Observer-Based adaptive neural network controller for uncertain nonlinear systems with unknown control directions subject to input time delay and saturation

Talkhoncheh, Mahdi Khajeh; Shahrokhi, Mohammad

doi:10.1016/j.ins.2017.08.024

Cited by 39 publications

(28 citation statements)

References 46 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…In addition from definition of̃i and their boundedness, it is concluded that̂i are also bounded. Consequently, from (22), (23), and (25), it can be shown that ij and v i are bounded. Since z ij and ij ∈ L ∞ , (21) implies boundedness of x ij .…”

Section: Adaptive Controller Design and Stability Analysismentioning

confidence: 97%

“…Consider the uncertain MIMO arbitrarily switched nonlinear system (1) under Assumptions 1-3 subject to input nonlinearity (2) and unmodeled dynamics. Applying control laws (25), virtual controllers (22), (23), and adaptation laws (24) guarantee the SGUUB of all the closed-loop signals and the tracking errors converge to their corresponding predefined regions.…”

Section: Adaptive Controller Design and Stability Analysismentioning

confidence: 99%

“…The system dynamics may be totally unknown or it can be in the form of parametric uncertainty. In the former case, an intelligent approximator like fuzzy logic systems (FLSs) or neural networks (NNs) can be used to estimate the system unknown dynamics, whereas, for the latter case, some adaptive laws for updating the estimates of unknown parameters can be employed . Likewise, the design of adaptive controller for switched systems with unknown dynamics has been addressed in the works of Li and Tong and Jiang et al, and several adaptive controllers for a class of switched systems with parametric uncertainties have been proposed in related works .…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Adaptive prescribed performance control of switched MIMO uncertain nonlinear systems subject to unmodeled dynamics and input nonlinearities

Malek

Shahrokhi

Vafa

et al. 2018

Intl J Robust & Nonlinear

Self Cite

View full text Add to dashboard Cite

Summary In this paper, the design of an adaptive tracking control for a class of switched uncertain multiple‐input–multiple‐output nonlinear systems in the strict‐feedback form with unmodeled dynamics in the presence of three types of input nonlinearity under arbitrary switching has been addressed. By means of an intelligent approximator like a fuzzy logic system or a neural network, the unknown dynamics are estimated. The unmodeled dynamics have been tackled with a dynamic signal. A universal framework for describing different types of input nonlinearity including saturation, backlash, and dead zone has been utilized. By applying the backstepping approach and the common Lyapunov function method, virtual and actual controllers and the adaptive law for each subsystem have been constructed. Finally, it has been shown that the closed‐loop system is semiglobally uniformly ultimately bounded and the tracking errors converge to their predefined bounds. The effectiveness of the proposed control scheme has been shown through simulation study.

show abstract

Section: Adaptive Controller Design and Stability Analysismentioning

confidence: 97%

Section: Adaptive Controller Design and Stability Analysismentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Adaptive prescribed performance control of switched MIMO uncertain nonlinear systems subject to unmodeled dynamics and input nonlinearities

Malek

Shahrokhi

Vafa

et al. 2018

Intl J Robust & Nonlinear

Self Cite

View full text Add to dashboard Cite

show abstract

“…Definition 3 (see [45,46] Suppose that the part that exceeds the saturation limiter is referred to as ( ); then one has…”

Section: Remarkmentioning

confidence: 99%

Adaptive Fuzzy Synchronization of Fractional-Order Chaotic (Hyperchaotic) Systems with Input Saturation and Unknown Parameters

Liu

Chen

et al. 2017

Complexity

View full text Add to dashboard Cite

We investigate the synchronization problem of fractional-order chaotic systems with input saturation and unknown external disturbance by means of adaptive fuzzy control. An adaptive controller, accompanied with fractional adaptation law, is established, fuzzy logic systems are used to approximate the unknown nonlinear functions, and the fractional Lyapunov stability theorem is used to analyze the stability. This control method can realize the synchronization of two fractional-order chaotic or hyperchaotic systems and the synchronization error tends to zero asymptotically. Finally, we show the effectiveness of the proposed method by two simulation examples.

show abstract

“…[24][25][26] In such methods, the dead-zone nonlinearity is separated into the linear and nonlinear bounded term. Inspired by the aforementioned work, 29 barrier Lyapunov functions (BLFs) are added to the control scheme to constrain outputs. The stability analysis and control design of the time-delay systems have attracted much attention in the past years.…”

Section: Introductionmentioning

confidence: 99%

Prescribed performance adaptive fuzzy dynamic surface control of nonaffine time‐varying delayed systems with unknown control directions and dead‐zone input

Tooranjipour

Vatankhah

Arefi

2019

Adaptive Control & Signal

View full text Add to dashboard Cite

In this paper, an adaptive prescribed performance control method is presented for a class of uncertain strict feedback nonaffine nonlinear systems with the coupling effect of time-varying delays, dead-zone input, and unknown control directions. Owing to the universal approximation property, fuzzy logic systems are used to approximate the uncertain terms in the system. Since there is no systematic approach to determine the required upper bounds of errors in control systems, the prior selection of control parameters to have a satisfactory performance is somehow impossible. Therefore, the prescribed performance technique as a solution is applied in this study to bring satisfactory performance indices to the system such as overshoot and steady state performance within a predetermined bound. Dynamic surface control strategy is also introduced to the proposed control scheme to address the "explosion of complexity" behavior existing in conventional backstepping methods. To ease the control design, the mean-value theorem is utilized to transform the nonaffine system into the affine one. Moreover, with the help of this theorem, the unknown dead-zone nonlinearity is separated into the linear and nonlinear disturbance-like bounded term. The proposed method relaxes a prior knowledge of control direction by employing Nussbaum-type functions, and the effect of time-varying delays are compensated by constructing the proper Lyapunov-Krasovskii functions. The proposed controller guarantees that all the closed-loop signals are semiglobally uniformly ultimately bounded and the error evolves within the decaying prescribed bounds. In the end, in order to demonstrate the superiority of this method, simulation examples are given. KEYWORDS adaptive fuzzy control, dead-zone nonlinearity, dynamic surface control, nonaffine systems, prescribed performance, time-varying delays 1134

show abstract

Observer-Based adaptive neural network controller for uncertain nonlinear systems with unknown control directions subject to input time delay and saturation

Cited by 39 publications

References 46 publications

Adaptive prescribed performance control of switched MIMO uncertain nonlinear systems subject to unmodeled dynamics and input nonlinearities

Adaptive prescribed performance control of switched MIMO uncertain nonlinear systems subject to unmodeled dynamics and input nonlinearities

Adaptive Fuzzy Synchronization of Fractional-Order Chaotic (Hyperchaotic) Systems with Input Saturation and Unknown Parameters

Prescribed performance adaptive fuzzy dynamic surface control of nonaffine time‐varying delayed systems with unknown control directions and dead‐zone input

Contact Info

Product

Resources

About