Adaptive neural control for switched nonlinear systems with unmodeled dynamics and unknown output hysteresis

Lyu, Ziliang; Liu, Zhi; Zhang, Yun; Chen, C.L. Philip

doi:10.1016/j.neucom.2019.02.057

Cited by 20 publications

(9 citation statements)

References 43 publications

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“…Step 3: According to the u k (t), e k (t) and ϕ k (t) obtained in Step 2, the control input sequence u k+1 (t) should be calculated according to equation (11). Then the variables would be renewed as the u k+1 (t) inputted the system.…”

Section: Model-free Control Methods Synnthesismentioning

confidence: 99%

“…In AMB control system, CFCS is necessary. There are many research fruits in the field of unmolded dynamics and actuator faults and unknown output of the control system [9]- [11], iterative feedback tuning [12], [13]. Furthermore, besides conventional PID controller, 2-degree of freedom (DOF) controller, nonlinear smooth feedback control method and linear parameter varying controller were studied for AMB [14]- [16].…”

Section: Introductionmentioning

confidence: 99%

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A Model-Free Control Method for Synchronous Vibration of Active Magnetic Bearing Rotor System

Zheng

Zhou

et al. 2019

IEEE Access

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The unbalanced force on the active magnetic bearing (AMB) rotor system is the main reason of system vibrations, which always have periodic repetitive characteristics. However, the closed-loop feedback control system (CFCS) is difficult to achieve effective control of these repetitive problems. In this paper, we firstly analyzed the synchronous vibration by taking AMB rotor mass imbalance as an example. Then, we proposed a model-free control (MFC) method based on the Newton-type ILC algorithm, and the key of this MFC is to use a partial derivative (P-D) of the output with respect to the input. The simplicity of this algorithm lies in that and the P-D is calculated by only using the input and output (I/O) data of the system and then used to adjust the ILC gain. Subsequently, we proposed a parallel plug-in control scheme based on existing AMB control system to suppress synchronous vibration. Finally, we carried out the simulation and experiment to research the control method mentioned in this paper. The results show that the MFC has a good control effect on AMB synchronous vibration. Notably, this MFC for synchronous vibration has the advantages of being without system model, simple design and good portability, and can provide theoretical and experimental basis for the application of AMB in high precision and high speed fields.INDEX TERMS Active magnetic bearing, synchronous vibration, model-free, iterative learning control parallel control scheme.

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Section: Model-free Control Methods Synnthesismentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

A Model-Free Control Method for Synchronous Vibration of Active Magnetic Bearing Rotor System

Zheng

Zhou

et al. 2019

IEEE Access

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“…34 Compared with the above models, the modified Bouc-Wen hysteresis model was put forward by, 35 which can preferably solve the more general hysteresis problem. Based on the modified Bouc-Wen hysteresis model, for switched systems or large-scale systems, many interesting research results about unknown hysteresis have been obtained, such as input hysteresis, 36,37 backlash-like hysteresis, 38 output hysteresis 39,40 . However, according to our current knowledge, there is no research on large-scale switched nonlinear systems with output hysteresis.…”

Section: Introductionmentioning

confidence: 99%

“…The control strategy proposed in Reference 36 is only suitable for controlling large‐scale systems with unknown actuator hysteresis, rather than switched systems with output hysteresis. Even though the control results of switched systems with output hysteresis were reported in References 39 and 40, the controlled objects do not include large‐scale systems. The authors of References 23 and 24 considered the tracking control problem of large‐scale switched systems, but the problem of output hysteresis cannot be solved. It seems to us that little has been known about the research of large‐scale systems, switched systems, asymmetric input saturation, output hysteresis and MTN technology appearing in the same framework.…”

Section: Introductionmentioning

confidence: 99%

Tracking control for large‐scale switched nonlinear systems subject to asymmetric input saturation and output hysteresis: A new adaptive network‐based approach

Han

et al. 2022

Intl J Robust & Nonlinear

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For large‐scale switched nonlinear systems subject to asymmetric input saturation and output hysteresis, an adaptive control strategy is put forward by using a novel neural network, that is, multi‐dimensional Taylor network (MTN), which can effectively cope with the output tracking problem of this system. Firstly, asymmetric input saturation is expressed as the combination of a linear function and a bounded error function. Then, the modified Bouc‐Wen hysteresis model is employed to solve the nonlinear problem caused by output hysteresis. Afterwards, based on the approximation ability of MTN, a novel adaptive decentralized control method is designed by combining Lyapunov stability theory with adaptive backstepping technology, which realizes the stability and boundedness of the controlled systems. It should be noted that the asymmetric input saturation, the output hysteresis, large‐scale nonlinear systems and switched nonlinear systems appear in the same framework for the first time. Finally, a practical example and a numerical example are given to verify the availability of the proposed control strategy.

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“…Li and He (2019) presented the method of adaptive finite-time tracking control for strict-feedback nonlinear continuous-time systems subject to full-state constraints with dead-zone. Meanwhile, the effect of unmodeled dynamics on the performance of nonlinear systems was considered in Wang et al (2018); Xia and Zhang (2019); and Lyu et al (2019). Unmodeled dynamics exist in almost all physical systems because it cannot describe the exact mathematical model.…”

Section: Introductionmentioning

confidence: 99%

Adaptive control based on Barrier Lyapunov function for a class of full-state constrained stochastic nonlinear systems with dead-zone and unmodeled dynamics

Shen

Xin-jun

Yin

2021

Transactions of the Institute of Measurement and Control

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This paper investigates the problem of adaptive control based on Barrier Lyapunov function for a class of full-state constrained stochastic nonlinear systems with dead-zone and unmodeled dynamics. To stabilize such a system, a dynamic signal is introduced to dominate unmodeled dynamics and an assistant signal is constructed to compensate for the effect of the dead zone. Dynamic surface control is used to solve the “complexity explosion” problem in traditional backstepping design. Two cases of symmetric and asymmetric Barrier Lyapunov functions are discussed respectively in this paper. The proposed Barrier Lyapunov function based on backstepping method can ensure that the output tracking error converges in the small neighborhood of the origin. This control scheme can ensure that semi-globally uniformly ultimately boundedness of all signals in the closed-loop system. Two simulation cases are proposed to verify the effectiveness of the theoretical method.

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Adaptive neural control for switched nonlinear systems with unmodeled dynamics and unknown output hysteresis

Cited by 20 publications

References 43 publications

A Model-Free Control Method for Synchronous Vibration of Active Magnetic Bearing Rotor System

A Model-Free Control Method for Synchronous Vibration of Active Magnetic Bearing Rotor System

Tracking control for large‐scale switched nonlinear systems subject to asymmetric input saturation and output hysteresis: A new adaptive network‐based approach

Adaptive control based on Barrier Lyapunov function for a class of full-state constrained stochastic nonlinear systems with dead-zone and unmodeled dynamics

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