Complementary Stability and Loop Shaping for Improved Human–Robot Interaction

Robots intended for high-force interaction with humans face particular challenges to achieve performance and stability. They require low and tunable endpoint impedance as well as high force capacity, and demand actuators with low intrinsic impedance, the ability to exhibit high impedance (relative to the human subject), and a high ratio of force to weight. Force-feedback control can be used to improve actuator performance, but causes well-known interaction stability problems. This paper presents a novel method to design actuator controllers for physically interactive machines. A loop-shaping design method is developed from a study of fundamental differences between interaction control and the more common servo problem. This approach addresses the interaction problem by redefining stability and performance, using a computational approach to search parameter spaces and displaying variations in performance as control parameters are adjusted. A measure of complementary stability is introduced, and the coupled stability problem is transformed to a robust stability problem using limited knowledge of the environment dynamics (in this case, the human). Design examples show that this new measure improves performance beyond the current best-practice stability constraint (passivity). The controller was implemented on an interactive robot, verifying stability and performance. Testing showed that the new controller out-performed a state-of-the-art controller on the same system