Robot and Uav Control: An Overview
Nonlinear control is an important area whereby the application of mathematical principles and the basic methods underpinning the analysis, synthesis and design of the controllers are studied, without making a conscious or deliberate attempt to mask the nonlinearities that arise naturally in the mathematical modeling of the process plant or other components associated with a controlled system. Normally, in linear control theory, it is customary to linearize the plant by assuming operation close to an equilibrium point or quiescent condition characterized by a minimal number of steady variables. In nonlinear control, while we continue to operate around an equilibrium point or quiescent condition, no attempts are made to approximate the local dynamics by assuming the excursions from the equilibrium point or quiescent condition are small. In nonlinear control theory, a large variety of approaches and mathematical tools for analysis are employed. The main reason for this is that no tool or methodology is universally applicable to a nonlinear system. Consequently, system approaches for the analysis and design of nonlinear control systems are only available for certain classes of nonlinear systems. Moreover, robotic systems represent a special class of dynamic systems that are
characterized by number features which are distinct. This chapter is concerned only with the methods of implementing feedback control systems for the special class of nonlinear process plants that are associated with robotic systems and autonomous mobile vehicles.