ABSTRACT
This chapter aims to the integration of crisp algorithmic control and soft knowledge-based control in the context of robotic manipulator control. In particular, crisp algorithms are restricted to high-bandwidth control loops at the servo level, and knowledge-based control is introduced at higher levels in a control hierarchy in order to effectively monitor the robot performance and to tune the conventional crisp controllers at the servo level. Higher level activities such as task description, procedural decomposition, sub-task allocation, path planning, activity coordination, and supervisory control are also integral within the control system. Kinematic and kinetic formulations are useful in modeling and control of robots. A common application of fuzzy logic control in robots is within the joint-servo loops as an integral part of the direct-digital controller. The servo expert monitors the error response of the particular degree of freedom of the robot. These monitored data form the context for the servo expert.
