Adaptive fuzzy output-feedback control design for a class of P-norm stochastic nonlinear systems with output constraints

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Abstract

This paper considers the control problem of p-norm stochastic nonlinear systems with output constraints, while the system nonlinearities are completely unknown and the system states are unavailable except the output. A nonlinear observer is constructed to estimate the unmeasurable states. Then, based on the constructed observer and a tan-type barrier Lyapunov function (BLF), an adaptive fuzzy output-feedback control strategy is developed by combining the technique of adding a power integrator with the fuzzy logic systems (FLSs). The proposed scheme enables that all the signals of the considered closed-loop systems are bounded in probability while the prespecified output constraint is not violated. Finally, a numerical example verifies the validation of the proposed scheme.

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Fang, L., Ding, S., Park, J. H., & Ma, L. (2021). Adaptive fuzzy output-feedback control design for a class of P-norm stochastic nonlinear systems with output constraints. IEEE Transactions on Circuits and Systems I: Regular Papers, 68(6), 2626–2638. https://doi.org/10.1109/TCSI.2021.3063084

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