This paper presents an integrated control design approach for a class of dynamical systems that satisfy a certain matching condition subject to known input time-delay, unknown parameters, and time-varying disturbances, simultaneously. A novel nonlinear predictor adaptive robust control (PARC) is proposed to track a desired state trajectory. The controller uses predictor-based model compensation to attenuate the effect of input time-delay, gradient type projection with prediction-based learning mechanisms to reduce the parameter uncertainties, and prediction-based nonlinear robust feedback to attenuate the effect of model approximation errors and disturbances, simultaneously. The controller guarantees a prescribed transient performance (with global exponential convergence) and final steady-state tracking error with an ultimate bound proportional to the time-delay, the disturbances, and the switching gain. The effectiveness of the proposed control design is illustrated with a simple tumor growth example.


This is the publishers version of Jayaprakash, Suraj & Kwon, Cheolhyeon & Hwang, Inseok. (2017). Prediction-based Adaptive Robust Control for a Class of Uncertain Time-delay Systems. IFAC-PapersOnLine. 50. 6489-6494. 10.1016/j.ifacol.2017.08.1046.


Predictor feedback, adaptive control, sliding mode control, tracking, stability

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