Structured Controllers for Uncertain Systems : A Stochastic Optimization Approach

Structured Controllers for Uncertain Systems focuses on the development of easy-to-use design strategies for robust low-order or fixed-structure controllers (particularly the industrially ubiquitous PID controller). These strategies are based on a recently-developed stochastic optimization method termed the "Heuristic Kalman Algorithm" (HKA) the use of which results in a simplified methodology that enables the solution of the structured control problem without a profusion of user-defined parameters. An overview of the main stochastic methods employable in the context of continuous non-convex optimization problems is also provided and various optimization criteria for the design of a structured controller are considered; H

Rosario Toscano was born in Catania, Italy. He received his masters degree with specialization in control from the Institut National des Sciences Appliquées de Lyon in 1996. He received the Ph.D. degree from the Ecole Centrale de Lyon in 2000. He received the HDR degree (Habilitation to Direct Research) from the University Jean Monnet of Saint-Etienne in 2007. He is currently an associate professor at the Ecole Nationale d'Ingénieurs de Saint-Etienne (ENISE). His research interests include dynamic reliability, fault detection, robust control, and multimodel approach applied to diagnosis and control.