scholarly journals Analysis and Verification of Finite Time Servo System Control with PSO Identification for Electric Servo System

Energies ◽  
2019 ◽  
Vol 12 (18) ◽  
pp. 3578 ◽  
Author(s):  
Zhihong Wu ◽  
Ruifeng Yang ◽  
Chenxia Guo ◽  
Shuangchao Ge ◽  
Xiaole Chen
Keyword(s):  
Los Angeles ◽  
Finite Time ◽  
Servo System ◽  
Response Speed ◽  
Physical Parameters ◽  
System Control ◽  
Identification Algorithm ◽  
Control Performance ◽  
Servo Mechanism ◽  
Test Platform

Electric servo system (ESS) is a servo mechanism in a control system of an aircraft, a ship, etc., which controls efficiency and directly affects the energy consumption and the dynamic characteristics of the system. However, the control performance of the ESS is affected by uncertainties such as friction, clearance, and component aging. In order to improve the control performance of the ESS, a control technology combining particle swarm optimization (PSO) and finite time servo system control (FTSSC) was introduced into ESS. In fact, it is difficult to know the uncertain physical parameters of the real ESS. In this paper, the genetic algorithm (GA) was introduced into PSO and the inertia weight was improved, which increased the parameter optimization precision and convergence speed. A new feedback controller is proposed to improve response speed and reduce errors by using FTSSC theory. The performance of the controller based on PSO identification algorithm was verified by co-simulation experiments based on Automatic Dynamic Analysis of Mechanical Systems (ADAMS) (MSC software, Los Angeles, CA, USA) and matrix laboratory (MATLAB)/Simulink (MathWorks, Natick, MA, USA). Meanwhile, the proposed strategy was validated on the servo test platform in the laboratory. Compared with the existing control strategy, the control error was reduced by 75% and the steady-state accuracy was increased by at least 50%.

scholarly journals Synthesis and Verification of Finite-Time Rudder Control with GA Identification for Electric Rudder System

Energies ◽  
2020 ◽  
Vol 13 (6) ◽  
pp. 1379
Author(s):  
Zhihong Wu ◽  
Ruifeng Yang ◽  
Chenxia Guo ◽  
Shuangchao Ge ◽  
Xiaole Chen
Keyword(s):  
Control System ◽  
Los Angeles ◽  
Flight Control ◽  
Finite Time ◽  
Static Characteristic ◽  
Physical Parameters ◽  
Flight Control System ◽  
Control Command ◽  
Control Accuracy

The electric rudder system (ERS) is the executive mechanism of the flight control system, which can make the missile complete the route correction according to the control command. The performance and quality of the ERS directly determine the dynamic quality of the flight control system. However, the transient and static characteristic of ERS is affected by the uncertainty of physical parameters caused by nonlinear factors. Therefore, the control strategy based on genetic algorithm (GA) identification method and finite-time rudder control (FTRC) theory is studied to improve the control accuracy and speed of the system. Differently from the existing methods, in this method, the difficulty of parameter uncertainty in the controller design is solved based on the ERS mathematical model parameter identification strategy. Besides, in this way, the performance of the FTRC controller was verified by cosimulation experiments based on automatic dynamic analysis of mechanical systems (ADAMS) (MSC software, Los Angeles, CA, USA) and matrix laboratory (MATLAB)/Simulink (MathWorks, Natick, MA, USA). In addition, the advantages of the proposed method are verified by comparing with the existing strategy results on the rudder test platform, indicating that the control accuracy is improved by 70% and the steady-state error is reduced by at least 50%.

Application of IFT and SPSA to Servo System Control

2011 ◽  
Vol 22 (12) ◽  
pp. 2363-2375 ◽  
Author(s):  
M.-B Radac ◽  
R.-E Precup ◽  
E. M. Petriu ◽  
S. Preitl
Keyword(s):  
Servo System ◽  
System Control

A PMSM position servo system based on finite-time control

2008 ◽  
Author(s):  
Liu Huixian ◽  
Ding Shihong ◽  
Li Shihua ◽  
Chen Xisong
Keyword(s):  
Finite Time ◽  
Servo System ◽  
Time Control ◽  
Position Servo

Electro-Hydraulic Servo System Controlled by Index Reaching Law Sliding Mode

2011 ◽  
Vol 317-319 ◽  
pp. 1490-1494 ◽  
Author(s):  
Bao Quan Jin ◽  
Yan Kun Wang ◽  
Ya Li Ma
Keyword(s):  
Sliding Mode Control ◽  
Control Strategy ◽  
Position Control ◽  
Sliding Mode ◽  
External Disturbance ◽  
Servo System ◽  
Response Speed ◽  
Reaching Law ◽  
Mode Control ◽  
Hydraulic Servo

