A reconfigurable PID fault tolerant tracking controller design for LPV systems

Rabaoui, Bouali; Hamdi, Habib; Braïek, Naceur Benhadj; Rodrigues, Mickaël

doi:10.1016/j.isatra.2019.08.049

Cited by 16 publications

(8 citation statements)

References 17 publications

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“…Depending on the comparison result, the controller gives new control signals thanks to the proposed PID-AFTTC algorithm which allows to tolerate actuator faults and track trajectories. In contrast to Rabaoui approach, 8 who has considered only a linear output and an actuator fault for LPV systems, the proposed method concerns the class of systems with LPV output equations under a more critical situation in the presence of both sensor and actuator faults. The comparison with Makni approach, 11 which has developed a FTTC with a passive structure, proves that the control algorithm of our proposed PID-AFTTC is better by ensuring the tracking trajectories with high performances in terms of accuracy and rapidity.…”

Section: Discussionmentioning

confidence: 99%

See 1 more Smart Citation

Descriptor observer‐based sensor and actuator fault tolerant tracking control design for linear parameter varying systems

Rabaoui

Hamdi

Braïek

et al. 2020

Intl J Robust & Nonlinear

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This article investigates the design of a descriptor observer (DO)-based sensor and actuator fault (SAF) tolerant tracking control for linear parameter varying (LPV) systems with LPV outputs and disturbed by unknown inputs. The fault tolerant tracking control closed loop system is made of: a DO, a proportional integral derivative (PID) AF tolerant tracking controller, and a sensor fault compensation block. The proposed approach gives a solution to the tracking control problem for this class of systems where the observer and the controller gain matrices can be obtained by solving an optimization problem. The main advantages of this approach with regard to previous approaches are getting around a critical situation which is that the studied LPV system is subject to SAFs simultaneously and unknown inputs, with less conservative results and improving trajectory tracking performances especially in terms of accuracy and rapidity. The performances of the proposed approach are compared to a previous study through a numerical example which is carried out on an hydraulic system.

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Section: Discussionmentioning

confidence: 99%

“…To obtain the expression of the dynamic of the tracking error ̇ē t (t) from Equation (36), the following assumption will be necessary: Assumption 6 (8). The matrices Δ ij ∈ ℜ (n+m)×(n+m) are assumed to be invertible; that is:…”

Section: Augmented System Synthesismentioning

confidence: 99%

Descriptor observer‐based sensor and actuator fault tolerant tracking control design for linear parameter varying systems

Rabaoui

Hamdi

Braïek

et al. 2020

Intl J Robust & Nonlinear

View full text Add to dashboard Cite

show abstract

“…In general, the FTC approaches [2][3][4][5][6][7][8][9][10][11] can be divided into two categories: active fault-tolerant control (AFTC) and passive fault-tolerant control (PFTC). PFTC mainly counts on the robustness of the controller itself to reduce the influence of a class of presumed faults.…”

Section: Introductionmentioning

confidence: 99%

“…AFTC approaches mainly utilize real‐time fault detection and diagnosis module to obtain the fault information, and then reconstruct the control law to make the system obtain a more satisfactory control effect 6 . In Reference 7, a reconfigurable Proportional‐Integral‐Derivative Fault Tolerant Tracking Controller is proposed for the Linear Parameter Varying systems with actuator faults and disturbances. In Reference 8, the bias, drift, and loss of accuracy additive faults are considered.…”

Section: Introductionmentioning

confidence: 99%

Observer‐based single‐network incremental adaptive dynamic programming for fault‐tolerant control of nonlinear systems with actuator faults

Zhang

2022

Adaptive Control & Signal

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Summary A model‐free incremental adaptive fault‐tolerant control (FTC) scheme is proposed for a class of nonlinear systems with actuator faults. To deal with actuator faults and guarantee the approximate optimal performance of the nominal nonlinear system without any prior knowledge of system dynamics, a single‐network incremental adaptive dynamic programming (SIADP) algorithm based on incremental neural network observer is developed to design an active fault‐tolerant control (AFTC) policy. An approximate linear time‐varying system is obtained by incremental nonlinear technique, in which the relevant matrix parameters are identified by recursive least square estimation. Then, a SIADP algorithm‐based fault‐tolerant controller is developed. Based on the redundancy characteristic and function of actuators, a grouping scheme of actuators is introduced. An incremental neural network observer is designed to approximate the actuator faults. The novel SIADP scheme is constructed with a simplified single critic neural network to shorten the learning time and decrease the computational burden in the control process, in which the norm of the weight estimations of critic neural network is updated. Moreover, based on the Lyapunov theorem, the uniformly ultimately bounded stability of the closed‐loop incremental system is proved. Finally, simulations are given to verify the effectiveness of the proposed FTC scheme.

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“…In Reference 8, linear quadratic regular (LQR) based model reference adaptive controller (MRAC) is designed to deal with the parameter variation and actuator failure due to vertical tail damaged aircraft. Some recent results on the FTC strategy belong to the class of the LPV system are obtained in References 9‐12. CA scheme is considered an effective strategy to deal with actuator faults/failures specifically when sufficient redundant actuators are available in the system.…”

Section: Introductionmentioning

confidence: 99%

A new actuator fault‐tolerant control for Lipschitz nonlinear system using adaptive sliding mode control strategy

Ijaz

Chen

Hamayun

2021

Intl J Robust & Nonlinear

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This article proposed a new adaptive integral sliding mode (ISM) based fault‐tolerant control (FTC) strategy to solve the actuator's faults and failures compensation problem for the class of Lipschitz nonlinear systems. A nominal state feedback virtual control law is designed first to stabilize the Lipschitz nonlinear system and to attain the desired nominal performance. To cater for the effect of faults and failures, the control allocation (CA) scheme reorganizes the virtual input signals among the healthy redundant actuators based on actuator's effectiveness level. Then, a nonlinear adaptive integral sliding mode controller (ISMC) is incorporated with the CA scheme to compensate for unknown disturbance and uncertainties effect that arises in the system by virtue of actuator faults/failures and error in fault estimation . An effective synthesis procedure is adopted to ensure the closed‐loop stability condition using linear matrix inequality (LMI) optimization. Finally, the FTC scheme is tested to achieve maneuvering control of coaxial octorotor unmanned aerial vehicle (UAV) system. Simulations are performed on the nonlinear system at different actuator faults/failures combinations. Moreover, the effect of wind‐gust, parameter variations, estimated state feedback and sensor noise are considered in nonlinear simulations. Finally, the results obtained during faults/failures are compared with the nominal condition and fixed ISMC based CA scheme.

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A reconfigurable PID fault tolerant tracking controller design for LPV systems

Cited by 16 publications

References 17 publications

Descriptor observer‐based sensor and actuator fault tolerant tracking control design for linear parameter varying systems

Descriptor observer‐based sensor and actuator fault tolerant tracking control design for linear parameter varying systems

Observer‐based single‐network incremental adaptive dynamic programming for fault‐tolerant control of nonlinear systems with actuator faults

A new actuator fault‐tolerant control for Lipschitz nonlinear system using adaptive sliding mode control strategy

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