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RISS 인기검색어
- 검색키워드
- 저자 : Dao Thanh Liem (검색결과 6 건)
- 무료
- 기관 내 무료
- 유료
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Force control of Electro-Hydraulics System using Adaptive PID sliding mode controller
Dao Thanh Liem(도황팅),K.K.Ahn(안경관) 유공압건설기계학회 2016 유공압건설기계학회 학술대회논문집 Vol.2016 No.6
In this study, a sliding mode controller with PID tuning method (PIDSMC) is proposed to control an EHA system. The simple test rig using the EHA and MR fluid damper was setup for the investigation. In the PIDSMC, the PID controller is employed to approximate the sliding-mode equivalent control along the direction that makes the sliding-mode asymptotically stable. Due to the system nonlinearity of the EHA system the PID control gain parameters are computed according to the adaptive law. The proposed controller was evaluated with the conventional PID controller in controlling the damping force of the EHA system with respect to the different desired force and supply current levels applied to the MR damper. Experimental results are carried out to investigate the effectiveness of the proposed controller.
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Adaptive Grey Predictor-based Controller for Force Control of EHA System
Dao Thanh Liem,Bui Ngoc Minh Truong,Kyoung Kwan Ahn 제어로봇시스템학회 2016 제어로봇시스템학회 국제학술대회 논문집 Vol.2016 No.10
This study aims to develop an effective control approach for force control of a typical EHA system. This control scheme is considered as an advanced combination of a feedforward neural network – based PID (FNNPID) controller and a fuzzy grey predictor (FGP), shortened as feedforward neural network fuzzy grey predictor (FNNFGP). Here, the FNNPID controller is used to drive the system to desired targets. Meanwhile, the FGP predictor with self-tuning ability of the predictor step size takes part in, first, estimating the system output in the near future to optimize the controller parameters in advance and, second, creating a compensating control signal accordingly to the system perturbations and, consequently, improving the control performance. Real-time experiments have been carried out to investigate the effectiveness of the proposed control approach.
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A Smart Grey Predictor based Adaptive Fuzzy Neural Controller for Electro-Hydraulic Actuator System
Dao Thanh Liem,Kyoung Kwan Ahn(안경관) 유공압건설기계학회 2016 유공압건설기계학회 학술대회논문집 Vol.2016 No.11
Recently, electro-hydraulic actuators (EHAs) have shown significant advantages over conventionally valve-controlled actuators. EHAs have a wide range of applications where force or position control with high accuracy is exceedingly necessary. Besides the benefits, however, EHA is a highly complex nonlinear system which causes challenges for both modeling and control tasks. This paper aims to develop an effective control approach for force control of a typical EHA system. This control scheme is considered as an advanced combination of a feedforward neural network - based PID controller and a fuzzy grey predictor, shortened as feedforward neural network fuzzy grey predictor. Here, the FNNPID controller is used to drive the system to desired targets. Additionally, a learning mechanism with robust checking conditions is implemented into the FNNPID in order to optimize online its parameters with respect to the control error minimization. Meanwhile, the FGP predictor with self-tuning ability of the predictor step size takes part in, first, estimating the system output in the near future to optimize the controller parameters in advance and, second, creating a compensating control signal accordingly to the system perturbations and, consequently, improving the control performance. Real-time experiments have been carried out to investigate the effectiveness of the proposed control approach.
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Hysteresis Modeling of Magneto-Rheological Damper using Self-Tuning Lyapunov-based Fuzzy Approach
Liem, Dao Thanh,Truong, Dinh Quang,Ahn, Kyoung Kwan Korean Society for Precision Engineering 2015 International Journal of Precision Engineering and Vol.16 No.1
Magneto-rheological (MR) fluid damper is a semi-active control device that has recently received more attention because they offer the adaptability of active control devices without requiring the associated large power sources. But inherent nonlinear nature of the MR fluid damper is one of the challenging aspects for utilizing this device to achieve the high performance. So development of an accurate MR fluid damper model is necessary to take the advantages from its unique characteristics. The focus of this paper is to develop an alternative method for modeling a MR fluid damper by using a so-called self-tuning Lyapunov-based fuzzy model (STLFM). Here, the model is constructed in the form of a center average fuzzy interference system, of which the fuzzy rules are designed based on the Lyapunov stability condition. In addition, in order to optimize the STLFM, the back propagation learning rules are used to adjust the fuzzy weighting net. Firstly, experimental data of a damping system using this damper is used to optimize the model. Next, the optimized model is used to estimate online the damping performance in the real-time conditions. The modeling results prove convincingly that the developed model could represent satisfactorily the behavior of the MR fluid damper.
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Grey Prediction Based Adaptive Sliding Mode Control for Electro-Hydraulic Actuator System
Dao Thanh Liem,Kyoung Kwan Ahn 제어로봇시스템학회 2015 제어로봇시스템학회 국제학술대회 논문집 Vol.2015 No.10
In this study, an adaptive sliding mode controller with PID tuning method based on the grey predictor (SMCGP) is proposed to control an EHA system. The simple test rig using the EHA and MR fluid damper was setup for the investigation. In the SMCGP, the PID controller is employed to approximate the sliding-mode equivalent control along the direction that makes the sliding-mode asymptotically stable. Due to the system nonlinearity of the EHA system the PID control gain parameters are computed according to the adaptive law. Furthermore, the fuzzy grey predictor (FGP) takes part in estimating the system output in the near future to optimize the controller parameters in advance. The proposed controller was evaluated with the conventional PID controller in controlling the damping force of the EHA system with respect to the different desired force and supply current levels applied to the MR damper. Experimental results are carried out to investigate the effectiveness of the proposed controller.
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Hysteresis Modeling of Magneto-Rheological Damper using Self-Tuning Lyapunov-based Fuzzy Approach
Dao Thanh Liem,DINH QUANG TRUONG,안경관 한국정밀공학회 2015 International Journal of Precision Engineering and Vol. No.
Magneto-rheological (MR) fluid damper is a semi-active control device that has recently received more attention because they offerthe adaptability of active control devices without requiring the associated large power sources. But inherent nonlinear nature of theMR fluid damper is one of the challenging aspects for utilizing this device to achieve the high performance. So development of anaccurate MR fluid damper model is necessary to take the advantages from its unique characteristics. The focus of this paper is todevelop an alternative method for modeling a MR fluid damper by using a so-called self-tuning Lyapunov-based fuzzy model(STLFM). Here, the model is constructed in the form of a center average fuzzy interference system, of which the fuzzy rules aredesigned based on the Lyapunov stability condition. In addition, in order to optimize the STLFM, the back propagation learning rulesare used to adjust the fuzzy weighting net. Firstly, experimental data of a damping system using this damper is used to optimize themodel. Next, the optimized model is used to estimate online the damping performance in the real-time conditions. The modeling resultsprove convincingly that the developed model could represent satisfactorily the behavior of the MR fluid damper.
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