Lecture Notes in Control and Information Sciences: Developments in Model-Based Optimization and Control : Distributed Control and Industrial Applications 464 (2015, Paperback) read online TXT, DJV, MOBI
9783319266855 3319266853 This book deals with optimizationmethods as tools for decision making and control in the presence ofuncertainty. It is oriented to the use of these tools in engineering and,specifically, in automatic control design with all its components: analysis of dynamicalsystems, estimation problems, and feedback control design. Developments in Model-Based Optimization and Control takes advantage of optimization-based formulations for such classicalfeedback design objectives as stability, performance and feasibility affordedby the established body of results and methodologies constituting optimalcontrol theory. It makes particular use of the popular formulation known aspredictive control or receding-horizon optimization. The individual contributions in thisvolume are wide-ranging in subject matter but coordinated within a five-partstructure covering material on: complexity and structure in model predictive control (MPC); collaborative MPC; distributed MPC; optimization-based analysis and design; and applications. The various contributions cover asubject spectrum including explicit and more modern decentralized andcooperative formulations of receding-horizon optimal control. Readers will findthirteen chapters dedicated to optimization-based tools for robustnessanalysis, and decision-making in relation to feedback mechanisms--faultdetection, for example--and three to applications.< Developments in Model-Based Optimization and Control is a selection of contributions expanded and updated from the Optimisation-basedControl and Estimation workshops held in November 2012 and November 2013.It forms a useful resource for academic researchers and graduate students interestedin the state of the art in predictive control. Control engineers working inpredictive control, particularly in its bioprocess applications will also findthis collection instructive.
9783319266855 3319266853 This book deals with optimizationmethods as tools for decision making and control in the presence ofuncertainty. It is oriented to the use of these tools in engineering and,specifically, in automatic control design with all its components: analysis of dynamicalsystems, estimation problems, and feedback control design. Developments in Model-Based Optimization and Control takes advantage of optimization-based formulations for such classicalfeedback design objectives as stability, performance and feasibility affordedby the established body of results and methodologies constituting optimalcontrol theory. It makes particular use of the popular formulation known aspredictive control or receding-horizon optimization. The individual contributions in thisvolume are wide-ranging in subject matter but coordinated within a five-partstructure covering material on: complexity and structure in model predictive control (MPC); collaborative MPC; distributed MPC; optimization-based analysis and design; and applications. The various contributions cover asubject spectrum including explicit and more modern decentralized andcooperative formulations of receding-horizon optimal control. Readers will findthirteen chapters dedicated to optimization-based tools for robustnessanalysis, and decision-making in relation to feedback mechanisms--faultdetection, for example--and three to applications.< Developments in Model-Based Optimization and Control is a selection of contributions expanded and updated from the Optimisation-basedControl and Estimation workshops held in November 2012 and November 2013.It forms a useful resource for academic researchers and graduate students interestedin the state of the art in predictive control. Control engineers working inpredictive control, particularly in its bioprocess applications will also findthis collection instructive.