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Predictive control. --- Model based predictive control --- Model predictive control --- Automatic control
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This monograph focuses on the design of optimal reference governors using model predictive control (MPC) strategies. These MPC-based governors serve as a supervisory control layer that generates optimal trajectories for lower-level controllers such that the safety of the system is enforced while optimizing the overall performance of the closed-loop system. The first part of the monograph introduces the concept of optimization-based reference governors, provides an overview of the fundamentals of convex optimization and MPC, and discusses a rigorous design procedure for MPC-based reference governors. The design procedure depends on the type of lower-level controller involved and four practical cases are covered: PID lower-level controllers; linear quadratic regulators; relay-based controllers; and cases where the lower-level controllers are themselves model predictive controllers. For each case the authors provide a thorough theoretical derivation of the corresponding reference governor, followed by illustrative examples. The second part of the book is devoted to practical aspects of MPC-based reference governor schemes. Experimental and simulation case studies from four applications are discussed in depth: control of a power generation unit; temperature control in buildings; stabilization of objects in a magnetic field; and vehicle convoy control. Each chapter includes precise mathematical formulations of the corresponding MPC-based governor, reformulation of the control problem into an optimization problem, and a detailed presentation and comparison of results. The case studies and practical considerations of constraints will help control engineers working in various industries in the use of MPC at the supervisory level. The detailed mathematical treatments will attract the attention of academic researchers interested in the applications of MPC.
Predictive control. --- Model based predictive control --- Model predictive control --- Automatic control --- Chemical engineering. --- Manufactures. --- Engineering. --- Control and Systems Theory. --- Industrial Chemistry/Chemical Engineering. --- Manufacturing, Machines, Tools, Processes. --- Automotive Engineering. --- Construction --- Industrial arts --- Technology --- Manufactured goods --- Manufactured products --- Products --- Products, Manufactured --- Commercial products --- Manufacturing industries --- Chemistry, Industrial --- Engineering, Chemical --- Industrial chemistry --- Engineering --- Chemistry, Technical --- Metallurgy --- Control engineering. --- Automotive engineering. --- Control engineering --- Control equipment --- Control theory --- Engineering instruments --- Automation --- Programmable controllers
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Stabilizing and Optimizing Control for Time-Delay Systems introduces three important classes of stabilizing controls for time-delay systems: non-optimal (without performance criteria); suboptimal (including guaranteed costs); and optimal controls. Each class is treated in detail and compared in terms of prior control structures. State- and input-delayed systems are considered. The book provides a unified mathematical framework with common notation being used throughout. Receding-horizon, or model predictive, linear quadratic (LQ), linear-quadratic-Gaussian and H∞ controls for time-delay systems are chosen as optimal stabilizing controls. Cost monotonicity is investigated in order to guarantee the asymptotic stability of closed-loop systems operating with such controls. The authors use guaranteed LQ and H∞ controls as representative sub-optimal methods; these are obtained with pre-determined control structures and certain upper bounds of performance criteria. Non-optimal stabilizing controls are obtained with predetermined control structures but with no performance criteria. Recently developed inequalities are exploited to obtain less conservative results. To facilitate computation, the authors use linear matrix inequalities to represent gain matrices for non-optimal and sub-optimal stabilizing controls, and all the initial conditions of coupled differential Riccati equations of optimal stabilizing controls. Numerical examples are provided with MATLAB® codes (downloadable from http://extras.springer.com/) to give readers guidance in working with more difficult optimal and suboptimal controls. Academic researchers studying control of a variety of real processes in chemistry, biology, transportation, digital communication networks and mechanical systems that are subject to time delays will find the results presented in Stabilizing and Optimizing Control for Time-Delay Systems to be helpful in their work. Practitioners working in related sectors of industry will also find this book to be of use in developing real-world control systems for the many time-delayed processes they encounter.
Predictive control. --- Time delay systems. --- Systems theory. --- Mathematical optimization. --- Chemical engineering. --- Control and Systems Theory. --- Systems Theory, Control. --- Optimization. --- Industrial Chemistry/Chemical Engineering. --- Time delay control --- Time delay control systems --- Time delay controllers --- Time-delayed systems --- Feedback control systems --- Process control --- Model based predictive control --- Model predictive control --- Automatic control --- Chemistry, Industrial --- Engineering, Chemical --- Industrial chemistry --- Engineering --- Chemistry, Technical --- Metallurgy --- Optimization (Mathematics) --- Optimization techniques --- Optimization theory --- Systems optimization --- Mathematical analysis --- Maxima and minima --- Operations research --- Simulation methods --- System analysis --- Control engineering. --- System theory. --- Control engineering --- Control equipment --- Control theory --- Engineering instruments --- Automation --- Programmable controllers --- Systems, Theory of --- Systems science --- Science --- Philosophy
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