Adaptive neural dynamic surface control for a class of uncertain nonlinear systems with disturbances

Cui, Yang; Zhang, Huaguang; Wang, Yingchun; Zhang, Zhao

doi:10.1016/j.neucom.2015.03.004

Cited by 21 publications

(15 citation statements)

References 30 publications

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“…It is noted that the observer is applied to evaluate the results of the proposed controller. The parameters [k 1 , k 2 ] are chosen as [1, 1.5] for random regular bump and [1,5] for random step wave bump.…”

Section: Control Results Of the Hac-ifvmentioning

confidence: 99%

“…Besides of uncertain nonlinear system, the problem of unknown input nonlinearity such as dead-zone or backlash-like hysteresis was also studied through the hybrid adaptive control [4]. It has been also shown that the neural works can be designed for a good performance of the hybrid adaptive control to deal with the uncertain system [5]. A hybrid adaptive controller possessing the robustness against input and parameter uncertainties was studied using the sliding mode controller associated with the fuzzy model [6,7].…”

Section: Introductionmentioning

confidence: 99%

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Robust Adaptive Controls of a Vehicle Seat Suspension System

Phu¹,

Huy²,

Choi³

2018

Adaptive Robust Control Systems

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This work proposes two novel adaptive fuzzy controllers and applies them to vibration control of a vehicle seat suspension system subjected to severe road profiles. The first adaptive controller is designed by considering prescribed performance of the sliding surface and combined with adaptation laws so that robust stability is guaranteed in the presence of external disturbances. As for the second adaptive controller, both the Hinfinity controller and sliding mode controller are combined using inversely fuzzified values of the fuzzy model. In order to evaluate control performances of the proposed two adaptive controllers, a semi-active vehicle suspension system installed with a magneto-rheological (MR) damper is adopted. After determining control gains, two controllers are applied to the system and vibration control performances such as displacement at the driver's position are evaluated and presented in time domain. In this work, to demonstrate the control robustness two severe road profiles of regular bump and random step wave are imposed as external disturbances. It is shown that both adaptive controllers can enhance ride comfort of the driver by reducing the displacement and acceleration at the seat position. This excellent performance is achieved from each benefit of each adaptive controller; accurate tracking performance of the first controller and fast convergence time of the second controller.

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Section: Control Results Of the Hac-ifvmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Robust Adaptive Controls of a Vehicle Seat Suspension System

Phu¹,

Huy²,

Choi³

2018

Adaptive Robust Control Systems

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“…Disturbance observers are designed as equations (33) and (66). The adaptive prescribed performance control laws are designed as equations (21), (29), (46), (56), and (63). Then the closed-loop system is globally stable.…”

Section: Controller Designmentioning

confidence: 99%

Robust adaptive tracking control for unmanned helicopter with constraints

Liu

2017

International Journal of Advanced Robotic Systems

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In this article, a prescribed performance-based adaptive neural network control scheme is proposed for an uncertain small-scale unmanned helicopter system subject to input saturations and output constraints. The radial basis function neural networks are employed to approximate system uncertainties. A nonlinear disturbance observer is developed to tackle input saturation. Meanwhile, the prescribed performance function is adopted to deal with output constraint. The closed-loop system stability is rigorously proved using Lyapunov synthesis. Finally, simulation results for unmanned helicopter system are presented to demonstrate the effectiveness of developed tracking control scheme using disturbance observer and radial basis function neural network.

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“…In order to overcome the problem "explosion of complexity", Swaroop et al [17] proposed a dynamic surface control (DSC) technique by introducing a first-order filtering. So far many researchers have developed this method, such as [18][19][20][21][22][23]. The work [20] investigated decentralized dynamic surface control for a class of interconnected nonlinear systems.…”

Section: Introductionmentioning

confidence: 99%

Modeling and Extended State Observer Based Dynamic Surface Control for Cold Rolling Mill System

Zhang

2016

Mathematical Problems in Engineering

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The modeling and control problems are investigated for cold rolling mill system. Firstly, we establish a monitor automatic gauge control (MAGC) model for a practical cold rolling mill system. The new model is with mismatched uncertainties. Then, an extended state observer (ESO) is developed to estimate uncertainties. In the general high-order systems, the ESO is also used to estimate states. By dynamic surface control method, we design the controller to guarantee stabilization of the cold rolling mill system. Furthermore, we extend proposed method to general high-order systems, in which we analyze the difference from cold rolling mill system. Finally, simulation results for MAGC system are presented to demonstrate the effectiveness of the proposed control strategy.

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Adaptive neural dynamic surface control for a class of uncertain nonlinear systems with disturbances

Cited by 21 publications

References 30 publications

Robust Adaptive Controls of a Vehicle Seat Suspension System

Robust Adaptive Controls of a Vehicle Seat Suspension System

Robust adaptive tracking control for unmanned helicopter with constraints

Modeling and Extended State Observer Based Dynamic Surface Control for Cold Rolling Mill System

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