Adaptive Fuzzy Output-Feedback Control Design for a Class of p-Norm Stochastic Nonlinear Systems With Output Constraints

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.

Automated summary

This paper addresses the control problem of p-norm stochastic nonlinear systems with output constraints, proposing an adaptive fuzzy output-feedback control strategy. By constructing a nonlinear observer and utilizing a barrier Lyapunov function, the proposed scheme ensures all signals of the closed-loop systems are bounded and do not violate output constraints.