Book Description

This book introduces multi-objective design methods to solve multi-objective optimization problems (MOPs) of linear/nonlinear dynamic systems under intrinsic random fluctuation and external disturbance. The MOPs of multiple targets for systems are all transformed into equivalent linear matrix inequality (LMI)-constrained MOPs. Corresponding reverse-order LMI-constrained multi-objective evolution algorithms are introduced to solve LMI-constrained MOPs using MATLAB®. All proposed design methods are based on rigorous theoretical results, and their applications are focused on more practical engineering design examples. Features: Discusses multi-objective optimization from an engineer’s perspective Contains the theoretical design methods of multi-objective optimization schemes Includes a wide spectrum of recent research topics in control design, especially for stochastic mean field diffusion problems Covers practical applications in each chapter, like missile guidance design, economic and financial systems, power control tracking, minimization design in communication, and so forth Explores practical multi-objective optimization design examples in control, signal processing, communication, and cyber-financial systems This book is aimed at researchers and graduate students in electrical engineering, control design, and optimization.