Recent developments in model-predictive control promise remarkable opportunities for designing multi-input, multi-output control systems and improving the control of single-input, single-output systems. This volume provides a definitive survey of the latest model-predictive control methods available to engineers and scientists today. The initial set of chapters present various methods for managing uncertainty in systems, including stochastic model-predictive control. With the advent of affordable and fast computation, control engineers now need to think about using ¿computationally intensive controls,¿ so the second part of this book addresses the solution of optimization problems in ¿real¿ time for model-predictive control. The theory and applications of control theory often influence each other,