scholarly journals Lateral Stability Control of Four-Wheel Independent Drive Electric Vehicles Based on Model Predictive Control

2018 ◽  
Vol 2018 ◽  
pp. 1-15 ◽  
Author(s):  
Bin Huang ◽  
Sen Wu ◽  
Song Huang ◽  
Xiang Fu
Keyword(s):  
Model Predictive Control ◽  
Predictive Control ◽  
Control Algorithm ◽  
Control Method ◽  
Integrated Control ◽  
Stability Control ◽  
Lateral Stability ◽  
Integrated Simulation ◽  
Consumption Rates ◽  
Experiment Verification

Four-wheel independent drive electric vehicle was used as the research object to discuss the lateral stability control algorithm, thus improving vehicle stability under limit conditions. After establishing hierarchical integrated control structure, we designed the yaw moment decision controller based on model predictive control (MPC) theory. Meanwhile, the wheel torque was assigned by minimizing the sum of consumption rates of adhesion coefficients of four tires according to the tire friction ellipse theory. The integrated simulation platform of Carsim and Simulink was established for simulation verification of yaw/rollover stability control algorithm. Then, we finished road experiment verification of real vehicle by integrated control algorithm. The result showed that this control method can achieve the expectation of effective vehicle tracking, significantly improving the lateral stability of vehicle.

scholarly journals A Robust Control Method for Lateral Stability Control of In-Wheel Motored Electric Vehicle Based on Sideslip Angle Observer

2018 ◽  
Vol 2018 ◽  
pp. 1-11 ◽  
Author(s):  
Yaxiong Wang ◽  
Feng Kang ◽  
Taipeng Wang ◽  
Hongbin Ren
Keyword(s):  
Robust Control ◽  
Electric Vehicles ◽  
Control Algorithm ◽  
Control Method ◽  
Stability Control ◽  
Lateral Stability ◽  
Level Control ◽  
Sideslip Angle ◽  
Safety Control ◽  
Yaw Moment

In-wheel motored powertrain on electric vehicles has more potential in maneuverability and active safety control. This paper investigates the longitudinal and lateral integrated control through the active front steering and yaw moment control systems considering the saturation characteristics of tire forces. To obtain the vehicle sideslip angle of mass center, the virtual lateral tire force sensors are designed based on the unscented Kalman filtering (UKF). And the sideslip angle is estimated by using the dynamics-based approaches. Moreover, based on the estimated vehicle state information, an upper level control system by using robust control theory is proposed to specify a desired yaw moment and correction front steering angle to work on the electric vehicles. The robustness of proposed algorithm is also analyzed. The wheel torques are distributed optimally by the wheel torque distribution control algorithm. Numerical simulation is carried out in Matlab/Simulink-Carsim cosimulation environment to demonstrate the effectiveness of the designed robust control algorithm for lateral stability control of in-wheel motored vehicle.

scholarly journals Research on Tracking Control of A Quadrotor UAV Based on Model Predictive Control and PD Control

2021 ◽  
Vol 2085 (1) ◽  
pp. 012008
Author(s):  
Jimin Yu ◽  
Zhi Yong ◽  
Yousi Wang
Keyword(s):  
Model Predictive Control ◽  
Predictive Control ◽  
Tracking Control ◽  
Control Algorithm ◽  
Control Method ◽  
Control Input ◽  
Pd Control ◽  
Quadrotor Uav ◽  
Model Predictive Control Algorithm ◽  
Method Model

Abstract In order to solve the problem of path tracking of a quadrotor UAV, this paper proposes a track tracking control method which combines Model Predictive Control algorithm and PD control method. Model Predictive Control algorithm can generate control input for formation flight and track the specified trajectory. PD control can achieve rapid response to attitude and adjust error quickly. The simulation results verify the effectiveness of the proposed control method.

