Time-Optimal Coordination Control for the Gear-Shifting Process in Electric-Driven Mechanical Transmission (Dog Clutch) without Impacts

2020 ◽  
Vol 9 (2) ◽  
pp. 155-168
Author(s):  
Ziwang Lu ◽  
◽  
Guangyu Tian ◽  
Keyword(s):  
Control Strategy ◽  
Position Control ◽  
Control Method ◽  
Synchronization Control ◽  
Mechanical Transmission ◽  
Coordination Control ◽  
Optimal Position ◽  
Drive Motor ◽  
Time Optimal ◽  
Optimal Coordination

Torque interruption and shift jerk are the two main issues that occur during the gear-shifting process of electric-driven mechanical transmission. Herein, a time-optimal coordination control strategy between the the drive motor and the shift motor is proposed to eliminate the impacts between the sleeve and the gear ring. To determine the optimal control law, first, a gear-shifting dynamic model is constructed to capture the drive motor and shift motor dynamics. Next, the time-optimal dual synchronization control for the drive motor and the time-optimal position control for the shift motor are designed. Moreover, a switched control for the shift motor between a bang-off-bang control and a receding horizon control (RHC) law is derived to match the time-optimal dual synchronization control strategy of the drive motor. Finally, two case studies are conducted to validate the bang-off-bang control and RHC. In addition, the method to obtain the appropriate parameters of the drive motor and shift motor is analyzed according to the coordination control method.

A Synchronous Control Strategy for Independent Multi-Motor System Based on CMAC

2012 ◽  
Vol 468-471 ◽  
pp. 115-121 ◽  
Author(s):  
Wei Min Xu ◽  
Bao Bao Ding ◽  
Rui Geng ◽  
Xian Wen Zhou
Keyword(s):  
Control Strategy ◽  
Control Method ◽  
Synchronization Control ◽  
Control Methods ◽  
Interference Immunity ◽  
Cmac Neural Network ◽  
Drive Systems ◽  
Axis Drive ◽  
Coupling Algorithm ◽  
Control Accuracy

With progress making in the art of industrial fields, control methods for synchronized multi-motor systems get more and more extensive applications, and there are increasingly high requirements for synchronous controllers. In this paper, a new control method for multi-axis drive systems is proposed, an adjacent-coupling algorithm based synchronization control strategy is designed, and a CMAC neural network based controller is developed. Simulation results show good performance of synchronization control accuracy, interference immunity, and convergence for the suggested synchronous controller

Research on Vehicle Chassis Integrated Control Technology Based on Coordination Strategy

2012 ◽  
Vol 249-250 ◽  
pp. 667-671 ◽  
Author(s):  
Kui Yang Wang ◽  
Chuan Yi Yuan ◽  
Jin Hua Tang ◽  
Guo Qing Li
Keyword(s):  
Control Strategy ◽  
Control Method ◽  
Integrated Control ◽  
Steering System ◽  
Suspension System ◽  
Coordination Control ◽  
Feedback Information ◽  
Coordination Strategy ◽  
Negative Effect ◽  
To Receive

In order to eliminate mutual negative effect of brake, steering and suspension system, a kind of layered coordinated control method based on multiple controllers is put forward. Framework of coordination control system of chassis is established, coordination strategy of upper controller and control strategy of lower controllers are designed. The upper controller is used mainly to receive operation information of driver, running state of vehicle and feedback information of lower controllers, and send coordination control strategy to lower controllers. The lower controllers include controller of electro mechanical braking system (EMB), controller of electric power steering system (EPS) and controller of active suspension system (ASS), which are used to receive decision instruction of upper controller, control actuators to accomplish control tasks and send execution situation to upper controller in time.

scholarly journals A Novel Control Method and Mathematical Model for Intelligent Robot

2021 ◽  
Vol 15 ◽  
pp. 486-493
Author(s):  
Nianxiang Wu
Keyword(s):  
Steady State ◽  
Dynamic Response ◽  
Position Control ◽  
Control Method ◽  
Current Control ◽  
Robot Dynamics ◽  
Gravity Compensation ◽  
Drive Motor ◽  
Separate Control ◽  
Fast Dynamic

Hamiltonian method based on action micro-control is widely used in the control of mechanical arm synchronous motor. In order to realize the combination of robot dynamics and drive motor control, Hamiltonian control method is used in this paper to exploit a novel controller for robot, which can be used for better steady-state characteristics in the system. However, dynamic response of port-controlled Hamiltonian (PCH) of control system is slower, so the related control method is exploited and coordinated with the proportional-derivative (PD) plus gravity compensation. At this time, the system has both the fast dynamic response of the PD and the steady state of the PCH. The reverse motor method is used and the two controllers are combined by current conversion to realize the overall control of the robot and the drive motor. The robot drive motor is controlled, and the robot joint position control is combined with the drive motor current control by current conversion. It can be seen from the simulation results that the coordinately controlling the end position of robot can reach the desired position quickly and accurately. Moreover, compared with the separate control of PD plus gravity compensation and PCH control method, it is proved that this scheme has both a fast dynamic process and better performance and ability to resist load torque disturbance. So control method proposed in this paper has a good application prospect

scholarly journals Muscle Coordination Control for an Asymmetrically Antagonistic-Driven Musculoskeletal Robot Using Attractor Selection

