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A new hybrid intelligent control algorithm for a seven-link biped walking robot

机译:七连杆双足步行机器人的新型混合智能控制算法

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In recent years, many studies on bipedal walking robots and control algorithms have been conducted. However, different conditions and circumstances that have to be taken into account make the control of biped walking robots a big challenge. This paper proposes the implementation of a new hybrid intelligent control approach for a seven-link biped walking robot to track the specified trajectory based on a compensatory neurofuzzy network and fuzzy controller. This algorithm consists of two main parts: the feedforward compensator includes an integrated compensatory neurofuzzy network for identification of the inverse dynamics model which attempts to cancel the dynamics of the robot, and the feedback controller which includes a Mamdani-type fuzzy controller to compensate the modeling error and the effect of noise on the system. Moreover, a new style of membership functions distribution for fuzzy controller with noise reduction capability is proposed and its influence on the performance of the robot under noise-free and noisy conditions is investigated. Simulations performed on a biped robot illustrate the methods and their performance. The results confirm the high tracking capability and effectiveness of the proposed control approach.
机译:近年来,已经对双足步行机器人和控制算法进行了许多研究。但是,必须考虑到的不同条件和环境使Biped步行机器人的控制成为一大挑战。本文提出了一种基于补偿神经模糊网络和模糊控制器的七链双足步行机器人混合动力智能控制新方法的实现方法。该算法包括两个主要部分:前馈补偿器包括一个集成的补偿神经模糊网络,用于识别试图取消机器人动力学的逆动力学模型;以及反馈控制器,其中包括一个Mamdani型模糊控制器以补偿模型错误和噪声对系统的影响。此外,提出了一种新型的具有降噪能力的模糊控制器隶属函数分布,并研究了其在无噪声和高噪声条件下对机器人性能的影响。在两足动物机器人上进行的仿真说明了方法及其性能。结果证实了所提出的控制方法的高跟踪能力和有效性。

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