesis , 1981 .

[21]  Hartwig U. Steusloff Advanced Real-Time Languages for Distributed Industrial Process Control , 1984, Computer.

[22]  T. Sadeghi,et al.  Computer-aided control system analysis and design using interactive computer graphics , 1982, IEEE Control Systems Magazine.

[23]  J. Freudenberg,et al.  Right half plane poles and zeros and design tradeoffs in feedback systems , 1985 .

[24]  M. A. Sheirah,et al.  A self-tuning regulator for distributed parameter systems , 1978, Autom..

[25]  G. Zames,et al.  Feedback, minimax sensitivity, and optimal robustness , 1983 .

[26]  M. Morari Robust stability of systems with integral control , 1983, The 22nd IEEE Conference on Decision and Control.

[27]  M. Vajta Self-Tuning Control of a Heat Conduction Process 1 , 1983 .

[28]  A. El-Sakkary,et al.  The gap metric: Robustness of stabilization of feedback systems , 1985 .

[29]  R. Kosut,et al.  Robust adaptive control: Conditions for global stability , 1985 .

[30]  J. H. Seinfeld,et al.  Brief survey of approaches to deriving the optimal linear distributed parameter filter , 1984 .

[31]  Juha T. Tanttu,et al.  TDP - A Distributed Parameter Systems Simulator , 1985 .

[32]  J. Cruz,et al.  RELATIONSHIP BETWEEN SENSITIVITY AND STABILITY OF MULTIVARIABLE FEEDBACK SYSTEMS. , 1981 .

[33]  Kameshwar Poolla,et al.  Robust stabilization of distributed systems , 1986, Autom..

[34]  P. Kokotovic,et al.  Stability analysis of an adaptive system with unmodelled dynamics , 1985 .

[35]  Sten Bay Jørgensen,et al.  Multivariable adaptive identification and control of a distributed chemical reactor , 1984 .

[36]  G. Zames,et al.  H ∞ -optimal feedback controllers for linear multivariable systems , 1984 .

[37]  K. Glover All optimal Hankel-norm approximations of linear multivariable systems and their L, ∞ -error bounds† , 1984 .

[38]  R. Schumann Computer-Aided Configuration and Start-Up of Process Control Systems , 1985 .

[39]  Ignacio E. Grossmann,et al.  Optimization strategies for flexible chemical processes , 1983 .

[40]  Petros A. Ioannou,et al.  Robust redesign of adaptive control , 1984 .

[41]  Michael J. Grimble Robustness of combined state and state-estimate feedback control schemes , 1984 .

[42]  Stephen P. Boyd,et al.  Necessary and sufficient conditions for parameter convergence in adaptive control , 1986, Autom..