Control and Estimation with MATLAB*, 4th Edition

This text is based on much of the author's work experience. The text is intended to outline or explain things he wishes he had known earlier in his career. There is little of theory, but much of control algorithms and how to design them. The text is composed of six chapters. The 1st chapter has to do with state estimation and data smoothing. The chapter includes Luenberger observers, alpha-beta-gamma filters, Kalman filters, extended Kalman filters, proportional-integral Kalman filters, and H Infinity filters. It is given at the beginning of the text as it is a necessary interface between control algorithms and sensors. Chapter 2 describes RLS and Kalman filter state estimation approaches to fault detection and includes an example. Chapter 3 has to do with control system design to mitigate the effects of disturbances, including disturbance accommodating control, H Infinity, and ADRC. A few adaptive control methods are described including MRAC and L1 Adaptive Control. Chapter 4 describes ways to tune proportional integral derivative (PID) control algorithms. This is the most commonly used and, therefore, most important control algorithm. Chapter 5 describes several feedforward control techniques. Chapter 6 has a few applications that may be of interest to the reader. It shows a few of the techniques explained in the text by using control system and estimation methods.