Fuzzy control of nonlinear electromagnetic suspension systems

Su, Xiaojie; Yang, Xiaozhan; Shi, Peng; Wu, Ligang

doi:10.1016/j.mechatronics.2013.08.002

Cited by 80 publications

(44 citation statements)

References 28 publications

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“…In our future work, we aim to use a class of fuzzy models to approximate the spacecraft attitude dynamics (see [19][20][21][22][23]), which can transfer the nonlinear system into a set of linear systems.…”

Section: Discussionmentioning

confidence: 99%

Decentralized robust attitude tracking control for spacecraft networks under unknown inertia matrices

Zhang

2015

Neurocomputing

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Section: Discussionmentioning

confidence: 99%

Decentralized robust attitude tracking control for spacecraft networks under unknown inertia matrices

Zhang

2015

Neurocomputing

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“…With respect to actuators, in [1], a frequency dependent weighting filter is integrated with a ∞ controller to come up with a linear electromagnetic actuator. This kind of actuator has been researched extensively as it has the bandwidth of a full electric system [2,3]. However, the force supplied is constricted and limited for heavyduty vehicles.…”

Section: Introductionmentioning

confidence: 99%

T-S Fuzzy Model Based H-Infinity Control for 7-DoF Automobile Electrohydraulic Active Suspension System

Zhou

Zhao

et al. 2017

Journal of Control Science and Engineering

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This paper presents a double loop controller for a 7-DoF automobile electrohydraulic active suspension via T-S fuzzy modelling technique. The outer loop controller employs a modified -infinity feedback control based on a T-S fuzzy model to provide the actuation force needed to ensure better riding comfort and handling stability. The resulting optimizing problem is transformed into a linear matrix inequalities solution issue associated with stability analysis, suspension stroke limit, and force constraints. Integrating these via parallel distributed compensation method, the feedback gains are derived to render the suspension performance dependent on the perturbation size and improve the efficiency of active suspensions. Adaptive Robust Control (ARC) is then adopted in the inner loop design to deal with uncertain nonlinearities and improve tracking accuracy. The validity of improvements attained from this controller is demonstrated by comparing with conventional Backstepping control and a passive suspension on a 7-DoF simulation example. It is shown that the T-S fuzzy model based controller can achieve favourable suspension performance and energy conservation under both mild and malevolent road inputs.

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“…The simulation results for the sampled-data depth control of AUV convincingly illustrated the effectiveness of the developed techniques. Xiaojie Su, et al [8] presented a T-S model-based fuzzy controller design approach for electromagnetic suspension systems. The T-S fuzzy model was firstly applied to represent the nonlinear electromagnetic suspension systems.…”

Section: Introductionmentioning

confidence: 99%

“…Numerical simulation on an electromagnetic suspension system was performed to validate the effectiveness of the proposed approach. From [5][6][7][8], we can see that fuzzy control is rarely used alone, and is usually used in conjunction with other control methods.…”

Section: Introductionmentioning

confidence: 99%

A Simple Fuzzy PI Control of Dual-Motor Driving Servo System

Zhao

Wang²

2017

MATEC Web Conf.

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Abstract. Aiming at the control problem of dual-motor driving servo system, in order to avoid the complicated numerical calculation of complicated control algorithm, we presented a simple fuzzy PI controller for the first time. Firstly, we explained system control principle. In view of the shortcomings of current-error negative feedback, we used speed-error negative feedback synchronous driving control strategy. Then we theoretically analyzed dual-motor synchronous driving system in detail. We proposed the conditions of dual-motor driving servo system synchronous operation for step signal and ramp signal, respectively. Finally, we presented a simple fuzzy PI controller, by combining fuzzy controller with PI controller. We analyzed the fuzzy PI control system and found it was stable. We considered two cases in simulation tests comparing fuzzy PI control with PI control. Simulation results show that fuzzy PI control has better adaptability than conventional PI control, validating the effectiveness and efficiency of the proposed control strategy.

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Fuzzy control of nonlinear electromagnetic suspension systems

Cited by 80 publications

References 28 publications

Decentralized robust attitude tracking control for spacecraft networks under unknown inertia matrices

Decentralized robust attitude tracking control for spacecraft networks under unknown inertia matrices

T-S Fuzzy Model Based H-Infinity Control for 7-DoF Automobile Electrohydraulic Active Suspension System

A Simple Fuzzy PI Control of Dual-Motor Driving Servo System

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