Reduced Adaptive Fuzzy Tracking Control for High-Order Stochastic Nonstrict Feedback Nonlinear System With Full-State Constraints

Sun, Wei; Su, Shun‐Feng; Dong, Guowei; Bai, Weiwei

doi:10.1109/tsmc.2019.2898204

Cited by 152 publications

(76 citation statements)

References 52 publications

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“…The feasibility of the presented algorithm has been verified by a demonstrative simulation. In our future work, it will be an interesting and challenging issue to apply the method proposed in this paper to the neural network in [42][43][44], containment control in [45,46], sliding mode control in [47], and adaptive fuzzy control in [48,49].…”

Section: Resultsmentioning

confidence: 99%

Reliable Dissipative Interval Type-2 Fuzzy Control for Nonlinear Systems with Stochastic Incomplete Communication Route and Actuator Failure

Pan

Zhang

et al. 2020

Int. J. Fuzzy Syst.

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Section: Resultsmentioning

confidence: 99%

Reliable Dissipative Interval Type-2 Fuzzy Control for Nonlinear Systems with Stochastic Incomplete Communication Route and Actuator Failure

Pan

Zhang

et al. 2020

Int. J. Fuzzy Syst.

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“…There are still some other sticky challenges, for instance, unknown control direction, state constraints, multiagent systems, prescribed performance, system security, and actuator faults, which will be our future research.…”

Section: Resultsmentioning

confidence: 99%

Multigradient recursive reinforcement learning NN control for affine nonlinear systems with unmodeled dynamics

Bai

Zhang

Zhou

et al. 2019

Intl J Robust & Nonlinear

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Summary In this paper, an adaptive reinforcement learning approach is developed for a class of discrete‐time affine nonlinear systems with unmodeled dynamics. The multigradient recursive (MGR) algorithm is employed to solve the local optimal problem, which is inherent in gradient descent method. The MGR radial basis function neural network approximates the utility functions and unmodeled dynamics, which has a faster rate of convergence than that of the gradient descent method. A novel strategic utility function and cost function are defined for the affine systems. Finally, it concludes that all the signals in the closed‐loop system are semiglobal uniformly ultimately bounded through differential Lyapunov function method, and two simulation examples are presented to demonstrate the effectiveness of the proposed scheme.

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“…In addition, this assumption is essential to guarantee the error system is convergent rather than only bounded. Assumption 2 is used commonly to address the reference signal [ 30 , 36 ] and is conventionally true in practice [ 37 ]. Contrary to the assumption adopted in [ 38 ], Assumption 2 relaxes the boundedness of desired output trajectory signal

.…”

Section: Problem Formulation and Preliminariesmentioning

confidence: 99%

Event-Triggered Adaptive Fault Tolerant Control for a Class of Uncertain Nonlinear Systems

Zhu

Chen

et al. 2020

Entropy

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This paper considers an adaptive fault-tolerant control problem for a class of uncertain strict feedback nonlinear systems, in which the actuator has an unknown drift fault and the loss of effectiveness fault. Based on the event-triggered theory, the adaptive backstepping technique, and Lyapunov theory, a novel fault-tolerant control strategy is presented. It is shown that an appropriate comprise between the control performance and the sensor data real-time transmission consumption is made, and the fault-tolerant tracking control problem of the strict feedback nonlinear system with uncertain and unknown control direction is solved. The adaptive backstepping method is introduced to compensate the actuator faults. Moreover, a new adjustable event-triggered rule is designed to determine the sampling state instants. The overall control strategy guarantees that the output signal tracks the reference signal, and all the signals of the closed-loop systems are convergent. Finally, the fan speed control system is constructed to demonstrate the validity of the proposed strategy and the application of the general systems.

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Reduced Adaptive Fuzzy Tracking Control for High-Order Stochastic Nonstrict Feedback Nonlinear System With Full-State Constraints

Cited by 152 publications

References 52 publications

Reliable Dissipative Interval Type-2 Fuzzy Control for Nonlinear Systems with Stochastic Incomplete Communication Route and Actuator Failure

Reliable Dissipative Interval Type-2 Fuzzy Control for Nonlinear Systems with Stochastic Incomplete Communication Route and Actuator Failure

Multigradient recursive reinforcement learning NN control for affine nonlinear systems with unmodeled dynamics

Event-Triggered Adaptive Fault Tolerant Control for a Class of Uncertain Nonlinear Systems

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