A Simplified Adaptive Fixed Time Control of Pure‐Feedback Stochastic Nonlinear Systems Subject to Full State Constraints
ABSTRACT In this paper, a novel fixed time adaptive fuzzy control scheme for pure‐feedback stochastic nonlinear systems with full state constraints is proposed based on dynamic surface control (DSC) technique and barrier Lyapunov functions (BLFs) method. Firstly, the mean value theorem is utilized t...
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Published in | International journal of adaptive control and signal processing Vol. 39; no. 4; pp. 829 - 840 |
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Main Authors | , , , , |
Format | Journal Article |
Language | English |
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Hoboken, USA
John Wiley & Sons, Inc
01.04.2025
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Abstract | ABSTRACT
In this paper, a novel fixed time adaptive fuzzy control scheme for pure‐feedback stochastic nonlinear systems with full state constraints is proposed based on dynamic surface control (DSC) technique and barrier Lyapunov functions (BLFs) method. Firstly, the mean value theorem is utilized to transform the pure‐feedback structure of the considered systems into strict‐feedback ones, which make it possible for the utilization of backstepping method to design the controller. Then, DSC technique is used to reduce the computational complexity problem caused by backstepping method. Fuzzy logic systems are exploited to approximate the unknown nonlinear functions. Moreover, combine BLFs method with fixed time stability theorem, the fixed time adaptive fuzzy controller is constructed, which guarantees that all states do not violate the prescribed constraints and all signals are semi‐globally uniform ultimately bounded. Finally, a simulation example is given to verify the effectiveness of the studied control.
A novel fixed time adaptive fuzzy control scheme for pure‐feedback stochastic nonlinear systems with full state constraints is proposed based on dynamic surface control technique and barrier Lyapunov functions. DSC technique is used to reduce the computational complexity problem caused by backstepping method. Fixed time adaptive fuzzy controller is constructed, which guarantees that all states do not violate the prescribed constraints and all signals are semi‐globally uniform ultimately bounded. |
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AbstractList | ABSTRACT
In this paper, a novel fixed time adaptive fuzzy control scheme for pure‐feedback stochastic nonlinear systems with full state constraints is proposed based on dynamic surface control (DSC) technique and barrier Lyapunov functions (BLFs) method. Firstly, the mean value theorem is utilized to transform the pure‐feedback structure of the considered systems into strict‐feedback ones, which make it possible for the utilization of backstepping method to design the controller. Then, DSC technique is used to reduce the computational complexity problem caused by backstepping method. Fuzzy logic systems are exploited to approximate the unknown nonlinear functions. Moreover, combine BLFs method with fixed time stability theorem, the fixed time adaptive fuzzy controller is constructed, which guarantees that all states do not violate the prescribed constraints and all signals are semi‐globally uniform ultimately bounded. Finally, a simulation example is given to verify the effectiveness of the studied control.
A novel fixed time adaptive fuzzy control scheme for pure‐feedback stochastic nonlinear systems with full state constraints is proposed based on dynamic surface control technique and barrier Lyapunov functions. DSC technique is used to reduce the computational complexity problem caused by backstepping method. Fixed time adaptive fuzzy controller is constructed, which guarantees that all states do not violate the prescribed constraints and all signals are semi‐globally uniform ultimately bounded. In this paper, a novel fixed time adaptive fuzzy control scheme for pure‐feedback stochastic nonlinear systems with full state constraints is proposed based on dynamic surface control (DSC) technique and barrier Lyapunov functions (BLFs) method. Firstly, the mean value theorem is utilized to transform the pure‐feedback structure of the considered systems into strict‐feedback ones, which make it possible for the utilization of backstepping method to design the controller. Then, DSC technique is used to reduce the computational complexity problem caused by backstepping method. Fuzzy logic systems are exploited to approximate the unknown nonlinear functions. Moreover, combine BLFs method with fixed time stability theorem, the fixed time adaptive fuzzy controller is constructed, which guarantees that all states do not violate the prescribed constraints and all signals are semi‐globally uniform ultimately bounded. Finally, a simulation example is given to verify the effectiveness of the studied control. |
Author | Li, Mengyang Wang, Nan Tao, Fazhan Fu, Zhumu Fan, Pengyu |
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In this paper, a novel fixed time adaptive fuzzy control scheme for pure‐feedback stochastic nonlinear systems with full state constraints is proposed... In this paper, a novel fixed time adaptive fuzzy control scheme for pure‐feedback stochastic nonlinear systems with full state constraints is proposed based on... |
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SubjectTerms | Adaptive control adaptive fuzzy fixed time control barrier Lyapunov functions Constraints Control systems Control systems design Controllers Differential calculus dynamic surface control Feedback Feedback control systems Fuzzy control Fuzzy logic Fuzzy systems Liapunov functions Nonlinear systems pure‐feedback stochastic nonlinear systems Simulation Stochastic systems |
Title | A Simplified Adaptive Fixed Time Control of Pure‐Feedback Stochastic Nonlinear Systems Subject to Full State Constraints |
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