Robust fuzzy neural network controller with nonlinear disturbance observer for two-axis motion control system

Lin, Faa Jeng; Chou, Po-Huan; Kung, Ying‐Shieh

doi:10.1049/iet-cta:20070108

Cited by 38 publications

(31 citation statements)

References 19 publications

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“…where 1 , 2 , and 3 are positive real constants. The function Proj (4), if the condition | | < is satisfied, exponentially decays to zero, and asymptotically decays to zero using the control law as (10), (15), (20), and (22). The state variables of the system are bounded meanwhile.…”

Section: Adaptive Sliding Mode Controller Based Main Systemmentioning

confidence: 99%

See 1 more Smart Citation

Adaptive Sliding Mode Robust Control for Virtual Compound-Axis Servo System

Ren

Liu

Chang

et al. 2013

Mathematical Problems in Engineering

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A structure mode of virtual compound-axis servo system is proposed to improve the tracking accuracy of the ordinary optoelectric tracking platform. It is based on the structure and principles of compound-axis servo system. A hybrid position control scheme combining the PD controller and feed-forward controller is used in subsystem to track the tracking error of the main system. This paper analyzes the influences of the equivalent disturbance in main system and proposes an adaptive sliding mode robust control method based on the improved disturbance observer. The sliding mode technique helps this disturbance observer to deal with the uncompensated disturbance in high frequency by making use of the rapid switching control value, which is based on the subtle error of disturbance estimation. Besides, the high-frequency chattering is alleviated effectively in this proposal. The effectiveness of the proposal is confirmed by experiments on optoelectric tracking platform.

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Section: Adaptive Sliding Mode Controller Based Main Systemmentioning

confidence: 99%

“…High-frequency components of the disturbances such as sudden changes in external forces and Coulomb friction can degrade the control effect of a DOB based tracking control. Therefore, some researchers have tried to design the fuzzy disturbance observer [8,9], nonlinear disturbance observer [10,11] and extended state observer [12,13].…”

Section: Introductionmentioning

confidence: 99%

Adaptive Sliding Mode Robust Control for Virtual Compound-Axis Servo System

Ren

Liu

Chang

et al. 2013

Mathematical Problems in Engineering

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“…One is the disturbance observer (DOB) technique originally presented by Ohnishi [18]. Following this direction, many DOB-based control methods have been reported in different applications, e.g., robotic systems [19], hard disk drive systems [28], general motion control systems [20][21][22][23][24], inverted pendulum systems [25], PMSM systems [26,2,27,7], etc. Among these results, different kinds of DOB have been developed, including linear DOBs [26,2,22,28], fuzzy DOBs [25], neural network based DOBs [27], and other nonlinear DOBs [19][20][21]23,7,24], etc.…”

Section: Introductionmentioning

confidence: 99%

Disturbance rejection control method for permanent magnet synchronous motor speed-regulation system

Xia

Zhou

2012

Mechatronics

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“…A fuzzy logic system is a universal approximator which, with increasing number of IF-Then rules, can approximate any nonlinearities with arbitrary precision [12]. Based on its capability, the fuzzy logic system is vastly adopted for nonlinear systems identification and control [13], and various adaptive fuzzy control approaches based on the feedback linearization have been introduced to controll nonlinear systems [14][15][16][17][18][19][20][21][22]. Generally, the adaptive fuzzy control approaches can have nice performance.…”

Section: Introductionmentioning

confidence: 99%

Robust adaptive fuzzy backstepping output feedback tracking control for nonlinear system with dynamic uncertainties

Tong

2010

Sci. China Inf. Sci.

134

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In this paper, an adaptive fuzzy output feedback control approach based on backstepping design is proposed for a class of SISO strict feedback nonlinear systems with unmeasured states, nonlinear uncertainties, unmodeled dynamics, and dynamical disturbances. Fuzzy logic systems are employed to approximate the nonlinear uncertainties, and an adaptive fuzzy state observer is designed for the states estimation. By combining backstepping technique with the fuzzy adaptive control approach, a stable adaptive fuzzy output feedback robust control is constructed recursively, in which nonlinear damping terms and a dynamical signal are introduced to counteract the nonlinear uncertainties and dominate the dynamic disturbances, respectively. It is proved that the proposed adaptive fuzzy control approach guarantees that all the signals of the closed-loop system are semi-globally uniformly bounded, and the tracking error converges to a small neighborhood of the origin. Simulation studies are included to illustrate the effectiveness of the proposed approach. CitationTong S C, Li Y M. Robust adaptive fuzzy backstepping output feedback tracking control for nonlinear system with dynamic uncertainties.

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Robust fuzzy neural network controller with nonlinear disturbance observer for two-axis motion control system

Cited by 38 publications

References 19 publications

Adaptive Sliding Mode Robust Control for Virtual Compound-Axis Servo System

Adaptive Sliding Mode Robust Control for Virtual Compound-Axis Servo System

Disturbance rejection control method for permanent magnet synchronous motor speed-regulation system

Robust adaptive fuzzy backstepping output feedback tracking control for nonlinear system with dynamic uncertainties

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