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[ subject:"Predictive control." ]
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MPC-based reference governors = theo...
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Klauco, Martin.
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MPC-based reference governors = theory and case studies /
紀錄類型:
書目-電子資源 : Monograph/item
正題名/作者:
MPC-based reference governors/ by Martin Klauco, Michal Kvasnica.
其他題名:
theory and case studies /
其他題名:
Model prredictive control based reference governors
作者:
Klauco, Martin.
其他作者:
Kvasnica, Michal.
出版者:
Cham :Springer International Publishing : : 2019.,
面頁冊數:
xxiii, 137 p. :ill., digital ;24 cm.
內容註:
Reference Governors -- Part I: Theory -- Mathematical Preliminaries and General Optimization -- Model Predictive Control -- Inner Loops with PID Controllers -- Inner Loops with Relay-Based Controllers -- Inner Loops with LQ Controllers -- Inner Loops with Model Predictive Controllers -- Part II: Case Studies -- Boiler-Turbine System -- Magnetic-Levitation Process -- Thermostatically Controlled Indoor Temperature -- Cascade Model Predictive Control of Chemical Reactors -- Conclusions and Future Work.
Contained By:
Springer eBooks
標題:
Predictive control. -
電子資源:
https://doi.org/10.1007/978-3-030-17405-7
ISBN:
9783030174057
MPC-based reference governors = theory and case studies /
Klauco, Martin.
MPC-based reference governors
theory and case studies /[electronic resource] :Model prredictive control based reference governorsby Martin Klauco, Michal Kvasnica. - Cham :Springer International Publishing :2019. - xxiii, 137 p. :ill., digital ;24 cm. - Advances in industrial control,1430-9491. - Advances in industrial control..
Reference Governors -- Part I: Theory -- Mathematical Preliminaries and General Optimization -- Model Predictive Control -- Inner Loops with PID Controllers -- Inner Loops with Relay-Based Controllers -- Inner Loops with LQ Controllers -- Inner Loops with Model Predictive Controllers -- Part II: Case Studies -- Boiler-Turbine System -- Magnetic-Levitation Process -- Thermostatically Controlled Indoor Temperature -- Cascade Model Predictive Control of Chemical Reactors -- Conclusions and Future Work.
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.
ISBN: 9783030174057
Standard No.: 10.1007/978-3-030-17405-7doiSubjects--Topical Terms:
667592
Predictive control.
LC Class. No.: TJ217.6 / .K538 2019
Dewey Class. No.: 629.8
MPC-based reference governors = theory and case studies /
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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.
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