Synchronization controller for a 3-R planar parallel pneumatic artificial muscle (PAM) robot using modified ANFIS algorithm

详细信息    查看全文

• 作者：Le Duy Khoa^a ; ^{duykhoale2010@hotmail.com} ; Dinh Quang Truong^a ; ^{truongdq@ulsan.ac.kr} ; Kyoung Kwan Ahn^b ; ^{kkahn@ulsan.ac.kr}
• 关键词：Motion synchronization ; Pneumatic artificial muscle ; ANFIS ; Parallel planar robot
• 刊名：Mechatronics
• 出版年：2013
• 出版时间：June, 2013
• 年：2013
• 卷：23
• 期：4
• 页码：462-479
• 全文大小：2537 K

文摘

Parallel manipulator is a closed-kinematic chain mechanism in which performance of its end effector - moving platform is contributed by its independent actuators. In traditional designs, each elemental actuator has its own controller as well as reference input, and it works independently without gathering information from its neighbors. Consequently, as one of the actuators cannot keep up with the others, the platform performance is easily deteriorated due to the lack of coherence between these actuators. Therefore, the aim of this paper is to design a 3-R planar parallel robot and develop a proper synchronization controller for its tracking control task. Adaptive Network Based Fuzzy Inference System (ANFIS) algorithm was modified and applied as the main strategy of this synchronization controller. The controller is then able to compensate errors between the actuators and enforce them to cooperate harmonically with each other regardless external disturbances caused by the outside environment or geometrical constraints of the closed-loop structure. Simulations and practical experiments on a scaled parallel robot were carried out to evaluate the designed controller. The results showed that by applying the proposed control technique, the working errors of the component actuators converged quickly to zero almost at the same time. As a result, the tracking performance of the common platform was significantly improved in comparison with the performance when applying a non-synchronization controller. The proposed method is effective in controlling systems which require collaborations between the sub-agents.