Data-based design of high-performance motion controllers

This paper presents a data-based design of a linear feedback controller, which realizes desired closed-loop sensitivity and complementary sensitivity transfer functions. These transfer functions are specified via a single model-based performance cost. The data-based equivalent of this cost is derived, and its utility for the feedback design is demonstrated. A designer can prescribe the controller structure and complexity. Experimental results obtained in a direct-drive robot motion control problem show the quality of the design.