Vassilis L. Syrmos – författare

A NEW EDITION OF THE CLASSIC TEXT ON OPTIMAL CONTROL THEORYAs a superb introductory text and an indispensable reference, this new edition of Optimal Control will serve the needs of both the professional engineer and the advanced student in mechanical, electrical, and aerospace engineering. Its coverage encompasses all the fundamental topics as well as the major changes that have occurred in recent years. An abundance of computer simulations using MATLAB and relevant Toolboxes is included to give the reader the actual experience of applying the theory to real-world situations. Major topics covered include: Static OptimizationOptimal Control of Discrete-Time SystemsOptimal Control of Continuous-Time SystemsThe Tracking Problem and Other LQR ExtensionsFinal-Time-Free and Constrained Input ControlDynamic ProgrammingOptimal Control for Polynomial SystemsOutput Feedback and Structured ControlRobustness and Multivariable Frequency-Domain TechniquesDifferential GamesReinforcement Learning and Optimal Adaptive Control

A NEW EDITION OF THE CLASSIC TEXT ON OPTIMAL CONTROL THEORY

As a superb introductory text and an indispensable reference, this new edition of Optimal Control will serve the needs of both the professional engineer and the advanced student in mechanical, electrical, and aerospace engineering. Its coverage encompasses all the fundamental topics as well as the major changes that have occurred in recent years. An abundance of computer simulations using MATLAB and relevant Toolboxes is included to give the reader the actual experience of applying the theory to real-world situations. Major topics covered include:

Static Optimization Optimal Control of Discrete-Time Systems Optimal Control of Continuous-Time Systems The Tracking Problem and Other LQR Extensions Final-Time-Free and Constrained Input Control Dynamic Programming Optimal Control for Polynomial Systems Output Feedback and Structured Control Robustness and Multivariable Frequency-Domain Techniques Differential Games Reinforcement Learning and Optimal Adaptive Control