Research on Self-Tuning Observer-Compensator Control Scheme and Its Application

2008 ◽  
Author(s):  
Linhui Liu ◽  
Jie Chen ◽  
Lixin Xu
Keyword(s):  
Control Scheme ◽  
Self Tuning

Application of Active Mount Engine Vibration Isolation to Fuzzy Control Systems

2013 ◽  
Vol 341-342 ◽  
pp. 1023-1027
Author(s):  
Hui Guo ◽  
Guo Chun Sun ◽  
Min Fan
Keyword(s):  
Control Systems ◽  
Pid Control ◽  
Vibration Isolation ◽  
The Body ◽  
Fuzzy Pid Control ◽  
Power Train ◽  
Engine Vibration ◽  
Control Scheme ◽  
Self Tuning ◽  
Piezoelectric Stack Actuator

An automobile power-train active mount system with a piezoelectric stack actuator is introduced. The influence caused by power-train to the body of the car is analyzed by means of parameter self-tuning fuzzy PID control, on which the simulating results are based. It turns out that this control scheme can restrain the influence better caused by power-train to the body of the car.

Performance Enhancement of Pneumatic Vibration Isolators Using Self-Tuning PID Feedback and Time-Delay-Control (TDC)-Based Feedforward Scheme

2018 ◽  
Author(s):  
Jin-Wei Liang ◽  
Hung-Yi Chen ◽  
Lyu-Cyuan Zeng
Keyword(s):  
Mathematical Model ◽  
Performance Enhancement ◽  
Control Method ◽  
Hybrid Control ◽  
Model Performance ◽  
Experimental Investigations ◽  
Isolation System ◽  
Control Scheme ◽  
Self Tuning ◽  
Hybrid Control Scheme

A hybrid control scheme that combines a self-tuning PID-feedback loop and TDC-based feedforward scheme is proposed in this study to cope with an active pneumatic vibration isolator. In order to establish an effective TDC feedforward control a reliable mathematical model of the pneumatic isolator is required and developed firstly. Numerical and experimental investigations on the validity of the mathematical model are performed. It is found that although slight discrepancy exists between predicted and observed behaviors of the system, the overall model performance is acceptable. The resultant model is then applied in the design of the TDC feedforward scheme. A neuro-based adaptive PID control is integrated with the TDC feedforward algorithm to form the hybrid control. Numerical and experimental isolation tests are carried out to examine the suppression performances of the proposed hybrid control scheme. The results show that the proposed hybrid control method outperforms solely TDC feedforward while the latter outperforms the passive isolation system. Moreover, the proposed hybrid control scheme can suppress the vibration near the system’s resonance.

High Altitude Airship Flight Control System Design and Simulation

2011 ◽  
Vol 128-129 ◽  
pp. 142-145
Author(s):  
Yong Hua Fan ◽  
Xin Li ◽  
Yun Feng Yu
Keyword(s):  
Control System ◽  
High Altitude ◽  
System Design ◽  
Flight Control ◽  
Control System Design ◽  
Flight Control System ◽  
Compound Control ◽  
Control Scheme ◽  
Self Tuning

The high altitude airship can not have desired performance to control the altitude rapidly and accurately when the elevator or ancillary air bursa charge or deflation is used only, because the elevator has little efficiency when the velocity is low and auxiliary air bursas charge or deflation control is very slow. It is present a method to design flight control system for a high altitude airship using auxiliary air bursas charge or deflation and elevator combination control. This combination control scheme is that the ancillary air bursa and elevator are also used to control the airship attitude to get large raise velocity and the ancillary air bursa control is used to adjust the airship altitude for suspension. In this paper, a high altitude airship model with compound control of elevator and ancillary air bursa charge and deflation is given firstly. Then the combination controller is designed by using fuzzy self-tuning control. Finally, it has been proved by simulation that the flight control system has desirable performance and the compound control scheme is feasible.

scholarly journals Neuro-PID Control for Electric Vehicle

2011 ◽  
Vol 15 (7) ◽  
pp. 846-853 ◽  
Author(s):  
Shigeru Omatu ◽  
◽  
Michifumi Yoshioka ◽  
Toru Fujinaka ◽  
◽  
...  
Keyword(s):  
Electric Vehicle ◽  
Pid Control ◽  
Control Method ◽  
Torque Control ◽  
Learning Ability ◽  
Control Problems ◽  
Process Industries ◽  
The Neural Network ◽  
Control Scheme ◽  
Self Tuning

In this paper we consider the neuro-control method and its application to control problems of an electric vehicle. The neuro-control methods adopted here is based on Proportional-plus-Integral-plus-Derivative (PID) control, which has been adopted to solve process control or intelligent control problems. In Japan about eighty four percent of the process industries have used the PID control. After deriving the self-tuning PID control scheme (neuro-PID) using the learning ability of the neural network, we will show the control results by using the speed and torque control of an electric vehicle.

Self-tuning proportional, integral and derivative controller based on genetic algorithm least squares

1998 ◽  
Vol 212 (6) ◽  
pp. 437-448 ◽  
Author(s):  
K Warwick ◽  
Y-H Kang
Keyword(s):  
Least Squares ◽  
Adaptive Controller ◽  
Recursive Least Squares ◽  
Industrial Processes ◽  
Industrial Plant ◽  
Parameter Estimator ◽  
Proportional Integral ◽  
Control Scheme ◽  
Self Tuning ◽  
Real Plant

A self-tuning proportional, integral and derivative control scheme based on genetic algorithms (GAs) is proposed and applied to the control of a real industrial plant. This paper explores the improvement in the parameter estimator, which is an essential part of an adaptive controller, through the hybridization of recursive least-squares algorithms by making use of GAs and the possibility of the application of GAs to the control of industrial processes. Both the simulation results and the experiments on a real plant show that the proposed scheme can be applied effectively.

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