Introduction

This introduction presents an overview of the key concepts discussed in the subsequent chapters of this book. The book introduces the performance index/optimisation which is the third main component of model-based predictive control (MPC) and also explores how these are combined with a prediction model to form a control law. It shows a number of simple MPC designs and these are used to gain insight into systematic tuning rules and also scenarios to avoid. The book shows how to set up the MPC algorithm to be well conditioned. It examines the relationship between model structure and prediction errors and hence on loop sensitivity. The book also shows how the identification can be configured to support the MPC design. It looks at constraint handling in the uncertain case and introduces the tool of invariant sets.