Abstract:

An adaptive control method based on adaptive-network-based fuzzy inference system（ANFIS）and multiple models is proposed for a class of uncertain discrete-time nonlinear systems with unstable zero-dynamics.The method is composed of a linear robust adaptive controller，a nonlinear adaptive controller using ANFIS and a switching mechanism.The linear controller ensures the boundedness of the input and output signals，and the nonlinear controller improves performance of the system.By using the switching scheme，both improved performance and stability are achieved simultaneously.When the ANFIS is used as a compensator for the unmodelled dynamics，firstly，a continuous，monotonic and invertible one-to-one mapping is used in this paper to transfer the non-compact definition domain of the unmodelled dynamics into a bounded closed set.As a result，the universal approximation property of ANFIS can be guaranteed.Furthermore，the ANFIS can successfully tackle the relatively low convergence rate of neural network and avoid the possibility that the network becomes trapped in local minima，thereby improving the control effect.A lemma is established and the analysis of stability and convergence of the closed-loop system are proven theoretically.Last，by comparing the simulation results，the effectiveness of the proposed method is illustrated.