Adaptive and nonlinear fuzzy force control techniques applied to robots operating in uncertain environments

For robots to perform many complex tasks there is a need for robust and stable force control. Linear, fixed-gain controllers can only provide adequate performance when they are tuned to specific task requirements, but if the environmental stiffness at the robot/task interface is unknown and varies significantly, performance is degraded. This paper describes the design of two nonlinear, fuzzy force controllers, developed primarily using analytical methods, which overcome the problems of conventional control. Using simulation and an experimental robot, they are shown to perform well over a wide range of stiffness and both a quantitative and qualitative assessment of their performance compared with conventional force control is presented.