Experimental Study on H∞ Control for United Brake of Electric Vehicle

2011 ◽  
Vol 204-210 ◽  
pp. 498-501
Author(s):  
Chuan Wei Zhang
Keyword(s):  
Robust Control ◽  
Electric Vehicle ◽  
Pid Control ◽  
Control Strategies ◽  
Tracking Error ◽  
Research Work ◽  
Response Speed ◽  
Rotational Inertia ◽  
Variable Load ◽  
Braking Distance

This paper discusses different united brake control strategies of electric vehicle (EV), presents a novel H∞ robust united brake control strategy for EV. Research work is done under different conditions namely variable battery voltage and variable load rotational inertia, separately. A comparison between conventional PID control and H∞ robust control is done when they are applied to the above mentioned conditions. Under the united brake condition, the experimental results show that the braking distance is shortened by the united brake system in the emergent brake; the braking ability of the EV is improved. H∞ robust control has better performance than the traditional PID control both in steady-state tracking error and response speed.

Experiment of H∞ Driving Control System for Electric Vehicle

2010 ◽  
Vol 20-23 ◽  
pp. 215-219 ◽  
Author(s):  
Chuan Wei Zhang
Keyword(s):  
Electric Vehicle ◽  
Pid Controller ◽  
Tracking Error ◽  
Research Work ◽  
Response Speed ◽  
Rotational Inertia ◽  
Variable Load ◽  
Battery Voltage ◽  
Robust Controller ◽  
Drive Control

This paper discusses different drive control methods of electric vehicle (EV), presents the design of H∞ robust controller for driving control, with the consideration of protecting the battery. Research work is done under different conditions namely variable battery voltage and variable load rotational inertia separately. Experiments show that the H∞ robust controller has better performance than the PID controller in both steady-state tracking error and response speed. Moreover, the H∞ robust controller can improve the drive range of electric vehicle.

Linear Motor Control Algorithm and Experimental Research Based on Feedforward Fuzzy PID

2014 ◽  
Vol 620 ◽  
pp. 363-368
Author(s):  
Lian Xia ◽  
Jing Qiu ◽  
Jiang Han
Keyword(s):  
Pid Control ◽  
Feedforward Control ◽  
Tracking Error ◽  
Response Speed ◽  
Linear Motor ◽  
Fuzzy Pid ◽  
Fuzzy Pid Control ◽  
Theory Analysis ◽  
Speed Tracking ◽  
Load Change

In this paper, theory analysis, the MATLAB research and experimental verification about feedforward fuzzy PID control have been performed by combining the characteristics of the PID, feedforward control and fuzzy control. Simulation results show that the feedforward fuzzy PID control could improve the response speed of the system and reduce the tracking error of the system which shows the obvious superiority compared with the PID, feedforward PID, and fuzzy PID. Load experiment for such four kinds of control modes is done on the linear motor platform, and the experimental results show that the accuracy of the feedforward fuzzy PID control is obviously higher than the other three kinds of control modes and the feedforward fuzzy PID control is easier to be implemented. The position error of feedforward fuzzy PID control is changeless during the load change, and the change of the speed tracking error is small, which proves that the feedforward fuzzy PID control is suitable for the condition of load change or the great disturbance.

Design of Optimum Controller of APT Fine Tracking Control System

2013 ◽  
Vol 712-715 ◽  
pp. 2738-2741 ◽  
Author(s):  
Ming Qiu Li ◽  
Shu Hua Jiang
Keyword(s):  
Pid Control ◽  
Tracking Control ◽  
Control Algorithm ◽  
Tracking System ◽  
Dynamic Performance ◽  
Tracking Error ◽  
Stable State ◽  
Response Speed ◽  
Optimum Control ◽  
Performance Requirements

APT (Acquisition, Pointing, and Tracking) system of space laser communication adopts compound axis structure; it consists of coarse tracking and fine tracking system. Its response speed and tracking precision mainly rests with the fine tracking system. Traditional PID control algorithm often is used in APT fine tracking system. In order to improve the dynamic performance of the system and decrease the tracking error, optimum control technology was adopted in this paper. On the basis of considering the system dynamic performance requirements and tracking precision requirement, optimum controller was designed. The simulation result shows that the bandwidth of APT fine tracking system is up to 1310 Hz, and the stable state error is less than 0.002. Compared with PID control, optimum control can improve the tracking performance of system.

