20182018 IEEE International Conference on Cyborg and Bionic Systems (CBS)Requires access

An adaptive fuzzy sliding mode controller for the depth control of an underactuated underwater vehicle

ShuQi Liu, Yuan Chen, Guangying Ma

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Abstract

An adaptive fuzzy sliding mode controller (AFSMC-A control method combining fuzzy control and sliding mode control; it is an intelligent control method for effective control of complex objects in an uncertain environment.) is proposed for depth control of an underactuated underwater vehicle based on the state-dependent Riccati equation. A proportional integral (PI-The integral action makes the output of the controller proportional to the integral of the deviation, so there is no residual at the end of the excess process, but with the integration effect, the stability is reduced.) control unit is integrated into a sliding mode controller (SMC-Essentially a special kind of nonlinear control, and nonlinearity appears as a control discontinuity.) for its control performance improvements and the steady-state error minimization. The issues on undesirable high frequency chattering in the PI plus SMC are addressed by an adaptive algorithm. A fuzzy controller instead of a switching control section of the robust variable structure is used to ensure the robustness of uncertain systems. Simulation results show that the effective depth control can be accomplished in the presence of various uncertainties.

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What this paper is about

An adaptive fuzzy sliding mode controller (AFSMC-A control method combining fuzzy control and sliding mode control; it is an intelligent control method for effective control of complex objects in an uncertain environment.) is proposed for depth control of an underactuated underwater vehicle based on the state-dependent Riccati equation. A proportional integral (PI-The integral action makes the output of the controller proportional to the integral of the deviation, so there is no residual at the end of the excess process, but with the integration effect, the stability is reduced.) control unit is integrated into a sliding mode controller (SMC-Essentially a special kind of nonlinear control, and nonlinearity appears as a control discontinuity.) for its control performance improvements and the steady-state error minimization. The issues on undesirable high frequency chattering in the PI plus SMC are addressed by an adaptive algorithm. A fuzzy controller instead of a switching control section of the robust variable structure is used to ensure the robustness of uncertain systems. Simulation results show that the effective depth control can be accomplished in the presence of various uncertainties.

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Available abstract

An adaptive fuzzy sliding mode controller (AFSMC-A control method combining fuzzy control and sliding mode control; it is an intelligent control method for effective control of complex objects in an uncertain environment.) is proposed for depth control of an underactuated underwater vehicle based on the state-dependent Riccati equation. A proportional integral (PI-The integral action makes the output of the controller proportional to the integral of the deviation, so there is no residual at the end of the excess process, but with the integration effect, the stability is reduced.) control unit is integrated into a sliding mode controller (SMC-Essentially a special kind of nonlinear control, and nonlinearity appears as a control discontinuity.) for its control performance improvements and the steady-state error minimization. The issues on undesirable high frequency chattering in the PI plus SMC are addressed by an adaptive algorithm. A fuzzy controller instead of a switching control section of the robust variable structure is used to ensure the robustness of uncertain systems. Simulation results show that the effective depth control can be accomplished in the presence of various uncertainties.

Key concepts: Control theory (sociology), Underactuation, Sliding mode control, Integral sliding mode, Robustness (evolution), Fuzzy logic, Variable structure control, Fuzzy control system

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