Description
This monograph provides a rigorous mathematical treatment of discrete-time Markov jump linear systems, a fundamental framework for modeling systems with random parameter jumps. The book addresses key theoretical developments and practical applications in control theory and signal processing.
The text covers essential topics including stochastic stability analysis, optimal control design, robust control strategies, and filtering techniques. It explores the theoretical foundations necessary for understanding systems subject to random mode switches, with applications ranging from manufacturing systems to aerospace engineering.
Written for researchers and graduate students, the work integrates probability theory with systems and control theory, providing both theoretical insights and computational methods. The book emphasizes practical problem-solving while maintaining mathematical rigor, making it an invaluable resource for advanced studies in stochastic control systems.
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