Simulation Research on Neural Network Sliding Mode Control of Energy-Regenerative Braking of Electric Vehicle

2010 ◽  
Vol 37-38 ◽  
pp. 1187-1190 ◽  
Author(s):  
Jian Bo Cao ◽  
Shi Ju E ◽  
Xi Lin Zhu ◽  
Hong Kui Jiang ◽  
Bing Gang Cao
Keyword(s):  
Neural Network ◽  
Electric Vehicle ◽  
Sliding Mode ◽  
Tracking Error ◽  
Response Speed ◽  
Regenerative Process ◽  
Regenerative Braking ◽  
Current Loop ◽  
Simulation Research ◽  
State Tracking

To improve the energy-regenerative efficiency and robustness of electric vehicle (EV), a novel energy-regenerative controller was designed and applied to the charge current loop of the EV. The controller that combines neural network (NN) with traditional sliding mode controller (SMC) comprises a radial basis function NN (RBFNN) and a SMC. The RBFNN is used to adaptively adjust the switching gain of the SMC. The simulation model of the energy-regenerative system is built with MATLAB/SIMULINK, and the simulation results show that comparing with traditional SMC, the NNSMC has better performance at response speed, steady-state tracking error and resisting disturbance in energy-regenerative process. Additionally, it can recover more energy.

scholarly journals Modeling & design of a ANN controller for a BLDC motor on Propulsion Application for Hybrid Electric Vehicle

2019 ◽  
Vol 8 (2S11) ◽  
pp. 3994-4000
Keyword(s):  
Electric Vehicle ◽  
Hybrid Electric Vehicle ◽  
High Efficiency ◽  
Reactive Power ◽  
Control Strategies ◽  
Research Work ◽  
Torque Ripple ◽  
Voltage Source ◽  
Bldc Motor ◽  
Motor Speed

This paper proposes the brushless direct current (BLDC) motor with high power density and high efficiency characteristics may be used to propulsion framework for electric vehicle. The progressive model for BLDC motor under rotor flux linkage route reference frame might have been providing. Here we analyzed the chart of ann vector and principal of ann control strategies and proposing the ann based reactive power with BLDC motor. To make ann based framework on active power, torque ripple, dc voltage, power factors can be used BLDC motor was designed. After designed simulation results was test the validity of field weakening based on reactive power with BLDC for electric vehicle application. In this research work will introduced artificial neural network (ANN) for non electrical input used. To control the BLDC motor speed it can using pulse width modulated control of the voltage source inverter (VLSI) using DC link voltage (Vdc) controller. To perform electronic commutation by hall signal sensing they are using PWM signal, to generate PWM signal inbuilt encoder can be used in this circuit. Analyze the BLDC motor performance driving propulsion framework is carried out under the MATLAB/Simulink software’s and efficiency of whole frame work is calculated under various source conditions

scholarly journals Ethylene Sensor-Enabled Dynamic Monitoring and Multi-Strategies Control for Quality Management of Fruit Cold Chain Logistics

Sensors ◽  
2020 ◽  
Vol 20 (20) ◽  
pp. 5830
Author(s):  
Xuepei Wang ◽  
Xinwu Li ◽  
Daqi Fu ◽  
Rajko Vidrih ◽  
Xiaoshuan Zhang
Keyword(s):  
Quality Management ◽  
Control Strategies ◽  
Response Speed ◽  
Chromatic Aberration ◽  
Quality Parameters ◽  
Soluble Solids ◽  
Cold Chain ◽  
Dynamic Monitoring ◽  
Quality Loss ◽  
Exogenous Ethylene

Due to the presence of bioactive compounds, fruits are an essential part of people’s healthy diet. However, endogenous ethylene produced by climacteric fruits and exogenous ethylene in the microenvironment could play a pivotal role in the physiological and metabolic activities, leading to quality losses during storage or shelf life. Moreover, due to the variety of fruits and complex scenarios, different ethylene control strategies need to be adapted to improve the marketability of fruits and maintain their high quality. Therefore, this study proposed an ethylene dynamic monitoring based on multi-strategies control to reduce the post-harvest quality loss of fruits, which was evaluated here for blueberries, sweet cherries, and apples. The results showed that the ethylene dynamic monitoring had rapid static/dynamic response speed (2 ppm/s) and accurately monitoring of ethylene content (99% accuracy). In addition, the quality parameters evolution (firmness, soluble solids contents, weight loss rate, and chromatic aberration) showed that the ethylene multi-strategies control could effectively reduce the quality loss of fruits studied, which showed great potential in improving the quality management of fruits in the supply chain.

