Observer-based indirect adaptive fuzzy-neural tracking control for nonlinear SISO systems using VSS and H∞ approaches

Lin, Tsung Chih; Wang, Chi-Hsu; Liu, Han Leih

doi:10.1016/s0165-0114(03)00167-2

Cited by 60 publications

(46 citation statements)

References 24 publications

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“…However, f (x, t) and g(x, t) are unknown and external disturbance, d(t) ̸ = 0, the ideal control effort (16) cannot be implemented. We replace f (x, t), g(x, t) and u ap by the fuzzy logic system f (x|θ f ), g(y|θ g ) and h(s|θ h ) in specified form as [9], [17]- [19], i.e.,…”

Section: Uncertain Fractional Order Chaotic Systems Tracking Design Vmentioning

confidence: 99%

“…Based on the trade-off between plant knowledge and control knowledge, the weighting factor α ∈ [1, 1] can be adjusted. Therefore, the total control effort can be expressed as (19) where the direct adaptive fuzzy controller u d and the indirect adaptive fuzzy controller u i are given as follows:…”

Section: Uncertain Fractional Order Chaotic Systems Tracking Design Vmentioning

confidence: 99%

“…Theorem: Consider the fractional order SISO nonlinear chaotic system (12) with control input (19), if the fuzzy-based adaptive laws are chosen as…”

Section: Uncertain Fractional Order Chaotic Systems Tracking Design Vmentioning

confidence: 99%

“…Using the corollary of Barbalat's Lemma [16]- [19], we have lim t→∞ |s(x, t)| = 0. Therefore, lim t→∞ |e(t)| = 0.…”

Section: Dθdmentioning

confidence: 99%

“…Like the conventional adaptive control, the adaptive fuzzy control is classified into direct and indirect fuzzy adaptive control categories [9], [17]- [19]. A direct adaptive fuzzy controller uses fuzzy logic systems as controller in which linguistic fuzzy control rules can be directly incorporated into the controller.…”

Section: Introduction In Domainmentioning

confidence: 99%

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Uncertain Fractional Order Chaotic Systems Tracking Design via Adaptive Hybrid Fuzzy Sliding Mode Control

Lin

Kuo

Balas

2011

INT J COMPUT COMMUN

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In this paper, in order to achieve tracking performance of uncertain fractional order chaotic systems an adaptive hybrid fuzzy controller is proposed. During the design procedure, a hybrid learning algorithm combining sliding mode control and Lyapunov stability criterion is adopted to tune the free parameters on line by output feedback control law and adaptive law. A weighting factor, which can be adjusted by the trade-off between plant knowledge and control knowledge, is adopted to sum together the control efforts from indirect adaptive fuzzy controller and direct adaptive fuzzy controller. To confirm effectiveness of the proposed control scheme, the fractional order chaotic response system is fully illustrated to track the trajectory generated from the fractional order chaotic drive system. The numerical results show that tracking error and control effort can be made smaller and the proposed hybrid intelligent control structure is more flexible during the design process.

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Section: Uncertain Fractional Order Chaotic Systems Tracking Design Vmentioning

confidence: 99%

Section: Uncertain Fractional Order Chaotic Systems Tracking Design Vmentioning

confidence: 99%

“…Theorem: Consider the fractional order SISO nonlinear chaotic system (12) with control input (19), if the fuzzy-based adaptive laws are chosen as…”

Section: Uncertain Fractional Order Chaotic Systems Tracking Design Vmentioning

confidence: 99%

“…Using the corollary of Barbalat's Lemma [16]- [19], we have lim t→∞ |s(x, t)| = 0. Therefore, lim t→∞ |e(t)| = 0.…”

Section: Dθdmentioning

confidence: 99%

Section: Introduction In Domainmentioning

confidence: 99%

See 3 more Smart Citations

Uncertain Fractional Order Chaotic Systems Tracking Design via Adaptive Hybrid Fuzzy Sliding Mode Control

Lin

Kuo

Balas

2011

INT J COMPUT COMMUN

Self Cite

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Switched adaptive control for a class of switched nontriangular nonlinear systems with vanishing control gains

Xie

Yang

Zhao

2019

Intl J Robust & Nonlinear

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Summary In this paper, the adaptive control problem for a class of switched nontriangular nonlinear systems is investigated, which allows the control gains to vanish at some points. Neither the triangular structure nor the solvability of the adaptive control problem is required for each subsystem. A key point of this work is to solve the adaptive control problem of switched nontriangular nonlinear systems with vanishing control gains by the dual design of the controllers and switching signals. To this end, firstly, a hysteresis‐type control gains‐dependent switching law is designed, which makes the control gain of the active subsystem not vanish and thus the associated designed control input can enter into the active subsystem. Moreover, the designed switching law guarantees a dwell time between any adjacent switching instants, which rules out the Zeno behavior. Secondly, when the adaptive control problem of each subsystem is unsolvable, a sufficient condition ensuring the solvability of the adaptive control problem of switched nontriangular nonlinear systems is developed even if no control input can enter into subsystems at some points. Finally, the effectiveness of the proposed result is illustrated by two examples.

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Multiple Lyapunov functions‐based adaptive neural network tracking control of uncertain switched nonlinear systems

Long

2019

Intl J Robust & Nonlinear

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Summary In this paper, the problem of adaptive neural network (NN) tracking control of a class of switched strict‐feedback uncertain nonlinear systems is investigated by state‐feedback, in which the solvability of the problem of adaptive NN tracking control for individual subsystems is unnecessary. A multiple Lyapunov functions (MLFs)–based adaptive NN tracking control scheme is established by exploiting backstepping and the generalized MLFs approach. Moreover, based on the proposed scheme, adaptive NN controllers of all subsystems and a state‐dependent switching law simultaneously are constructed, which guarantee that all signals of the resulting closed‐loop system are semiglobally uniformly ultimately bounded, and the tracking error converges to a small neighborhood of the origin. The scheme provided permits removal of a technical condition in which the adaptive NN tracking control problem for individual subsystems is solvable. Finally, the effectiveness of the design scheme proposed is shown by using two examples.

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Observer-based indirect adaptive fuzzy-neural tracking control for nonlinear SISO systems using VSS and H∞ approaches

Cited by 60 publications

References 24 publications

Uncertain Fractional Order Chaotic Systems Tracking Design via Adaptive Hybrid Fuzzy Sliding Mode Control

Uncertain Fractional Order Chaotic Systems Tracking Design via Adaptive Hybrid Fuzzy Sliding Mode Control

Switched adaptive control for a class of switched nontriangular nonlinear systems with vanishing control gains

Multiple Lyapunov functions‐based adaptive neural network tracking control of uncertain switched nonlinear systems

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