An adaptive state tracking control scheme for T–S fuzzy models in non-canonical form and with uncertain parameters

Huang, Yuhai; Qi, Ruiyun; Tao, Gang

doi:10.1016/j.jfranklin.2013.05.017

Cited by 8 publications

(4 citation statements)

References 34 publications

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“…Given a constant > 0. Suppose that the function ( ) in the system (12) satisfies conditions (2) and (…”

Section: Discussionmentioning

confidence: 99%

“…The main objective of tracking control is to minimize the error between the state (or output) of the plant and the state (or output) of a given reference model. So it involves two related problems, that is, state feedback tracking controller design [1][2][3] and output feedback tracking controller design [4][5][6][7][8][9]. Among them, the latter is paid much attention because of its attractive features such as low overheads of implementing control, the reliability of control systems, and widely practical applications where measurement of all the state variables is not possible.…”

Section: Introductionmentioning

confidence: 99%

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H∞Static Output Tracking Control of Nonlinear Systems with One-Sided Lipschitz Condition

Liu

Song

2014

Mathematical Problems in Engineering

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This paper is concerned withH∞static output tracking control of nonlinear systems with one-sided Lipschitz condition. The dimensions of system model and reference model may be different. A static output feedback controller is designed to guarantee that the system output asymptotically tracks the reference output withH∞disturbance rejection level. A new sufficient condition is derived to obtain the static output feedback gain by linear matrix inequality (LMI), and no equality constraints can be needed. Finally, an example is given to illustrate the effectiveness of the proposed method.

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“…Given a constant > 0. Suppose that the function ( ) in the system (12) satisfies conditions (2) and (…”

Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

H∞Static Output Tracking Control of Nonlinear Systems with One-Sided Lipschitz Condition

Liu

Song

2014

Mathematical Problems in Engineering

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“…The reentry phase of HSV has the following characteristics: large airspace, transonic speed, multi-stage, nonlinear, strong coupling, severe constraints and severe uncertainty [5,6]. In recent years, there have been a great number of research results, such as predictive control [7], fuzzy control [8], optimal control [9], adaptive sliding mode control [10] and robust control [11].…”

Section: Introductionmentioning

confidence: 99%

Adaptive fault‐tolerant attitude tracking control for hypersonic vehicle with unknown inertial matrix and states constraints

Wang

Yang

et al. 2023

IET Control Theory & Appl

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This paper proposes an adaptive fault‐tolerant control (FTC) method for hypersonic vehicle (HSV) with unexpected centroid shift, actuator fault, time‐varying full state constraints, and input saturation. The occurrence of unexpected centroid shift has three main effects on the HSV system, which are system uncertainties, eccentric moments, and variation of input matrix. In order to ensure the time‐varying state constraints, a novel attitude state constraint control strategy, to keep the safe flight of HSV, is technically proposed by a time‐varying state constraint function (TVSCF). A unified controller is designed to handle the time‐varying state constraints according to the proposed TVSCF. Then, the constrained HSV system can be transformed into a novel free‐constrained system based on the TVSCF. For the variation of system input matrix, input saturation and actuator fault, a special Nussbaum‐type function is designed to compensate for those time‐varying nonlinear terms. Additionally, the auxiliary systems is designed to compensate the constraint of system control inputs. Then, it is proved that the proposed control scheme can guarantee the boundedness of all closed‐loop signals based on the Lyapunov stability theory. At last, the simulation results are provided to demonstrate the effectiveness of the proposed fault‐tolerant control scheme.

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“…In recent years, some effective FTC approaches have been proposed for longitude dynamics of hypersonic vehicles, such as backstepping control, 7 state tracking control 8 and output feedback control. 9 In the study by Qi et al, 7 an adaptive backstepping FTC scheme was proposed for a hypersonic vehicle with parameter uncertainties and actuator fault.…”

Section: Introductionmentioning

confidence: 99%

Adaptive sliding mode fault-tolerant control for hypersonic vehicle based on radial basis function neural networks

Zhai

Jiang

2017

International Journal of Advanced Robotic Systems

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In this article, an adaptive sliding mode fault-tolerant control scheme is proposed to address the problem of robust and fast attitude tracking for a hypersonic vehicle in the presence of unknown external disturbances, additive fault and partial loss of effectiveness fault. Firstly, the healthy and faulty models of the vehicle are given. Then, a radial basis function neural network is designed to estimate the unknown additive fault, and the adaptive method is applied to deal with the unknown partial loss of effectiveness fault. Combined with the sliding mode control theory, the fault-tolerant controllers are designed for the outer and inner loops of the faulty system, respectively. The adaptive laws are designed to update parameter estimates to implement the inner-loop controller. Closed-loop stability is analysed and simulation results verify the effectiveness of the proposed fault-tolerant control scheme.

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An adaptive state tracking control scheme for T–S fuzzy models in non-canonical form and with uncertain parameters

Cited by 8 publications

References 34 publications

H∞Static Output Tracking Control of Nonlinear Systems with One-Sided Lipschitz Condition

H∞Static Output Tracking Control of Nonlinear Systems with One-Sided Lipschitz Condition

Adaptive fault‐tolerant attitude tracking control for hypersonic vehicle with unknown inertial matrix and states constraints

Adaptive sliding mode fault-tolerant control for hypersonic vehicle based on radial basis function neural networks

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