Design of PID Controller Based on Echo State Network With Time-Varying Reservoir Parameter

2021 ◽  
pp. 1-12
Author(s):  
Zhanshan Wang ◽  
Xianshuang Yao ◽  
Tieshan Li ◽  
Huaguang Zhang
Keyword(s):  
Pid Controller ◽  
Echo State Network ◽  
Time Varying ◽  
Reservoir Parameter

A Multi-Resolution PID Controller Based on the Wavelet Transform

2012 ◽  
Vol 472-475 ◽  
pp. 632-636 ◽  
Author(s):  
Cun Zhi Yao ◽  
Gui Xiang Zhang
Keyword(s):  
Control System ◽  
Wavelet Transform ◽  
Pid Controller ◽  
Control Design ◽  
Cumulative Effect ◽  
Measurement Noise ◽  
Time Varying ◽  
Error Signal ◽  
Proportional Integral Derivative ◽  
Proportional Integral Derivative Controller

The non-linear and time-varying natures of the process together with the large disturbances of several types are the key challenge for the control design. A controller based on multi- resolution decomposition using wavelets is presented in the paper. The wavelet is used to decompose the error signal into signals at different scales.These signals are then used to compensate for the uncertainties in the plant.The controller is similar to proportional integral derivative controller in principle and application. the output from this control system represents the cumulative effect of uncertainties such as measurement noise, frictional variations and external torque disturbances which manifest at different scales. This controller better solves the nonlinear and time-varying togetther with the great disturbance.

Application of BP Neural Network PID Controller in Landing Gear Based on MRF Damper

2015 ◽  
Vol 779 ◽  
pp. 226-232 ◽  
Author(s):  
Shi Xing Zhu ◽  
Yue Han ◽  
Bo Wang
Keyword(s):  
Neural Network ◽  
Bp Neural Network ◽  
Pid Controller ◽  
Experimental Testing ◽  
Computation Time ◽  
Landing Gear ◽  
Time Varying ◽  
Control Effect ◽  
Simulation And Experiment ◽  
Neural Network Pid

For characteristics of nonlinearity and time-varying volatility of landing gear based on MR damper, a BP neural network PID controller with a momentum was designed on basis of established dynamic mathematical model. BP neural network would adjust three parameters of PID online in time. The controller was inputted the energy which was combined by the feedback of acceleration and displacement of the control system, which greatly reduced the computation time of controller and the control effect was more obvious. After compared with PID, the simulation and experiment have showed that BP neural network PID has a better effect. The arithmetic can be put into practice through experimental testing.

Self-Tuning Predictive PID Controller Using a Time-Varying Proportional Gain

2014 ◽  
Vol 1049-1050 ◽  
pp. 929-933
Author(s):  
Rong Jia ◽  
Bin Liu ◽  
Kai Fang
Keyword(s):  
Real Time ◽  
Pid Controller ◽  
Design Method ◽  
Time Varying ◽  
System Parameters ◽  
Coprime Factorization ◽  
Self Tuning

This paper proposes a new design method of adaptive GPC-based PID controller. The proportional gain of a PID controller is time-varying, and the PID controller is designed based on strongly stable GPC that is extended by using coprime factorization. Hence, a GPC law can be approximated by the PID controller finely. Finally, the system parameters are updated in real-time to resist to disturbance, by using the RLS method. Simulation examples show the effectiveness of the proposed method.

Research on Temperature Control System of Fruit and Vegetable Processing Line Based on Fuzzy Immune PID

2013 ◽  
Vol 420 ◽  
pp. 395-400
Author(s):  
Yong Ling He ◽  
Yuan Liu ◽  
Xiang Gui Wei ◽  
Qian Feng Zhang ◽  
Jie Ping Li ◽  
...  
Keyword(s):  
Control System ◽  
Water Temperature ◽  
Temperature Control ◽  
Pid Controller ◽  
Temperature Control System ◽  
Time Varying ◽  
Fruit And Vegetable ◽  
Processing Line ◽  
Processing Water ◽  
Mouth Feel

Temperature control has direct effect on mouth feel of fruit and vegetable processing products. This paper, by analyzing the control requirements of cucumber slices processing water temperature, proposes to control the water temperature for cucumber slice processing production line by using fuzzy immune PID. With the features of time-varying, nonlinear and hysteretic nature for temperature control, this paper designs fuzzy immune PID controller by borrowing the regulating action of immune system and linking the advantages of immune PID controller.

scholarly journals Adaptive Feedback Control for a Pasteurization Process

Processes ◽  
2020 ◽  
Vol 8 (8) ◽  
pp. 930
Author(s):  
Emil D.J. Rasmussen ◽  
Massimiliano Errico ◽  
Stefania Tronci
Keyword(s):  
Control Strategy ◽  
Adaptive Algorithm ◽  
Pid Controller ◽  
Linear Control ◽  
Control Algorithms ◽  
Time Varying ◽  
Control Parameters ◽  
Adaptive Feedback ◽  
Control Approach ◽  
Adaptive Feedback Control

The milk pasteurization process is nonlinear in nature, and for this reason, the application of linear control algorithms does not guarantee the obtainment of the required performance in every condition. The problem is here addressed by proposing an adaptive algorithm, which was obtained by starting from an observer-based control approach. The main result is the obtainment of a simple PI-like controller structure, where the control parameters depend on the state of the system and are adapted online. The proposed algorithm was designed and applied on a simulated process, where the temperature dependence of the milk’s physical properties was considered. The control strategy was tested by simulating different situations, particularly when time-varying disturbances entered the system. The use of the adaptive rule reduces the variance generally introduced by the PI or PID controller.

Algorithm and Implementation of Smith Predictive Control

2014 ◽  
Vol 687-691 ◽  
pp. 60-63
Author(s):  
Zi De Tian
Keyword(s):  
Predictive Control ◽  
Pid Controller ◽  
Control Algorithm ◽  
Computer Control ◽  
Delay System ◽  
Smith Predictor ◽  
Time Varying ◽  
Math Model ◽  
Time Varying Delay ◽  
Varying Delay

With invariable time delay theoretically,Smith predictor is deeply studied,the fact that the Smith predictor depends on the math model of the system is found ,and so it is very difficult to control the time-varying delay system well. Therefore,it is necessary to take an effective method--using PID controller with the digital Smith predictor,and studying its control algorithm,and doing the simulation in the lab of micro-computer control. Simulation results have proved the efficiency of the algorithm and the validity.

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