Nonlinear predictive control : theory and practice The book is divided into 4 parts and comprises 12 chapters dealing with the following subjects: nonlinear model predictive control applications; output feedback and tracking of nonlinear systems; model predictive control of nonlinear parameter varying systems via receding horizon control Lyapunov functions; nonlinear model algorithmic control for multivariable nonminimum phase processes; open loop and closed loop optimality in interpolation MPC; closed loop predictions in model based predictive control of linear and nonlinear systems; computationally efficient nonlinear predictive control algorithm for control of constrained nonlinear systems; long prediction horizon nonlinear model predictive control; nonlinear control of industrial processes; nonlinear model based predictive control using multiple local models; and neural network control of a gasoline engine with rapid sampling