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Adaptive neural network fixed‐time control of p$$ p $$ ‐normal systems with asymmetric output constraints

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This paper studies the problem of fixed‐time H∞$$ {H}_{\infty } $$ control for a class of nonlinear p$$ p $$ ‐normal systems with asymmetric output constraints and external disturbances. Compared… Click to show full abstract

This paper studies the problem of fixed‐time H∞$$ {H}_{\infty } $$ control for a class of nonlinear p$$ p $$ ‐normal systems with asymmetric output constraints and external disturbances. Compared with the existing fixed‐time control schemes, the smooth switching functions are designed to avoid the singularity problem. Then, a time‐varying nonlinear transformation function (NTF) is introduced, blue and a unified tool to deal with the symmetric, asymmetric, and even unconstrained problems simultaneously. Moreover, by adding blue one power integration technology, the H∞$$ {H}_{\infty } $$ controller is designed, which can inhibit the influence of external disturbances on the system. According to Lyapunov stability analysis, the presented fixed‐time H∞$$ {H}_{\infty } $$ blue control method ensures that all signals are bounded in a fixed time. In the end, two simulation examples demonstrate the effectiveness of the proposed scheme.

Keywords: asymmetric output; time; control; systems asymmetric; fixed time; normal systems

Journal Title: Asian Journal of Control
Year Published: 2023

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