Abstract
In robotics, despite considerable effort to minimise system modelling errors, uncertainties are always present and sometimes significant. In this paper, modelling errors are first represented by a class of bounded disturbances in the input control channels (torques) of the robot. A measure of the robot system's abil3ity to reject these disturbances is. formulated in a nonlinear H∞ norm sense and a control design is subsequently proposed to achieve optimal disturbance rejection. If more detailed information is available on the plant/model mismatch, then the control design can be modified to incorporate an adaptive scheme (with explicit parameter updating laws) in order to reduce the conservativeness of the original design and to improve robust performance of the overall system. In passing it is shown how the nonlinear quadratic optimization problem is a special case of nonlinear H∞ optimization.
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