Adaptive fuzzy control for full states constrained systems with nonstrict-feedback form and unknown nonlinear dead zone

Wu, Jian; Su, Benyue; Li, Jing; Zhang, Xu; Li, Xiaobo; Chen, Weisheng

doi:10.1016/j.ins.2016.10.016

Cited by 73 publications

(30 citation statements)

References 49 publications

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“…22 Another method is using special continuous indicator functions in which the linear parameters of dead-zone are approximated online. [24][25][26] In such methods, the dead-zone nonlinearity is separated into the linear and nonlinear bounded term. Recently, due to using UFAs, the dead-zone parameters are completely approximated, and hence, the requirements on the dead-zone parameters are relaxed.…”

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

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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

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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

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“…For example, a BLF‐based backstepping method has been presented to address the problem of control design for nonlinear strict‐feedback systems with partial state constraints and full state constraints and for nonlinear pure‐feedback systems with full state constraint control . In addition, approximation‐based adaptive control schemes combining radial basis function (RBF) neural networks or fuzzy logic systems (FLSs) have also been studied for the control of nonlinear systems with unknown nonlinearities subject to output and full state constraints; in these schemes, the RBF neural networks and FLSs are utilized to approximate the unknown system functions due to the strong approximation capabilities of smooth nonlinear functions to any desired accuracy over a compact set . For physical systems, the presented control schemes are often needed to ensure that certain prescribed performance requirements are satisfied, such as overshoot, convergence rate, or steady‐state error.…”

Section: Introductionmentioning

confidence: 99%

Prescribed performance adaptive neural output feedback dynamic surface control for a class of strict‐feedback uncertain nonlinear systems with full state constraints and unmodeled dynamics

Zhang

Sun

2019

Intl J Robust & Nonlinear

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Summary This paper studies the output feedback tracking control problem for a class of strict‐feedback uncertain nonlinear systems with full state constraints and unmodeled dynamics using a prescribed performance adaptive neural dynamic surface control design approach. A nonlinear mapping technique is employed to address the state constraints. Radial basis function neural networks are utilized to approximate the unknown nonlinear functions. The unmodeled dynamics is addressed by introducing an available dynamic signal. Subsequently, we construct the controller and parameter adaptive laws using a backstepping technique. Based on Lyapunov stability theory, it is shown that all signals in the closed‐loop system are semiglobally uniformly ultimately bounded and that the tracking error always remains within the prescribed performance bound. Simulation results are presented to demonstrate the effectiveness of the proposed control scheme.

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“…The nonlinear characteristics of backlash‐like hysteresis could seriously affect tracking performance, and it may cause a severe effect on the whole system . Several effective control design schemes have been studied for such systems with nonlinear input . To cope with hysteresis nonlinearity, a technique of robust adaptive backstepping control scheme was proposed in the work of Zhou et al, which is different from some existing control methods; the uncertain parameters within known intervals are not required to be obtained during backstepping controller design.…”

Section: Introductionmentioning

confidence: 99%

“…32 Several effective control design schemes have been studied for such systems with nonlinear input. [33][34][35][36][37][38][39] To cope with hysteresis nonlinearity, a technique of robust adaptive backstepping control scheme was proposed in the work of Zhou et al, 36 which is different from some existing control methods; the uncertain parameters within known intervals are not required to be obtained during backstepping controller design. In the work of Su et al, 40 the hysteresis model was established on the basis of the differential equation, and then, a robust adaptive control approach was studied by combining the differential equation with adaptive techniques.…”

Section: Introductionmentioning

confidence: 99%

Adaptive neural tracking control for nonstrict‐feedback nonlinear systems with unknown backlash‐like hysteresis and unknown control directions

Xin-jun

Yin

et al. 2018

Intl J Robust & Nonlinear

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Summary In this paper, a neural network–based adaptive tracking control problem is investigated for a class of nonstrict‐feedback nonlinear systems in the presence of unknown backlash‐like hysteresis nonlinearity, unmodeled dynamics, and unknown control directions. A state feedback controller is developed for the considered system by applying the adaptive backstepping technique and neural networks. The design difficulties exhibited in this paper due to unmodeled dynamics, unknown control directions, and nonstrict‐feedback form are handled by resorting to a dynamic signal, a Nussbaum function, and the variable separation approach, respectively. It is shown that the designed adaptive controller can guarantee that all the signals remain bounded and that the desired signal can be tracked with a small domain of the origin. A numerical example and an example of a real plant for a one‐link manipulator are provided to show the feasibility of the newly designed controller scheme.

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Adaptive fuzzy control for full states constrained systems with nonstrict-feedback form and unknown nonlinear dead zone

Cited by 73 publications

References 49 publications

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

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

Prescribed performance adaptive neural output feedback dynamic surface control for a class of strict‐feedback uncertain nonlinear systems with full state constraints and unmodeled dynamics

Adaptive neural tracking control for nonstrict‐feedback nonlinear systems with unknown backlash‐like hysteresis and unknown control directions

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