Robust fuzzy control subject to state variance and passivity constraints for perturbed nonlinear systems with multiplicative noises

Chang, Wen‐Jer; Huang, Bo-Jyun

doi:10.1016/j.isatra.2014.08.016

Cited by 17 publications

(11 citation statements)

References 33 publications

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“…The proof of Lemma 3 is given in Appendix B. (10) and (11) is FTB with respect to (0, c 2 , T, R 1 , R 2 , d) and (12) is satisfied, if there exist two scalar α ≥ 0, γ ≥ 0 and two symmetric positive definite matrices Q 1 ∈R n 1 Ân 1 , Q 2 ∈R n 2 Ân 2 such that…”

Section: Lemma 1 ([29]mentioning

confidence: 99%

“…Theorem 1. There exists a state feedback in the form of (9) such that the closed-loop system (1) , (10) and (11) is FTB with respect to (0, c 2 , T, R 1 , R 2 , d) and (12) is satisfied, if letting e…”

Section: Lemma 1 ([29]mentioning

confidence: 99%

“…When external disturbances are considered for the system, the notion of FTS is extended to Finite‐Time Boundedness (FTB). In the light of results coming from Linear Matrix Inequality (LMI) theory, many optimization and control problems can be formulated and solved by using LMIs . Sufficient conditions for FTB and FTS of linear time‐invariant systems were derived in .…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Robust Finite‐Time H_∞ Control of a Class of Disturbed Systems using Lmi‐Based Approach

Zhang

Zhong

Zhang

et al. 2016

Asian Journal of Control

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In this paper, the definition of robust finite‐time H∞ control is presented for a class of disturbed systems. Time‐varying norm‐bounded exogenous disturbance is considered in the system. A state feedback controller is designed, via a Linear Matrix Inequalities (LMIs) approach, which ensures that the closed‐loop system is finite‐time bounded (FTB) and reduces the effect of the disturbance input on the controlled output to a prescribed level. The main result, derived by Lyapunov functions, is a sufficient condition for FTB of disturbed systems and the sufficient condition can be reduced to a feasibility problem involving LMIs. Then a DC motor position control problem is simulated as a demonstration for this study. Simulation results are presented to show the effectiveness of the proposed method as a promising approach for controlling similar disturbed systems.

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Section: Lemma 1 ([29]mentioning

confidence: 99%

Section: Lemma 1 ([29]mentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Robust Finite‐Time H_∞ Control of a Class of Disturbed Systems using Lmi‐Based Approach

Zhang

Zhong

Zhang

et al. 2016

Asian Journal of Control

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“…In this paper, the signal of external disturbance is considered as a stochastic behavior. Solving the control problem of stochastic external disturbance, several papers have already developed the control theory by combining the covariance control theory and passivity theory successfully [19,20]. In addition to suppressing the effect of stochastic behaviors by the variance constraint, the passivity theory is also applied to dissipate its energy.…”

Section: Introductionmentioning

confidence: 99%

Pole Location and Input Constrained Robust Fuzzy Control for T-S Fuzzy Models Subject to Passivity and Variance Requirements

Qiao¹,

Chang

Lin

et al. 2021

Processes

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In this paper, a robust fuzzy controller for stochastic nonlinear systems subject to multiple performance constraints is discussed. To solve the problem of stochastic behaviors in nonlinear systems, the covariance control theory and passive control theory are applied based on the concept of energy. Additionally, the pole placement method is considered for the better transient behaviors of the system responses. However, it is known that the control inputs and maximum overshoot of the system responses may become bigger at the same time when the settling time or converge rate of the system is required to be faster. Due to this reason, the input constraint is also considered in the fuzzy controller design method to limit the value of the control gain. Moreover, an effective robust control method is applied to deal with the perturbation of the nonlinear systems. Based on the above performance constraints, the sufficient conditions can be obtained to achieve the stability in the sense of mean square and the multi-performance requirements. Finally, simulation results of the nonlinear synchronous generator system are presented to verify the feasibility and efficiency of the proposed control method.

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“…Thus, any control law based on a linearised representation is a compromise [1] to hydroelectric systems. In this case, an increasing number of state‐of‐the‐art control schemes, such as adaptive control [12–17], sliding model control [11, 12, 18, 19], fuzzy control [20–24], model predictive control (MPC) [25–32] and so on, are able to be considered to govern a large hydroelectric plant. Compared with the above‐mentioned control methods, MPC, specifically generalised predictive control (GPC), is researched as the basis of this paper.…”

Section: Introductionmentioning

confidence: 99%

Non‐linear fuzzy predictive control of hydroelectric system

Zhang

Chen

Yao

et al. 2017

IET Generation, Transmission & Distribution

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Robust fuzzy control subject to state variance and passivity constraints for perturbed nonlinear systems with multiplicative noises

Cited by 17 publications

References 33 publications

Robust Finite‐Time H_∞ Control of a Class of Disturbed Systems using Lmi‐Based Approach

Robust Finite‐Time H_∞ Control of a Class of Disturbed Systems using Lmi‐Based Approach

Pole Location and Input Constrained Robust Fuzzy Control for T-S Fuzzy Models Subject to Passivity and Variance Requirements

Non‐linear fuzzy predictive control of hydroelectric system

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Robust fuzzy control subject to state variance and passivity constraints for perturbed nonlinear systems with multiplicative noises

Cited by 17 publications

References 33 publications

Robust Finite‐Time H∞ Control of a Class of Disturbed Systems using Lmi‐Based Approach

Robust Finite‐Time H∞ Control of a Class of Disturbed Systems using Lmi‐Based Approach

Pole Location and Input Constrained Robust Fuzzy Control for T-S Fuzzy Models Subject to Passivity and Variance Requirements

Non‐linear fuzzy predictive control of hydroelectric system

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Product

Resources

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Robust Finite‐Time H_∞ Control of a Class of Disturbed Systems using Lmi‐Based Approach

Robust Finite‐Time H_∞ Control of a Class of Disturbed Systems using Lmi‐Based Approach