Closer than Close: MEC-Assisted Platooning with Intelligent Controller Migration

2021 ◽  
Author(s):  
Constantine Ayimba ◽  
Michele Segata ◽  
Paolo Casari ◽  
Vincenzo Mancuso
Keyword(s):  
Intelligent Controller

Dynamic Anti-Saturation Integral Controller Used in Time-Varying Delay System

2011 ◽  
Vol 467-469 ◽  
pp. 766-769
Author(s):  
Gui You Pu ◽  
Ge Wen Kang
Keyword(s):  
Variable Structure ◽  
Delay System ◽  
Time Varying ◽  
Control Methods ◽  
Simulation Studies ◽  
Motor Speed ◽  
Intelligent Controller ◽  
Time Varying Delay ◽  
Integral Controller ◽  
Varying Delay

Systems with large variable delay, traditional control methods can’t performance well. In this paper, a controller combined with the human-simulated intelligent controller (HSIC) and newly dynamic anti-saturation integral controller, is used in the time-varying delay motor speed control. Simulation studies show, there is no chatter in this controller which is always in norm variable structure controller and this method reaches good performance in the time-varying delay system.

An intelligent controller for process automation

1991 ◽  
Vol 4 (1) ◽  
pp. 55-73 ◽  
Author(s):  
Vivek V. Badami ◽  
Paul Nielsen ◽  
James B. Comly
Keyword(s):  
Process Automation ◽  
Intelligent Controller

Direct Inverse Control for ECRH Voltage Based on ICA-CMAC

2011 ◽  
Vol 268-270 ◽  
pp. 1755-1758
Author(s):  
Xiao Ping Luo ◽  
Peng Ying Du ◽  
Ying Qi Ge
Keyword(s):  
Nonlinear System ◽  
Power Supply ◽  
Cyclotron Resonance ◽  
Control Experiment ◽  
Electron Cyclotron Resonance ◽  
Electron Cyclotron Resonance Heating ◽  
Quick Response ◽  
High Voltage Power Supply ◽  
Inverse Control ◽  
Intelligent Controller

The negative high-voltage power supply of Electron Cyclotron Resonance Heating (ECRH) is a nonlinear system with serve sensitivity and it is not well for traditional controller to meet restrict demand on stability and quick response. Based on the concept of credit a novel CMAC is designed to accelerate the convergence of traditional CMAC and also is used as an intelligent controller for the power of ECRH based on the idea on direct inverse control. Experiment results show that ICA-CMAC can control the power of ECRH well with shorter settling time and less CPU consumption thus the validity of ICA-CMAC is determined.

Study on Intelligent Controller Design of Flow Metrological Calibration System

2020 ◽  
Author(s):  
Xiong Yin ◽  
Kai Wen ◽  
Yan Wu ◽  
Lei Zhou ◽  
Jing Gong
Keyword(s):  
Neural Network ◽  
Natural Gas ◽  
Pid Controller ◽  
Controller Design ◽  
Calibration System ◽  
Calibration Process ◽  
Intelligent Controller ◽  
Flow Adjustment ◽  
Precise Adjustment ◽  
Valve Opening

Abstract In recent years, China ramped up imports of natural gas to satisfy the growing demand, which has increased the number of trade meters. Natural gas flowmeters need to be calibrated regularly at calibration stations to ensure their accuracy. Nowadays, the flow metrological calibration process is done by the operator manually in China, which is easy to be affected by personnel experience and proficiency. China is vigorously developing industry 4.0 and AI(artificial intelligence) technologies. In order to improve the calibration efficiency, a design scheme of intelligent controller for flow metrological calibration system is first proposed in this paper. The intelligent controller can replace the operator for process switching and flow adjustment. First, the controller selects the standard flowmeter according to the type of the calibrated flowmeter, and switches the calibration process. To accurately control the calibration flow for 180 seconds, the controller continuously adjusts the regulating valve with a sequence of commands to the actuator. These commands are generated by intelligent algorithm which is predefined in the controller. Process switching is operated automatically according to flowmeter calibration specifications. In order to reach the required flow point quickly, the flow adjustment is divided into two steps: preliminary adjustment and precise adjustment. For preliminary adjustment, a BP neural network will be built first using the field historical data and simulation results. This neural network describes the relationship between the valve-opening scheme and the calibration flow. Therefore, it could give a calibration flow as close as possible to the expected value during calibration. For precise adjustment, an adaptive PID controller is used. It could adjust the valve opening degree automatically to make sure the flow deviation meet the calibration requirements. Since the PID controller is a self-adaptive PID controller, the process of adjustment is very quick, which can reduce the calibration time largely. After each calibration, both the original neural network and the adaptive function of the controller will be updated to achieve the self-growth. With the information of the calibrated flowmeter, the entire calibration system can run automatically. The experiment in a calibration station shows that the intelligent controller can control the deviation of the flow value within 5% during 4∼5 minutes.

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