Robust adaptive backstepping control for a class of constrained non-affine nonlinear systems via self-organizing Hermite-polynomial-based neural network disturbance observer

Zhang, Qiang; Wang, Cui

doi:10.1177/1687814017702811

Cited by 7 publications

(5 citation statements)

References 32 publications

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“…Fig. (21) illustrates that trajectory tracking error is minimized, also the Lyapunov function is always positive and its derivative is always negative, which justifies that the proposed method guarantees the stability of the CSTR system.…”

Section: B Benchmark System II 1) Nominal Casementioning

confidence: 56%

A Novel Adaptive LSSVR-Based Inverse Optimal Controller With Integrator for Nonlinear Non-Affine Systems

Sanci,

Uçak,

Günel

2023

IEEE Access

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In this study, a novel inverse optimal controller based on NARMA-L2 modelling technique and online least squares support vector regression (LSSVR) method has been proposed for nonlinear nonaffine systems. Firstly, the nonlinear autoregressive with exogenous inputs (NARX) model of the system is obtained using online LSSVR method, then this model is decomposed into NARMA-L2 submodels. Hence, the non-affine system model is converted to a nonlinear affine system model. The obtained NARMA-L2 submodels are used in computing the inverse optimal control law. Furthermore, the parameters of the inverse optimal controller have also been optimized online using the Levenberg-Marquadt algorithm. The performance of the proposed LSSVR based inverse optimal controller using NARMA-L2 model has been evaluated by simulations carried out on two benchmark systems, and the results show that the LSSVR based NARMA-L2 model and inverse optimal controller attain good modelling and control performances.

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Section: B Benchmark System II 1) Nominal Casementioning

confidence: 56%

A Novel Adaptive LSSVR-Based Inverse Optimal Controller With Integrator for Nonlinear Non-Affine Systems

Sanci,

Uçak,

Günel

2023

IEEE Access

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“…To utilize the controller u sd and u sq described in equations (24) and (29), respectively, the upper bound of should be known, which is unlikely to accomplish in reality. Hence, an adaptive item^is added to estimate on-line.…”

Section: Proposed Adaptive Controlmentioning

confidence: 99%

“…Hence, the system errors shown in equation (16) can converge to zero in a finite time. For elimination of the chattering problem in designed controller, signum function sgn in equations (24) and (29) are replaced by saturation function sat. The ultimate MTPA controller based on adaptive SMC backstepping is shown in equation 36with NDO in equation (10) and adaptive law in equation (34)…”

Section: Proposed Adaptive Controlmentioning

confidence: 99%

“…So some improved approaches combining of BC and other design methods are put forward. 24,25 SMC is an approach with the merits of simpleness, robustness, and reliability, and is particularly suitable for controlling the uncertain system. For an uncertain system with external disturbances, SMC can guarantee the robustness of the whole system.…”

Section: Introductionmentioning

confidence: 99%

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Adaptive sliding mode backstepping control - based maximum torque per ampere control of permanent magnet-assisted synchronous reluctance motor via nonlinear disturbance observer

Zheng

et al. 2018

Advances in Mechanical Engineering

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Combined with two approaches of sliding mode control and backstepping control, an adaptive sliding mode-based backstepping control scenario on the basis of nonlinear disturbance observer is proposed to complete maximum torque per ampere control for permanent magnet-assisted synchronous reluctance motor. The constraint relation of permanent magnet-assisted synchronous reluctance motor under maximum torque per ampere control is built, and the design of the controller is elaborated in detail. The uncertainties of modeling errors considering unmatched items are estimated through a presented nonlinear disturbance observer. The adaptive law reflecting the modeling error of the system is constructed. Globally asymptotic stability and convergence of the tracking error for the system are validated through Lyapunov stability criterion. Simulation and experimental results illustrate that external disturbances and uncertainties are observed correctly by nonlinear disturbance observer; the close-loop system controlled by the proposed controller can track the references rapidly and precisely, and the designed controller has a good robust ability.

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“…Controlling the state trajectories of chaotic systems have received good attention in the control literature [29][30][31][32][33]. We use adaptive backstepping control [34][35][36][37][38] for the global chaos control of the new non-equilibrium hyperjerk system.…”

Section: Introductionmentioning

confidence: 99%

Archives of Control Sciences

Vaidyanathan

Jafar

Pham

et al. 2018

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A novel 4-D chaotic hyperjerk system with four quadratic nonlinearities is presented in this work. It is interesting that the hyperjerk system has no equilibrium. A chaotic attractor is said to be a hidden attractor when its basin of attraction has no intersection with small neighborhoods of equilibrium points of the system. Thus, our new non-equilibrium hyperjerk system possesses a hidden attractor. Chaos in the system has been observed in phase portraits and verified by positive Lyapunov exponents. Adaptive backstepping controller is designed for the global chaos control of the non-equilibrium hyperjerk system with a hidden attractor. An electronic circuit for realizing the non-equilibrium hyperjerk system is also introduced, which validates the theoretical chaotic model of the hyperjerk system with a hidden chaotic attractor.

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Robust adaptive backstepping control for a class of constrained non-affine nonlinear systems via self-organizing Hermite-polynomial-based neural network disturbance observer

Cited by 7 publications

References 32 publications

A Novel Adaptive LSSVR-Based Inverse Optimal Controller With Integrator for Nonlinear Non-Affine Systems

A Novel Adaptive LSSVR-Based Inverse Optimal Controller With Integrator for Nonlinear Non-Affine Systems

Adaptive sliding mode backstepping control - based maximum torque per ampere control of permanent magnet-assisted synchronous reluctance motor via nonlinear disturbance observer

Archives of Control Sciences

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