2018 ◽  
Vol 2018 ◽  
pp. 1-10
Author(s):  
Shoichiro Ide ◽  
Atsushi Nishikawa
Keyword(s):  
Position Control ◽  
Control Method ◽  
Control Model ◽  
Muscle Coordination ◽  
Human Beings ◽  
Coordination Control ◽  
Living Things ◽  
Antagonistic Muscle ◽  
Musculoskeletal Robot ◽  
Attractor Selection

Recently, numerous musculoskeletal robots have been developed to realize the flexibility and dexterity analogous to human beings and animals. However, because the arrangement of many actuators is complex, the design of the control system for the robot is difficult and challenging. We believe that control methods inspired by living things are important in the development of the control systems for musculoskeletal robots. In this study, we propose a muscle coordination control method using attractor selection, a biologically inspired search method, for an antagonistic-driven musculoskeletal robot in which various muscles (monoarticular muscles and a polyarticular muscle) are arranged asymmetrically. First, muscle coordination control models for the musculoskeletal robot are built using virtual antagonistic muscle structures with a virtually symmetric muscle arrangement. Next, the attractor selection is applied to the control model and subsequently applied to the previous control model without muscle coordination to compare the control model’s performance. Finally, position control experiments are conducted, and the effectiveness of the proposed muscle coordination control and the virtual antagonistic muscle structure is evaluated.

Observer-Based Optimal Position Control for Electrohydraulic Steer-by-Wire System Using Gray-Box System Identified Model

2017 ◽  
Vol 139 (12) ◽  
Author(s):  
Mohamed Aly ◽  
Magdy Roman ◽  
Mohamed Rabie ◽  
Sayed Shaaban
Keyword(s):  
Input Signal ◽  
Control Strategy ◽  
Position Control ◽  
Reference Signal ◽  
Binary Sequence ◽  
Performance Criteria ◽  
Steering Wheel ◽  
Passenger Car ◽  
Optimal Position ◽  
Steer By Wire

Steer-by-wire (SBW) systems in a passenger car can improve vehicle steering capability and design flexibility by replacing the mechanical linkage between the steering wheel and front wheels by a control circuit. The steering controller, however, should provide good performance in response to driver's input signal. This includes fast response, absence of overshoot or oscillatory behavior, and good accuracy with minimal steady-state error. In this paper, an optimal control strategy based on observed system states is proposed and implemented on an electrohydraulic SBW system of a passenger car. First, a linear mathematical model is developed using gray-box system identification techniques. A standard input signal, pseudorandom binary sequence (PRBS), is designed to stimulate the system in the concerned bandwidth. Then, a linear-quadratic regulator (LQR) together with a full-state system observer is designed. Based on simulation, the LQR parameters and the observer poles are chosen to satisfy the aforementioned performance criteria for good steering. Finally, the control strategy is applied in a real-time environment to test the tracking capability, where the system is given high-rate reference signals (relative to the human rate of steering). The results show that the steering system tracks the reference signal with high accuracy even in the existence of high external force disturbances.

scholarly journals Hybrid Force and Position Control Strategy of Robonaut Performing Object Transfer Task

2018 ◽  
Vol 160 ◽  
pp. 05003
Author(s):  
Gang Chen ◽  
Yu-Qi Wang ◽  
Qing-Xuan Jia ◽  
Pei-Lin Cai
Keyword(s):  
Control Strategy ◽  
Position Control ◽  
Control Method ◽  
Transfer Task ◽  
Internal Force ◽  
Matlab Simulation ◽  
Constraint Force ◽  
Common Control ◽  
Transfer Operation ◽  
External Forces

This paper proposes a coordinated hybrid force/position control strategy of robonaut performing object transfer operation. Firstly, the constraint relationships between robonaut and object are presented. Base on them, the unified dynamic model of the robonaut and object is established to design the hybrid force/position control method. The movement, the internal force and the external constraint force of the object are considered as the control targets of the control system. Finally, a MATLAB simulation of the robonaut performing object transfer task verifies the correctness and effectiveness of the proposed method. The results show that all the targets can be control accurately by using the method proposed in this paper. The presented control method can control both internal and external forces while maintaining control accuracy, which is a common control strategy.

scholarly journals Position Control of Cable-Driven Robotic Soft Arm Based on Deep Reinforcement Learning

Information ◽  
2020 ◽  
Vol 11 (6) ◽  
pp. 310
Author(s):  
Qiuxuan Wu ◽  
Yueqin Gu ◽  
Yancheng Li ◽  
Botao Zhang ◽  
Sergey A. Chepinskiy ◽  
...  
Keyword(s):  
Reinforcement Learning ◽  
Control Strategy ◽  
Position Control ◽  
Control Method ◽  
Strategy Training ◽  
Soft Robot ◽  
Robot Arm ◽  
Control Task ◽  
Modeling And Control ◽  
And Migration

The cable-driven soft arm is mostly made of soft material; it is difficult to control because of the material characteristics, so the traditional robot arm modeling and control methods cannot be directly applied to the soft robot arm. In this paper, we combine the data-driven modeling method with the reinforcement learning control method to realize the position control task of robotic soft arm, the method of control strategy based on deep Q learning. In order to solve slow convergence and unstable effect in the process of simulation and migration when deep reinforcement learning is applied to the actual robot control task, a control strategy learning method is designed, which is based on the experimental data, to establish a simulation environment for control strategy training, and then applied to the real environment. Finally, it is proved by experiment that the method can effectively complete the control of the soft robot arm, which has better robustness than the traditional method.

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