Research on Position Recognition and Control Method of Single-leg Joint of Hydraulic Quadruped Robot

2021 ◽  
Vol 14 ◽  
Author(s):  
Bingwei Gao ◽  
Hao Guan ◽  
Wenming Tang ◽  
Wenlong Han ◽  
Shilong Xue
Keyword(s):  
Mathematical Model ◽  
Control System ◽  
Pid Control ◽  
Control Algorithm ◽  
Position Control ◽  
Quadruped Robot ◽  
Identification Method ◽  
Indirect Identification ◽  
The Mathematical Model ◽  
Position Control System

: In order to obtain the precise mathematical model of the position control system of the hydraulic quadruped robot, and to meet the requirements of the system parameters in different stages of motion, this paper studies the position control system of the single-leg joint of the hydraulic quadruped robot: First of all, this paper uses the closed-loop indirect identification method to identify the position of the leg joints of the hydraulic quadruped robot to obtain the mathematical model of the system; And then, the speed PID control algorithm and speed planning algorithm are designed, so that the system can quickly respond to the changes of system input according to the requirements of different speeds; Finally, the joint position control system of the hydraulic quadruped robot is simulated and verified by experiments. Background: The mathematical model of the positioning system of the hydraulic quadruped robot is clear, but the parameters in the model have the characteristics of uncertainty and time-variation. In the joint position control system of a hydraulic quadruped robot, different motion stages have different requirements for system parameters. Objective: The purpose of this study is to obtain the precise mathematical model of the position control system of the hydraulic quadruped robot and to meet the requirements of the system parameters in different stages of motion. Method: This research takes the hydraulic quadruped robot single-leg system as the research object and uses the closed-loop indirect identification method to identify the position of the leg joints of the hydraulic quadruped robot to obtain the mathematical model of the system. Then, the speed PID control method is designed and compared with the ordinary PID control by taking the positioning control accuracy of the robot before touching the ground as a standard to carry out the controlled trial. Results: In this research, the identification method and control algorithm are designed, and finally, the simulation and experimental research are carried out. The results of the simulation and experiment verify the correctness of the identification method and the effectiveness of the control algorithm. Conclusion: First of all, this paper uses the closed-loop indirect identification method to identify the position of the leg joints of the hydraulic quadruped robot to obtain the mathematical model of the system. Then, the speed PID control algorithm and speed planning algorithm are designed so that the system can quickly respond to the changes of system input according to the requirements of different speeds.

Position Control System of a Trunk in an Upward Airflow

2014 ◽  
Vol 657 ◽  
pp. 699-703
Author(s):  
Petru Gabriel Puiu ◽  
Daniel Drilea ◽  
Dragoş Iulian Nedelcu ◽  
Dragoș Andrioaia
Keyword(s):  
Mathematical Model ◽  
Control System ◽  
Physical Model ◽  
Position Control ◽  
Flow Simulations ◽  
Paper Work ◽  
Solid Works ◽  
The Mathematical Model ◽  
Position Control System ◽  
Made In

This paper work presents some aspects of modeling the behavior an object in an upward airflow with possible applications in pneumatic elevators. In the premises known from the literature, was formulated the physical model of corp behavior at air flow varying. In the first stage of the work, was completed in Solid Works the physical model and the functioning simulation in Flow Simulations. The imput data was provided in solving the mathematical model in Matcad 13. To achieve the control system was chose an open sources software solution with SCADA interface made in Pro wiew.

Simulation on Electro-Hydraulic Proportional Position Control System under Pressure Boundary Conditions

2011 ◽  
Vol 186 ◽  
pp. 21-25
Author(s):  
Jin Yu ◽  
Yuan Li ◽  
Xiao Kang Xu
Keyword(s):  
Mathematical Model ◽  
Control System ◽  
Boundary Conditions ◽  
Position Control ◽  
Step Response ◽  
Quick Response ◽  
Bode Diagram ◽  
The Mathematical Model ◽  
Pressure Boundary Conditions ◽  
Position Control System

Nowadays, the hydraulic straightening presses play an important role in straightening mandrels. For different mandrels, straightening forces and reductions differ. So the proportional position control system under pressure boundary conditions is required. The mathematical model of the system is deduced, and simulation of the system is carried out by MATLAB. The curves of step response and Bode diagram show that the system is steady and quick-response. The error caused by load is analyzed, which meets the straightening requirements and validates its design. The work in this paper can provide a high guidance for presses of similar kinds.

scholarly journals Application of Fuzzy Neural Network PID In Laser-guided Mortar Projectile

