Fuzzy Adaptive Fault-Tolerant Control for Uncertain Nonlinear Systems With Unknown Dead-Zone and Unmodeled Dynamics

Jing, Yan-Hui; Yang, Guang‐Hong

doi:10.1109/tfuzz.2019.2896844

Cited by 61 publications

(13 citation statements)

References 60 publications

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“…In the design of control system, besides considering disturbances, the dead-zone in actuators and unmodeled dynamics are also significant that need to be taken into accountconsidered. A methodology to deal with the dead-zone input and unmodeled dynamics was recently studied in [3], where the dead-zone was simply defined as hysteretic properties of the system and the unmodeled dynamics was assumed to be bounded by some constants. Due to its approximation capability, fuzzy logic system (FLS) has been frequently utilized in many practical systems subjected to unmodeled dynamics, parameter variations and non-predictable nonlinear parameters-, i.e.g., actuators and sensor faults.…”

Section: Introductionmentioning

confidence: 99%

Robust control for vibration control systems with dead-zone band and time delay under severe disturbance using adaptive fuzzy neural network

Phu

Van

2020

Journal of the Franklin Institute

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This study proposes a novel adaptive control method to deal with the dead-zone and time delay issues in actuators of vibration control systems. The controller is formulated based on a type-2 fuzzy neural network integrating with a new modification of Riccati-like equation. The developed new type Riccati-like equation is significant as it reduces energy consumption of control inputs to minimum. Two approaches are suggested to improve performance of the system using the basic elements of Riccati equation. In addition, a fuzzy neural network is applied to approximate the unmodeled dynamics and a sliding mode controller is developed to enhance the robustness of the system against uncertainties and disturbances. After proving the stability of the proposed controller via Lyapunov criterion, the effectiveness of the proposed approach is validated based on computer simulation for vibration control of a vehicle seat suspension. It is demonstrated that the unwanted vibrations due to external excitations are well controlled despite of the presence of dead-zone and time delay in actuators. Furthermore, when comparing with other two state-of-theart robust controllers [23,36], the proposed controller provides better vibration suppression capacity and requires less energy consumption.

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Section: Introductionmentioning

confidence: 99%

Robust control for vibration control systems with dead-zone band and time delay under severe disturbance using adaptive fuzzy neural network

Phu

Van

2020

Journal of the Franklin Institute

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“…Approximation-based adaptive control provides a way of applying traditional backstepping to nonlinear systems with unknown model dynamics. [1][2][3][4][5] Due to the ability of approximating nonlinear functions, fuzzy logic systems (FLSs), [6][7][8][9] or neural networks (NNs) [10][11][12][13][14] are employed to approximate unknown nonlinear functions. In order to identify the unknown functions better, the experience of experts and knowledge in practice are brought in FLSs.…”

Section: Introductionmentioning

confidence: 99%

“…1. Different from the previous researches in References [6][7][8]10,11, where NNs and FLSs are used to approximate unknown nonlinear functions, we apply the GFHM approximator to obtain better identification effect in this case. References 15,16,20,21, in which the PPC is not considered.…”

Section: Introductionmentioning

confidence: 99%

“…For the moment, few attempts have been made to pursue this idea. The main contributions can be listed as follows.Different from the previous researches in References 6‐8,10,11, where NNs and FLSs are used to approximate unknown nonlinear functions, we apply the GFHM approximator to obtain better identification effect in this case. Compared with the present methods in References 15,16,20,21, in which the PPC is not considered. we develop a GFHM‐dependent adaptive tracking control method for uncertain strict‐feedback MIMO nonlinear systems with prescribed performance.…”

Section: Introductionmentioning

confidence: 99%

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Adaptive prescribed performance tracking control for uncertain strict‐feedback Multiple Inputs and Multiple Outputs nonlinear systems based on generalized fuzzy hyperbolic model

Yang

ZongXue‐Jun

WangGuo‐Gang

2020

Adaptive Control & Signal

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This article proposes an adaptive prescribed performance tracking control methodology for a class of strict-feedback Multiple Inputs and Multiple Outputs nonlinear systems. A combination of backstepping technique and the generalized fuzzy hyperbolic model was used in recursive design of adaptive controller. A novel performance constraint function guarantees the tracking control performance. Lyapunov stability analysis proves that the designed controller can ensure the predefined transient and all signals within the closed-loop systems are semiglobally uniformly ultimately bounded. In the end, simulation results illustrate the validity of the proposed approach.

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“…Common principle of fault-tolerance supposes introducing redundancy into the system structure to substitute failed unit during operation, increases system weight, dimensions, energy consumption, etc. [27], [28], [29], [30]. Per se redundant units themselves are the source of faults.…”

Section: Introductionmentioning

confidence: 99%

Engineering method of fault-tolerant system simulations

Larkin¹,

Privalov²

2019

J Appl Eng Science

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It is shown that common method of units failure compensation, based on an introduction to the system a structural redundancy, leads to the increase of weight/size factor and energy consumption, but sometime does not prolongs its lifetime. The new approach to fault/recovery process modeling, based on use of fundamental apparatus of parallel semi-Markov process, in which ordinary processes simulate the life-cycle of individual units, and the complex process, assembled from ordinary processes, simulates reliability system as a whole, is proposed. Dependences for calculation of time intervals and probabilities of wandering through ordinary semi-Markov processes, with use of the recursive method are obtained. It is shown, that when there is rather complex model of unit life-cycle, semi-Markov process would be replaced with more coarse Markov process. Notions of complex semi-Markov process, such as functional states and semi-Markov matrices Cartesian product are introduced. Theoretical results obtained are confi rmed by the practical calculation of the reliability indicators of the system with passive redundancy.

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Fuzzy Adaptive Fault-Tolerant Control for Uncertain Nonlinear Systems With Unknown Dead-Zone and Unmodeled Dynamics

Cited by 61 publications

References 60 publications

Robust control for vibration control systems with dead-zone band and time delay under severe disturbance using adaptive fuzzy neural network

Robust control for vibration control systems with dead-zone band and time delay under severe disturbance using adaptive fuzzy neural network

Adaptive prescribed performance tracking control for uncertain strict‐feedback Multiple Inputs and Multiple Outputs nonlinear systems based on generalized fuzzy hyperbolic model

Engineering method of fault-tolerant system simulations

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