The parameters uncertainty and external disturbance play a negative role to improve electro-hydraulic position servo system performance. The valve controlled cylinder system model is established, using the traditional PID control strategy and reaching law control strategy for simulating the system, respectively, the two methods have similar control effects in the ideal model, but considering the external disturbances, the index approaches sliding mode control law has better response speed and stability. Research shown that sliding mode control algorithm has an important role for improving the performance of hydraulic servo position control system.

scholarly journals Modelling of Electro-mechanical Servo System Based on the Planetary Roller Screw Mechanism

2020 ◽  
Vol 306 ◽  
pp. 02004
Author(s):  
Jianxin Zhang ◽  
Chuanming Du ◽  
Shangjun Ma ◽  
Geng Liu
Keyword(s):  
Contact Stiffness ◽  
Servo System ◽  
Response Speed ◽  
Load Force ◽  
System Response ◽  
Analysis Model ◽  
Roller Screw ◽  
Fluctuation Amplitude ◽  
Screw Mechanism ◽  
Main Components

Taking the electro-mechanical servo system as the research object, considering the contact stiffness, friction and clearance of the main components in the electro-mechanical servo system, the analysis model of the electro-mechanical servo system based on Planetary roller screw mechanism (PRSM) is established by using AMESim software. The results showed that the response speed of the system slowed down when the friction of PRSM was taken into account. The larger the clearance or the smaller the stiffness, the greater the fluctuation amplitude of the system response. After the controller was adjusted, the steady-state error of the system caused by the load force can be reduced quickly.

Application of Single Neuron Adaptive PID Control in Electro-Hydraulic Position Servo System

2012 ◽  
Vol 542-543 ◽  
pp. 563-566
Author(s):  
Chao Yong Yan ◽  
Yao Jun Yu
Keyword(s):  
Single Neuron ◽  
Linear Time ◽  
Servo System ◽  
Good Control ◽  
Response Speed ◽  
System Response ◽  
Control Effect ◽  
Time Varying Parameters ◽  
Position Servo ◽  
Adaptive Pid Control

Currently used electro-hydraulic position servo system has more serious non-linear, time-varying parameters and external load disturbance, through the establishment of the system's mathematical model, designed the single neuron adaptive PID controller. Simulation results show that the improved system response speed, steady-state error is small, you can adjust the PID parameters online in real time and good control effect.

Modeling and Simulation of Physical Parameters of Human Respiratory System

2014 ◽  
Vol 658 ◽  
pp. 447-452
Author(s):  
Catarina Meireles ◽  
José Machado ◽  
Celina P. Leão
Keyword(s):  
Respiratory System ◽  
Respiratory Cycle ◽  
Physical Parameters ◽  
System Control ◽  
Common Control ◽  
Non Linear ◽  
Linear Behaviour ◽  
Physiological Profiles ◽  
Mathematical Equations

The respiratory system, due to its non-linear behaviour, is of difficult representation through fixed physical components and common control systems. Therefore, mathematical equations, that represents the respiratory cycle; mechanical components, giving dimension and movement to the simulator; and the electronic components, allowing data acquisition and system control are some factors that must be known and synchronized. The presented work describes the implementation of a mathematical model (in MatLab) that reproduces the non-linear behaviour of the respiratory system, allowing the characterization of different pathophysiological situations. In parallel a graphical interface was developed enabling the user track the change in air flow and volume handled during the respiratory cycle and build physiological profiles of different patients.

Robust BackStepping Control Based DRNN for Flight Simulator

2010 ◽  
Vol 139-141 ◽  
pp. 1708-1713 ◽  
Author(s):  
Dong Kai Shen ◽  
Jing Jing Wang ◽  
Zheng Hua Liu
Keyword(s):  
High Performance ◽  
Design Procedure ◽  
Backstepping Control ◽  
Flight Simulator ◽  
System Control ◽  
Control Performance ◽  
External Disturbances ◽  
Motion Simulator ◽  
Backstepping Controller ◽  
Simulation Results

Flight motion simulator is one kind of servo system with uncertainties and nonlinearities. To acquire higher frequency response and good robustness for the flight simulator, we present a Backstepping controller based on a Diagonal Recurrent Neural Network (DRNN) to work out this problem. For one thing, the design procedure of the robust Backstepping controller is described. Subsequently, the principle and the design steps of DRNN are analyzed and expatiated respectively. In the end, simulation results on the flight motion simulator show that robust backstepping control based on DRNN can compensate for external disturbances and enhance robustness of the system control performance. Therefore both robustness and high performance of the flight motion simulator are achieved.

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