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.