Microprocessor-Based Controllers for Robotic Manipulators

Robotic manipulators pose a challenging problem to control system theory. Classical controllers, such as the well know PID controller still used in present day industrial robots, are inadequate for high performance manipulators. This problem motivated the emergence of a new class of controllers based on different concepts, namely non-linear and adaptative controllers. Unfortunately, these complex algorithms require powerful computer structures. While monoprocessor systems may be non-economical, multi-microprocessor architectures are still in a research stage and the total computional efficiency is far from desirable. To surpass these limitations new controller structures were devised. Some are based on the reformulation of the overall control concepts. In this line of thought methods like sliding controllers and learning controllers are being actively investigated. In the former the algorithms are easy to implement using standard hardware and applications have already been reported. With respect to learning controllers, they are still in a research stage; nevertheless, preliminary results indicate that a considerable computational reduction can be achieved by a more intelligent use of the microprocessor memory. Alternative strategies based on a more sound allocation of the computing tasks were also suggested~: Techniques such as multirate sampling, preview schemes and dedicated compilers have achieved promising results. This chapter focuses on the aforementioned control methods having in mind its real-time implementation on microprocessor-based structures.