Aim To analyse the influence of knowledge base on the performance of the fuzzy controller of the electrohydraulic position control system,and to determine their selection cri- teria. Methods Experiments based on diffe...Aim To analyse the influence of knowledge base on the performance of the fuzzy controller of the electrohydraulic position control system,and to determine their selection cri- teria. Methods Experiments based on different membership functions,scaling factors and con-trol rules were done separately.The experiment results and the influence of different know- ledge base on the control performance were analysed in theory so that criteria of selcting knowledge base can be summarized correctly.Results Knowledge base,including membershipfunctions, scaling factors and control rules,has a crucial effect on the fuzzy control system.Suitably selected knowledge base can lead to good control performance of fuzzy control sys-tem. Conclusion Being symmetric,having an intersection ratio of 1 and satisfying width con- dition are three necessities for selecting membership functions.Selecting scaling factors dependson both the system requirement and a comprehensive analysis in the overshoot,oscillation, rising time and stability. Integrity and continuity must be guaranteed when determining control rules.展开更多
This paper provided a fuzzy-PI control. It makes use of the advantages of fuzzy controller for dynamic characteristics, and the advantages of PI control for steady characteristics of pneumatic position servo. Experime...This paper provided a fuzzy-PI control. It makes use of the advantages of fuzzy controller for dynamic characteristics, and the advantages of PI control for steady characteristics of pneumatic position servo. Experimental results show that positioning accuracy meets the conventional industrial needs, and prove that the fuzzy-PI controller to be correct and more effective than the usual PID controller. The control method improve the dynamic and steady characteristics of the system.展开更多
This paper deals with fuzzy intelligent position control of electro-hydraulic activated robotic excavator for the control of boom, arm and bucket axes. Intelligent control systems are required to overcome unde- sirabl...This paper deals with fuzzy intelligent position control of electro-hydraulic activated robotic excavator for the control of boom, arm and bucket axes. Intelligent control systems are required to overcome unde- sirable stick-slip motion, limit cycles and oscillations. Models of electro-hydraulic servo controlled front end loader excavators are highly nonlinear. The nonlinear model accounts for fluid flow rate of valve, pump hydraulics, and friction forces. The friction forces are modelled by Coulomb, viscous and Stribeck function. Interval Type-2 Fuzzy Logic Controller （IT2FLC） is used to study the time-domain position responses of axes in the presence of external applied load. It has the ability to control the position of each of the three axes with minimum actuator position errors. Models presented are accurate and study the dynamics of the actuator and load. To improve the transient behaviour of the robotic excavator, we elim- inated iitter of the bucket movement in the presence of nonlinearities.展开更多
A nonlinear dynamic friction control is dealt with using dynamic friction observer and intelligent cantrol. The adaptive dynamic friction obsrver based on the LuGre friction is proposed to estimate the friction parame...A nonlinear dynamic friction control is dealt with using dynamic friction observer and intelligent cantrol. The adaptive dynamic friction obsrver based on the LuGre friction is proposed to estimate the friction parameters and a directly friction state variable The dynamic structured Fuzzy Neural Network （RFNN） is designed to give additional robustness to the cantrol system under the presence of the friction model uncertainty. A proposed composite cantrol scheme is applied to the position tracking control of the servo systen. The performances of the proposed friction observer and the friction controller are demonstrated by simulation.展开更多
文摘Aim To analyse the influence of knowledge base on the performance of the fuzzy controller of the electrohydraulic position control system,and to determine their selection cri- teria. Methods Experiments based on different membership functions,scaling factors and con-trol rules were done separately.The experiment results and the influence of different know- ledge base on the control performance were analysed in theory so that criteria of selcting knowledge base can be summarized correctly.Results Knowledge base,including membershipfunctions, scaling factors and control rules,has a crucial effect on the fuzzy control system.Suitably selected knowledge base can lead to good control performance of fuzzy control sys-tem. Conclusion Being symmetric,having an intersection ratio of 1 and satisfying width con- dition are three necessities for selecting membership functions.Selecting scaling factors dependson both the system requirement and a comprehensive analysis in the overshoot,oscillation, rising time and stability. Integrity and continuity must be guaranteed when determining control rules.
文摘This paper provided a fuzzy-PI control. It makes use of the advantages of fuzzy controller for dynamic characteristics, and the advantages of PI control for steady characteristics of pneumatic position servo. Experimental results show that positioning accuracy meets the conventional industrial needs, and prove that the fuzzy-PI controller to be correct and more effective than the usual PID controller. The control method improve the dynamic and steady characteristics of the system.
文摘This paper deals with fuzzy intelligent position control of electro-hydraulic activated robotic excavator for the control of boom, arm and bucket axes. Intelligent control systems are required to overcome unde- sirable stick-slip motion, limit cycles and oscillations. Models of electro-hydraulic servo controlled front end loader excavators are highly nonlinear. The nonlinear model accounts for fluid flow rate of valve, pump hydraulics, and friction forces. The friction forces are modelled by Coulomb, viscous and Stribeck function. Interval Type-2 Fuzzy Logic Controller （IT2FLC） is used to study the time-domain position responses of axes in the presence of external applied load. It has the ability to control the position of each of the three axes with minimum actuator position errors. Models presented are accurate and study the dynamics of the actuator and load. To improve the transient behaviour of the robotic excavator, we elim- inated iitter of the bucket movement in the presence of nonlinearities.
基金supported by Ministry of Knowledge and Economy,Koreathe ITRC(Information Technology Research Center)support program(ⅡTA-2009-C1090-0902-0004)
文摘A nonlinear dynamic friction control is dealt with using dynamic friction observer and intelligent cantrol. The adaptive dynamic friction obsrver based on the LuGre friction is proposed to estimate the friction parameters and a directly friction state variable The dynamic structured Fuzzy Neural Network （RFNN） is designed to give additional robustness to the cantrol system under the presence of the friction model uncertainty. A proposed composite cantrol scheme is applied to the position tracking control of the servo systen. The performances of the proposed friction observer and the friction controller are demonstrated by simulation.
