Manfred Morari – författare

Model Predictive Control (MPC), the dominant advanced control approach in industry over the past twenty-five years, is presented comprehensively in this unique book. With a simple, unified approach, and with attention to real-time implementation, it covers predictive control theory including the stability, feasibility, and robustness of MPC controllers. The theory of explicit MPC, where the nonlinear optimal feedback controller can be calculated efficiently, is presented in the context of linear systems with linear constraints, switched linear systems, and, more generally, linear hybrid systems. Drawing upon years of practical experience and using numerous examples and illustrative applications, the authors discuss the techniques required to design predictive control laws, including algorithms for polyhedral manipulations, mathematical and multiparametric programming and how to validate the theoretical properties and to implement predictive control policies. The most important algorithms feature in an accompanying free online MATLAB toolbox, which allows easy access to sample solutions. Predictive Control for Linear and Hybrid Systems is an ideal reference for graduate, postgraduate and advanced control practitioners interested in theory and/or implementation aspects of predictive control.

Model Predictive Control (MPC), the dominant advanced control approach in industry over the past twenty-five years, is presented comprehensively in this unique book. With a simple, unified approach, and with attention to real-time implementation, it covers predictive control theory including the stability, feasibility, and robustness of MPC controllers. The theory of explicit MPC, where the nonlinear optimal feedback controller can be calculated efficiently, is presented in the context of linear systems with linear constraints, switched linear systems, and, more generally, linear hybrid systems. Drawing upon years of practical experience and using numerous examples and illustrative applications, the authors discuss the techniques required to design predictive control laws, including algorithms for polyhedral manipulations, mathematical and multiparametric programming and how to validate the theoretical properties and to implement predictive control policies. The most important algorithms feature in an accompanying free online MATLAB toolbox, which allows easy access to sample solutions. Predictive Control for Linear and Hybrid Systems is an ideal reference for graduate, postgraduate and advanced control practitioners interested in theory and/or implementation aspects of predictive control.

Model Predictive Control (MPC), the dominant advanced control approach in industry over the past twenty-five years, is presented comprehensively in this unique book. With a simple, unified approach, and with attention to real-time implementation, it covers predictive control theory including the stability, feasibility, and robustness of MPC controllers. The theory of explicit MPC, where the nonlinear optimal feedback controller can be calculated efficiently, is presented in the context of linear systems with linear constraints, switched linear systems, and, more generally, linear hybrid systems. Drawing upon years of practical experience and using numerous examples and illustrative applications, the authors discuss the techniques required to design predictive control laws, including algorithms for polyhedral manipulations, mathematical and multiparametric programming and how to validate the theoretical properties and to implement predictive control policies. The most important algorithms feature in an accompanying free online MATLAB toolbox, which allows easy access to sample solutions. Predictive Control for Linear and Hybrid Systems is an ideal reference for graduate, postgraduate and advanced control practitioners interested in theory and/or implementation aspects of predictive control.

Model Predictive Control (MPC), the dominant advanced control approach in industry over the past twenty-five years, is presented comprehensively in this unique book. With a simple, unified approach, and with attention to real-time implementation, it covers predictive control theory including the stability, feasibility, and robustness of MPC controllers. The theory of explicit MPC, where the nonlinear optimal feedback controller can be calculated efficiently, is presented in the context of linear systems with linear constraints, switched linear systems, and, more generally, linear hybrid systems. Drawing upon years of practical experience and using numerous examples and illustrative applications, the authors discuss the techniques required to design predictive control laws, including algorithms for polyhedral manipulations, mathematical and multiparametric programming and how to validate the theoretical properties and to implement predictive control policies. The most important algorithms feature in an accompanying free online MATLAB toolbox, which allows easy access to sample solutions. Predictive Control for Linear and Hybrid Systems is an ideal reference for graduate, postgraduate and advanced control practitioners interested in theory and/or implementation aspects of predictive control.

Shell Process Control Workshop covers the proceedings of a workshop of the same name, held in Houston, Texas on December 15, 1986. The said workshop seeks to improve the communication process between academic researchers, industrial researchers, and the engineering community in the field of process control, and in turn improve understanding of the nature of the control problems. The book covers topics such as design methodology based on the fundamental control; expert systems in process control and optimization; artificial intelligence; and adaptive control for processes. Also covered are topics such the approach of systems engineering to process modeling; modeling and control of dispersed phase systems; and advances in the use of the internal model control. The text is recommended for researchers and practitioners in the field of engineers who would like to know more about process control and modeling.

This volume contains the proceedings of the 8th Workshop on Hybrid S- tems: Computation and Control(HSCC2005)heldinZurich,Switzerlandduring March 9-11, 2005. The annual workshop on hybrid systems attracts researchers from academia and industry interested in modeling, analysis, and implemen- tion of dynamic and reactive systems involving both discrete and continuous - haviors. The previous workshops in the HSCC series were held in Berkeley, USA (1998),Nijmegen,TheNetherlands(1999),Pittsburgh,USA(2000),Rome,Italy (2001), Palo Alto, USA (2002), Prague, Czech Republic (2003), and Philad- phia, USA (2004). This year's HSCC was technically co-sponsored by the IEEE Control Systems Society. The program consisted of 3 invited talks and 40 regular papers selected from 91 regular submissions. The program covered topics such as tools for analysis and veri?cation, control and optimization, modeling, engineering applications, and emerging directions in programming language support and implementation. We would like to thank the Program Committee members and reviewers for anexcellentjobofevaluatingthesubmissionsandparticipatingintheonlineP- gram Committee discussions.Special thanks go to Markus P. J. Fromherz (Palo Alto Research Center, USA), Edward A. Lee (University of California, Berkeley, USA), and Pablo A. Parrilo (Massachusetts Institute of Technology, USA) for their participation as invited speakers. We are also grateful to the Steering C- mitteeforhelpfulguidanceandsupport. Manyotherpeopleworkedhardtomake the HSCC 2005 a success. We would like to thank Frank J. Christophersen and Ernesto Wandeler, the Publicity Chairs (with the help of Urban M.. ader); M- tine D'Emma and Monica Fricker for local arrangements; and Frank J. Chris- phersen for putting together the proceedings.