Robust control of nonlinear systems using model-error control synthesis

A new approach for the robust control of nonlinear systems is presented. This approach employs an optimal real-time nonlinear estimator to determine model-error corrections to the control input using a one time-step ahead technique. Control compensation is achieved by using the estimated model error as a signal synthesis adaptive correction to the nominal control input so that maximum performance is achieved in the face of extreme model uncertainty and disturbance inputs. A significant advantage of this approach over other adaptive methods is that model parameters need not be updated on-line. Instead, the effects of these errors are used to update the actual control signal, which leads to a simple design strategy. The model-error control synthesis approach is used in conjunction with a variable structure controller to suppress the wing-rock motion of a slender delta wing. Simulation results indicate that the model-error control synthesis approach is extremely effective in providing closed-loop robustness in the face of significant model uncertainties and disturbance inputs.