This paper proposes a new higher order model reference adaptive control (HO-MRAC) approach following direct adaptive control philosophy, which estimates unknown time-varying parameters. This approach leads to a Lyapunov based conventional MRAC update law, augmented by an observer type parameter predictor dynamics. The predictor dynamics are composed of a stable known part, a feedback of the parameter error and unknown higher order parameters, which are updated using a Lyapunov based adaptive design. So, this HO-MRAC can cope with rapidly changing parameters, due to estimation of their time derivatives. Moreover, for stability analysis, a Lyapunov based generic ultimate boundedness theorem is presented, which allows for a computation of separate bounds for each state vector partition. Furthermore, this theorem formulates the explicit specification of transient and ultimate bounds, reaching time on the ultimate bounds and a set of admissible initial conditions. Two challenging illustrative examples demonstrate the effectiveness of the proposed approach.
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This paper proposes a new higher order model reference adaptive control (HO-MRAC) approach following direct adaptive control philosophy, which estimates unknown time-varying parameters. This approach leads to a Lyapunov based conventional MRAC update law, augmented by an observer type parameter predictor dynamics. The predictor dynamics are composed of a stable known part, a feedback of the parameter error and unknown higher order parameters, which are updated using a Lyapunov based adaptive des...
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