Abstract
A controller is an essential part of a robotic system in achieving desired motion. A Proportional Integral Derivative (PID) controller is the simplest form of controller used for this purpose. A PID controller is widely used in industries for the control of processes or machines. In a robotic system, e.g., an industrial robot, a PID controller independently controls motion of each joint ignoring the effects of the system’s dynamics. However, for accomplishing complex motion or task, a PID controller does not always result into best performance, as shown by Lewis et al. (2004), Kelly et al. (2005), and Craig (2006). The legged robots discussed in Chaps. 6 and 7 are meant to perform a variety of complex tasks. As a result, the use of a PID controller without taking into account dynamics of the legged robots would result into poor control performance. On the other hand, the use of model-based controllers (Lewis et al. 2004; Kelly et al. 2005) has become popular in order to improve the performance of the conventional PID controllers. The model-based controllers work based on the information of the dynamic model of a system. If the dynamic model of a robot is not very accurate, the model-based control approach will still be able to eliminate major nonlinearities due to the robot’s inertia. In this chapter, simulation of model-based control of several robotic systems will be carried out.
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