True Digital Control

True Digital Control: Statistical Modelling andNon–Minimal State Space Designdevelops a true digitalcontrol design philosophy that encompasses data–basedmodel identification, through to control algorithm design,robustness evaluation and implementation. With a heritage from bothclassical and modern control system synthesis, this book issupported by detailed practical examples based on theauthors’ research into environmental, mechatronic and roboticsystems. Treatment of both statistical modelling and control designunder one cover is unusual and highlights the important connectionsbetween these disciplines. Starting from the ubiquitous proportional–integralcontroller, and with essential concepts such as pole assignmentintroduced using straightforward algebra and block diagrams, thisbook addresses the needs of those students, researchers andengineers, who would like to advance their knowledge of controltheory and practice into the state space domain; and academics whoare interested to learn more about non–minimal state variablefeedback control systems. Such non–minimal state feedback isutilised as a unifying framework for generalised digital controlsystem design. This approach provides a gentle learning curve, fromwhich potentially difficult topics, such as optimal, stochastic andmultivariable control, can be introduced and assimilated in aninteresting and straightforward manner. Key features: Covers both system identification and control systemdesign in a unified manner Includes practical design case studies and simulationexamples Considers recent research into time–variable andstate–dependent parameter modelling and control, essentialelements of adaptive and nonlinear control system design, and thedelta–operator (the discrete–time equivalent of thedifferential operator) systems Accompanied by a website hosting MATLAB examples True Digital Control: Statistical Modelling andNon–Minimal State Space Design is a comprehensive andpractical guide for students and professionals who wish to furthertheir knowledge in the areas of modern control and systemidentification.