While conceptually elegant, the generic formulations of nonlinear model predictive control are not ready to use for the stabilization of relatively fast systems. Doctor Alamir presents a successful approach to this problem based on a co-operation between structural considerations and on-line optimization. The balance between structural and optimization aspects of the method is dependent on the system being considered so the many examples developed here aim to transmit a mode of thought rather than a ready-to-use recipe. Among the systems given detailed treatment are:double inverted pendulum; non-holonomic systems in chained form; snake board; missile in intercept mission; polymerization reactor; walking robot; under-actuated satellite in failure mode. In addition, the basic stability results under receding horizon control schemes are revisited using a sampled-time, low-dimensional control parameterization that is mandatory for fast computation and some novel formulations are proposed which offer promising directions for future research.
While conceptually elegant, the generic formulations of nonlinear model predictive control are not ready to use for the stabilization of relatively fast systems. This book presents a successful approach to this problem based on a co-operation between structural considerations and on-line optimization. It also provides research showing how generic predictive control schemes can be extended from slow process-based systems to a variety of fast systems.