2021 ◽  
Vol 2113 (1) ◽  
pp. 012078
Author(s):  
Yang Song ◽  
Fangxiu Jia ◽  
Xiaoming Wang ◽  
Dingming Meng ◽  
Lei Zhuang
Keyword(s):  
Neural Network ◽  
Mathematical Model ◽  
Control System ◽  
Pid Control ◽  
Control Algorithm ◽  
Fuzzy Neural Network ◽  
Electromechanical Actuator ◽  
Fuzzy Neural ◽  
The Mathematical Model ◽  
Neural Network Pid

Abstract Based on the high control performance requirement of laser-guided mortar control system, the permanent magnet synchronous motor (PMSM) is adopted in this paper as the electromechanical actuator of the system, the mathematical model of the motor is analyzed, and the vector control technology is adopted to achieve precise control of position, speed and torque of the electromechanical actuator. Aiming at the characteristics of non-linearity, strong coupling and large parameter changes of the system in flight, an improved fuzzy neural network PID control method is proposed by combining the classical PID control algorithm with fuzzy control and neural network control algorithm to realize the real-time tuning and optimization of PID parameters. The mathematical model of the electromechanical actuator control system is established and simulated. The results show that the fuzzy neural network PID control has good tracking performance, small amplitude error, and strong adaptability to load changes.

Angular Position Control of Fluid-Driven Spindle

2009 ◽  
Author(s):  
Yohichi Nakao ◽  
Naoya Asaoka
Keyword(s):  
Mathematical Model ◽  
Control System ◽  
Steady State ◽  
Disturbance Observer ◽  
Position Control ◽  
Angular Position ◽  
Experimental Results ◽  
The Mathematical Model ◽  
Position Control System ◽  
State Error

A precise spindle is essential to achieve precision machining, such as diamond turning. A fluid driven spindle supported by hydrostatic bearings was thus designed and tested. A feature of the spindle is that several flow channels are designed in its rotor so that driving torque can be generated by supplying pressurized flow into the channels. Rotational speed of the spindle can be controlled by the flow rate. In addition, the rotational direction of the spindle can be controlled by switching supply ports. Thus angular position control of the spindle is achieved by designing appropriate feedback controller. In the present paper, mathematical model of the spindle was thus derived in order for designing an angular position control system. Then spindle characteristics calculated by the mathematical model were compared with experimental results. Furthermore, the angular position control system that has a disturbance observer in its feedback loop was designed based on the mathematical model. The performance of the designed control system was experimentally investigated through the step response. Experimental results verified that the designed controller minimizes the steady state error of angular position of the spindle. Consequently, the steady state error was comparable with the resolution of the rotary encoder, 0.018 degree. In particular, the experimental results indicated that the disturbance observer effectively reduced the influence of various load torque on the angular position of the spindle.

Research on the Servo Position Control System of the Carrying Manipulator Based on Pneumatic Drive

2012 ◽  
Vol 462 ◽  
pp. 748-752
Author(s):  
Mei Ning Zhao ◽  
Fang Wang ◽  
Miao Xin Dong
Keyword(s):  
Mathematical Model ◽  
Control System ◽  
Position Control ◽  
Heating Furnace ◽  
Pneumatic Drive ◽  
Molding Machine ◽  
Driving System ◽  
Control Character ◽  
Position Control System

Ammunition fuse shell is carried rapidly by the carrying manipulator from heating furnace to molding machine, so manipulator need accurate repeated position. The servo position control system is established to meet manipulator multi-point and flexible location based on pneumatic driving system. Linear mathematical model of the servo position control system is built based proper assumption, and model was used to analyze control system theoretically. The carrying manipulator can satisfy demands including decided order and positions; the control character is good by debugging.

A Control System on Soil Temperature

2014 ◽  
Vol 599-601 ◽  
pp. 673-679
Author(s):  
Shi Guo Chen ◽  
Li Hua Hu ◽  
Dong Sheng Wu ◽  
Xue Yong Chen
Keyword(s):  
Mathematical Model ◽  
Control System ◽  
Soil Temperature ◽  
Control Algorithm ◽  
Soil Ecology ◽  
Control Soil ◽  
Pid Algorithm ◽  
And Control ◽  
The Mathematical Model

The soil’s temperature plays an important role of soil ecology research. In order to gain and control soil’ temperature. A control system is proposed for soil’s temperature. And a new control algorithm which is based on the PID algorithm is designed in the control system to handle the complex change of the soil’s temperature. It does not need to know the mathematical model of soil’s temperature. At last, the control result is analyzed in this paper. The result shows that the soil’s temperature is controlled ideal by this control system which is accurate to 0.5°C.

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