The position-based impedance control combined with compliance-eliminated and feedforward compensation for HDU of legged robot

Ba, Kaixian; Yu, Bin; Zhu, Qiuguo; Gao, Zhengjie; Ma, Guoliang; Jin, Zhengguo; Kong, Xianwen

doi:10.1016/j.jfranklin.2019.08.014

Cited by 18 publications

(7 citation statements)

References 14 publications

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“…The method proposed in this paper is intended to conduct experimental research on the HDU performance test platform of legged robot [22] . The platform is mainly installed by two HDUs in the form of opposite top.…”

Section: A Experimental Resultsmentioning

confidence: 99%

“…The authors' cooperation team has carried out preliminary studies on the mathematical modeling and sensitivity analysis of HDU position control, which lays an application foundation for the research method in this paper [21] . In addition, related control methods based on constant parameter PID control were also studied in the previous study by the authors' cooperation team [22] . However, during the control process, problems such as shutdown to adjust parameters and unsatisfied adaptability of the control method in multiple working conditions are often encountered, so it is urgent to introduce machine learning related theories and combine them with the authors' preliminary research basis.…”

Section: Introductionmentioning

confidence: 99%

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An Improved DDPG and Its Application Based on the Double-Layer BP Neural Network

Zhang

Gao

et al. 2020

IEEE Access

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This paper focused on three application problems of the traditional Deep Deterministic Policy Gradient(DDPG) algorithm. That is, the agent exploration is insufficient, the neural network performance is unsatisfied, the agent output fluctuates greatly. In terms of agent exploration strategy, network training algorithm and overall algorithm implementation, an improved DDPG method based on double-layer BP neural network is proposed. This method introduces fuzzy algorithm and BFGS algorithm based on Armijo-Goldstein criterion, improves the exploration efficiency, learning efficiency and convergence of BP neural network, increases the number of layers of BP neural network to improve the fitting ability of the network, and adopts periodic update to ensure the stable operation of the algorithm. The experimental results show that the deep learning network based on the improved DDPG algorithm has greatly improved the performance compared with the traditional method after multiple rounds of self-learning under variable working conditions. This study lays a theoretical and experimental foundation for the extended application of deep learning algorithm.

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Section: A Experimental Resultsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

An Improved DDPG and Its Application Based on the Double-Layer BP Neural Network

Zhang

Gao

et al. 2020

IEEE Access

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“…The mathematical model of each link of the HDU adopted in this article is the same as the mathematical model of each link of the HDU established by the author in the previous period. 30 –32 To reduce the length, this article will not repeat them. According to the mathematical model of the HDU established in the previous period, five linearly independent system variables are selected as the state variables of the control system for the position-based impedance control system.…”

Section: State Space Expression Of Impedance Control System For Hdumentioning

confidence: 99%

“…In the previous research, the analysis researches the serial-parallel composition on dynamic compliances from both position control inner and impedance outer loop. 30 Aiming at the position-based impedance control system of the HDU, the disturbance rejection controller was designed based on the traditional PID controller to improve the control performance of the position inner loop. 31…”

Section: Introductionmentioning

confidence: 99%

State feedback-based impedance control for legged robot hydraulic drive unit via full-dimensional state observer

Zhu

Huang

et al. 2020

International Journal of Advanced Robotic Systems

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In this article, the hydraulic drive unit that drives the movement of the joint of a legged robot was researched, aiming at improving the control accuracy of the position-based impedance control system with dual input and single output. The state feedback control containing more state information of the system was adopted to replace the traditional output feedback and proportional-integral-derivative (PID) control, through the real-time calculation of the time-varying parameters of the servo valve flow, the nonlinear state space expression of the system was derived, the state feedback matrix and the input transformation amplifier were obtained and the full-dimensional state observer was designed. The experimental results show that the designed full-dimensional state observer can track the state variables of the actual system better. Compared with the traditional output feedback and PID control, state feedback control performs better in aspects of accuracy and system dynamics for the position-based impedance control system, which can further improve the compliance performance of the robot.

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“…After that, with the support of microelectronics technology, the hydraulic control unit became able to integrate with microprocessor, electronic power amplifier and sensor. So, the dynamic control accuracy, intelligence, reliability and robustness of the hydraulic control unit were improved [1][2][3]. When industry entered the 21st century, the tremendous cost of labor and energy forced industry to develop towards energy conservation and intelligence.…”

Section: Introductionmentioning

confidence: 99%

Review and Development Trend of Digital Hydraulic Technology

Zhang

Kong

et al. 2020

Applied Sciences

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Since the emergence of digital hydraulic technology, it has achieved good results in intelligence, integration, energy saving, etc. After decades of development, and it has also attracted wide attention in the industry. However, for many years, the definition of digital hydraulic technology has differed between researchers, and there is no uniform definition. Such a situation affects the development of it to a certain extent. Therefore, this paper gives the exact definition of digital hydraulic technology based on a large number of researches on it. At the same time, the paper analyzes the research status and developmental process of the such a technology, and we forecast the development trend of it.

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The position-based impedance control combined with compliance-eliminated and feedforward compensation for HDU of legged robot

Cited by 18 publications

References 14 publications

An Improved DDPG and Its Application Based on the Double-Layer BP Neural Network

An Improved DDPG and Its Application Based on the Double-Layer BP Neural Network

State feedback-based impedance control for legged robot hydraulic drive unit via full-dimensional state observer

Review and Development Trend of Digital Hydraulic Technology

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