Model Predictive Control System Design and Implementation Using MATLABproposes methods for design and implementation of MPC systems using basisfunctions that co... » 

Model Predictive Control System Design and Implementation Using MATLABproposes methods for design and implementation of MPC systems using basisfunctions that confer the following advantages continuous and discretetimeMPC problems solved in similar design frameworks a parsimonious parametricrepresentation of the control trajectory gives rise to computationallyefficient algorithms and better online performance and a more generaldiscretetime representation of MPC design that becomes identical to thetraditional approach for an appropriate choice of parameters. After thetheoretical presentation coverage is given to three industrial applications.The subject of quadratic programming often associated with the coreoptimization algorithms of MPC is also introduced and explained. The technicalcontents of this book is mainly based on advances in MPC using statespacemodels and basis functions. This volume includes numerous analytical examplesand problems and MATLAB programs and exercises. TOCDiscretetime MPC forBeginners. Discretetime MPC with Constraints. Discretetime MPC UsingLaguerre Functions. Discretetime MPC with Prescribed Degree of Stability.Continuoustime Orthonormal Basis Functions. Continuoustime MPC. Continuoustime MPC with Constraints. Continuoustime MPC with Prescribed Degree ofStability. Classical MPC Systems in Statespace Formulation. Implementationof Predictive Control Systems. «