Intelligent Impedance Control using Wavelet Neural Network for dynamic contact force tracking in unknown varying environments

DPM-LES investigation on flow field dynamic and acoustic characteristics of a twin-fluid nozzle by multi-field coupling method

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

In this paper, an active fault-tolerant control (FTC) system design is proposed for an n-degree-of-freedom (n-DOF) hydraulic manipulator with internal leakage faults and mismatched/matched lumped disturbances. A pair of matched and mismatched disturbance observers (DOBs) is proposed to simultaneously estimate and compensate for the effects of matched/mismatched disturbances on the control system in healthy conditions. The fault detection is achieved when the estimated matched disturbance is larger than a threshold. After that, a novel control reconfiguration law is designed to switch from a normal controller to a fault-tolerant controller with an online identification algorithm based on an adaptive mechanism. The proposed active FTC guarantees the position tracking performance in not only single-fault but also simultaneous-faults conditions. Moreover, the problem of uniting disturbance-observer-based control for external disturbance and adaptive control for parametric uncertainty is solved in a novel approach. Simulation results are conducted in a two-degree-of-freedom hydraulic leg prototype, which verifies the effectiveness of the proposed method.

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Active Fault Tolerant Control System Design for Hydraulic Manipulator With Internal Leakage Faults Based on Disturbance Observer and Online Adaptive Identification

In this study, a humanoid prototype of 2-DOF (degrees of freedom) lower limb exoskeleton is introduced to evaluate the wearable comfortable effect between person and exoskeleton. To improve the detection accuracy of the human-robot interaction torque, a BPNN (backpropagation neural networks) is proposed to estimate this interaction force and to compensate for the measurement error of the 3D-force/torque sensor. Meanwhile, the backstepping controller is designed to realize the exoskeleton's passive position control, which means that the person passively adapts to the exoskeleton. On the other hand, a variable admittance controller is used to implement the exoskeleton's active follow-up control, which means that the person's motion is motivated by his/her intention and the exoskeleton control tries best to improve the human-robot wearable comfortable performance. To improve the wearable comfortable effect, serval regular gait tasks with different admittance parameters and step frequencies are statistically performed to obtain the optimal admittance control parameters. Finally, the BPNN compensation algorithm and two controllers are verified by the experimental exoskeleton prototype with human-robot cooperative motion.

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Control and Implementation of 2-DOF Lower Limb Exoskeleton Experiment Platform

In this paper, aimed at the problem of control accuracy when the traditional position-based impedance control is applied in the hydraulic drive unit (HDU) of legged robot, a kind of nonlinear model-based variable impedance parameters controller (MVIPC) is designed. First, the mathematical model of position-based impedance control for HDU is given. Second, the performance of traditional position-based impedance control is tested on the HDU performance test platform under different working conditions, and the experimental results show that the control accuracy of this control method needs to be improved greatly. Thirdly, the control idea of MVIPC is described, and the theoretical derivation is deduced. MVIPC considers the high-order dynamic characteristics of servo valve, pressure-flow nonlinearity of servo valve, oil compressibility and load characteristics. Finally, the control performance of MVIPC is verified on the HDU performance test platform. The experimental results show that MVIPC can significantly improve the performance of traditional position-based impedance control, and have an excellent adaptability under different working conditions. This research can provide an underlying control method of hydraulic systems during the robot locomotion.

A Nonlinear Model-based Variable Impedance Parameters Control for Position-based Impedance Control System of Hydraulic Drive Unit

Kinematics correction algorithm for the LHDS of a legged robot with semi-cylindrical foot end based on V-DOF

Each joint of hydraulic drive legged robot adopts highly integrated electro-hydraulic servo system, and the system has two common forms, namely, valve-controlled cylinder system and pump-controlled cylinder system. The former has a large energy loss, which restricts the endurance of the legged robot in the field. Although the latter has the advantages of energy saving and high efficiency, the overall response ability of control system is unsatisfied. In this paper, a novel pump-valve compound drive system (PCDS) is designed. It combines the advantages of pump-controlled cylinder system and valve-controlled cylinder system, which can not only effectively reduce the energy loss of the system, but also ensure the electro-hydraulic servo system of the robot joint has the ideal response ability. This paper consists of three parts. In the first part, the mathematical model of nonlinear force control of PCDS is established, which takes into account the pressure-flow nonlinearity of servo valve, the asymmetry of servo cylinder and the complexity and variability of load. So this model has a high accuracy. In the second part, On the basis of the above model, a force control method combining tracking error compensation and load compensation control is designed. And this control method can improve the control precision of the robot. In the third part, the performance of the designed control method is verified by experiments. The experiments show that the designed force control method can effectively reduce the influence of external position disturbance on the tracking accuracy of the force control system and improve the control accuracy of the robot joint movement.

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Design, Mathematical Modeling and Force Control for Electro-Hydraulic Servo System With Pump-Valve Compound Drive

Hydraulic drive mode enables legged robots to have excellent characteristics, such as greater power-to-weight ratios, higher load capacities, and faster response speeds than other robots. Nowadays, highly integrated valve-controlled cylinder, called the hydraulic drive unit (HDU), is employed to drive the joints of these robots. However, there are some common problems in the HDU resulted from hydraulic systems, such as strong nonlinearity, asymmetry dynamic characteristics between positive and negative moving directions of the piston rod, and time-varying parameters. It is difficult to obtain the desired control performance by just using classical control methods such as the traditional PID control. In this paper, a position controller that combines fuzzy terminal sliding mode control (FTSMC) and time delay estimation (TDE) is proposed, in which FTSMC adopts a compound reaching law which combines the tangent function and the exponential reaching law. Moreover, the fuzzy control is introduced to adjust the parameters of the reaching law in real time to improve the adaptability of FTSMC. Based on FTSMC, the external uncertain disturbance of the HDU position control system is estimated by TDE, which ensures the simplicity of system modeling and the normal application of FTSMC. Finally, the control effects of the controller combining FTSMC and TDE are verified on the HDU performance test platform and the load simulation experiment platform. The experimental results show that the proposed controller greatly improves the system position control performance and has a strong disturbance rejection ability and a good adaptability under different working conditions. The above research results can provide an important reference and experimental basis for the inner loop of compliance control of legged robots.

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Jun-xiao Zhang

Papers

A Nonlinear Model-based Variable Impedance Parameters Control for Position-based Impedance Control System of Hydraulic Drive Unit

Kinematics correction algorithm for the LHDS of a legged robot with semi-cylindrical foot end based on V-DOF

Design, Mathematical Modeling and Force Control for Electro-Hydraulic Servo System With Pump-Valve Compound Drive

Fuzzy Terminal Sliding Mode Control with Compound Reaching Law and Time Delay Estimation for HDU of Legged Robot