scholarly journals The Effects of Weighting Functions on the Performances of Robust Control Systems

Proceedings ◽  
2020 ◽  
Vol 63 (1) ◽  
pp. 46
Author(s):  
Mircea Dulau ◽  
Stelian-Emilian Oltean
Keyword(s):  
Robust Control ◽  
Control Systems ◽  
Tracking Error ◽  
Weighting Functions ◽  
Loop Control ◽  
Frequency Sensitivity ◽  
Sensitivity Functions ◽  
Loop Control System ◽  
Robust Control Design ◽  
Robust Control Systems

An important stage in robust control design is to define the desired performances of the closed loop control system using the models of the frequency sensitivity functions S. If the frequency sensitivity functions remain within the limits imposed by these models, the control performances are met. In terms of the sensitivity functions, the specifications include: shape of S over selected frequency ranges, peak magnitude of S, bandwidth frequency, and tracking error at selected frequencies. In this context, this paper presents a study of the effects of the specifications of the weighting functions on the performances of robust control systems.

scholarly journals Neoteric Fuzzy control stratagem and design of Chopper fed Multilevel Inverter for enhanced Voltage Output involving Plug-In Electric Vehicle (PEV) applications

Electronics ◽  
2019 ◽  
Vol 8 (10) ◽  
pp. 1092 ◽  
Author(s):  
Sunddararaj ◽  
Rangarajan ◽  
Gopalan
Keyword(s):  
Electric Vehicle ◽  
New Technologies ◽  
Control Strategies ◽  
Economic Benefits ◽  
Multilevel Inverter ◽  
Control Logic ◽  
Bidirectional Converters ◽  
Hybrid Controller ◽  
And Control ◽  
Novel Design

The utilization of plug-in electric vehicles (PEV) has started to garner more attention worldwide considering the environmental and economic benefits. This has led to the invention of new technologies and motifs associated with batteries, bidirectional converters and inverters for Electric Vehicle applications. In this paper, a novel design and control of chopper circuit is proposed and configured with the series and parallel connection of the power electronic based switches for two-way operation of the converter. The bidirectional action of the proposed converter makes it suitable for plug-in electric vehicle applications as the grid is becoming smarter. The DC–DC converter is further interfaced with the designed multilevel inverter (MLI). The reduced switches associated with the novel design of MLI have overcome the cons associated with the conventional inverters in terms of enhanced performance in the proposed design. Further, novel control strategies have been proposed for the DC–DC converter based on Proportional Integral (PI) and Fuzzy based control logic. For the first time, the performance of the entire system is evaluated based on the comparison of proposed PI, fuzzy, and hybrid controllers. New rules have been formulated for the Fuzzy based controllers that are associated with the Converter design. This has further facilitated the interface of bidirectional DC–DC converter with the proposed MLI for an enhanced output voltage. The results indicate that the proposed hybrid controller provides better performance in terms of voltage gain, ripple, efficiency and overall aspects of power quality that forms the crux for PEV applications. The novelty of the design and control of the overall topology has been manifested based on simulation using MATLAB/SIMULINK.

Robust Control Method Based on Machine Learning for Boiler Combustion System

2014 ◽  
Vol 685 ◽  
pp. 368-372 ◽  
Author(s):  
Hao Zhang ◽  
Ya Jie Zhang ◽  
Yan Gu Zhang
Keyword(s):  
Robust Control ◽  
Intelligent Control ◽  
Pid Control ◽  
Control Algorithm ◽  
Control Method ◽  
Support Vector ◽  
Control Performance ◽  
Fuzzy Pid Control ◽  
On Line ◽  
Control Output

In this study, we presented a boiler combustion robust control method under load changes based on the least squares support vector machine, PID parameters are on-line adjusted and identified by LSSVM, optimum control output is obtained. The simulation result shows control performance of the intelligent control algorithm is superior to traditional control algorithm and fuzzy PID control algorithm, the study provides a new control method for strong non-linear boiler combustion control system.

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