Application of Model Predictive Control Based on BPNN to Heating Boiler

2011 ◽  
Vol 383-390 ◽  
pp. 2242-2248
Author(s):  
Yan Ping Wang
Keyword(s):  
Neural Network ◽  
Model Predictive Control ◽  
Predictive Control ◽  
Bp Neural Network ◽  
Control Algorithm ◽  
Closed Loop ◽  
Control Method ◽  
Feedback Information ◽  
Heating Boiler ◽  
Controlled Object

This paper presents the algorithm of model predictive control (MPC) based on BP neural network to the burden system of the heating boiler. Because the burden system of the heating boiler is complex, the proposed approach uses steady, effective way to control the boiler. There is a closed-loop, repeating online optimization, model-based control algorithm which deals with the feedback information and the quantity of the fuel entering the boiler by the way of multi-step future predicting and compensating based on BP neural network. By simulation, it is demonstrated that the burden system of the heating boiler using MPC as control method is better in performance than the traditional PID. Besides, it is compliant to the model of the controlled object, especially to those which parameters of the model are variable.

The Research of Wheel Drive Vehicle Yaw Stability Controller Based on Model Predictive Control

2014 ◽  
Vol 998-999 ◽  
pp. 735-740 ◽  
Author(s):  
Chen Guo Zou ◽  
Hong Liang Zhou ◽  
Zhen He
Keyword(s):  
Model Predictive Control ◽  
Predictive Control ◽  
Control Method ◽  
Stability Control ◽  
Safety Control ◽  
Yaw Rate ◽  
Wheel Drive ◽  
Yaw Stability ◽  
Braking Torque ◽  
Driving Torque

As an important active safety control method, vehicle yaw stability control guarantees the dynamic stability of vehicle. A wheel drive vehicle yaw stability controller based on model predictive control theory is designed to plan the longitudinal forces of the four wheels online to control the driving torque or braking torque of each wheel. With the designed controller, the vehicle is able to track the desired yaw rate in the process of turning. The yaw stability and longitudinal characteristics of the vehicle are guaranteed at the same time.

Simulation of the Integrated ABS and DYC Control for 4WID Electric Vehicle with Regenerative Braking

2013 ◽  
Vol 313-314 ◽  
pp. 1125-1129
Author(s):  
Fu Guang Yang ◽  
Jiu Hong Ruan ◽  
Yi Bin Li
Keyword(s):  
Control Method ◽  
Integrated Control ◽  
Stability Control ◽  
Primary Objective ◽  
Regenerative Braking ◽  
Lateral Stability ◽  
Direct Yaw Moment Control ◽  
Electrical Vehicle ◽  
Yaw Moment Control ◽  
Moment Control

Study the lateral stability control method with regenerative braking for 4WID electrical vehicle whiling braking, an integrated control strategy with primary objective to enhance vehicle lateral stability was proposed, by which the regenerative braking, hydraulic braking, ABS and direct yaw moment control system were coordinated effectively. Simulation results on split-μ road indicated that compared with traditional ABS, the integrated control method can improve the lateral stability of vehicle at urgent braking condition, and increase the mileage of electric vehicles.

Nonlinear Model Predictive Tracking Control for Nonholonomic AGV Based on Bio-Inspired Neurodynamics

2013 ◽  
Author(s):  
Xiao-Hong Yin ◽  
Can Yang
Keyword(s):  
Model Predictive Control ◽  
Predictive Control ◽  
Nonlinear Model ◽  
Control Method ◽  
Kinematic Model ◽  
Input Saturation ◽  
Stability Control ◽  
Control Approach ◽  
Velocity Jump ◽  
Control Principle

Considering nonholonomic constraint and input saturation of the Automatic Guided Vehicle (AGV) kinematic model, in the present work the nonlinear model predictive control was applied and a combined tracking/stability control approach was proposed. In addition, the bio-inspired neurodynamics model was applied to generate smooth forward velocities so that the sharp velocity jump can be overcome by the proposed controller. Specifically, an optimal sub-control method consisting of cost function and constraints were obtained based on the model predictive control principle, and a terminal sub-control method was designed to make the control system stable. Finally, the effectiveness of the proposed control strategy was demonstrated through comparison studies with simulations.

Nonlinear model predictive control of spacecraft relative motion

2018 ◽  
Vol 233 (11) ◽  
pp. 3906-3919 ◽  
Author(s):  
Piotr A Felisiak ◽  
Krzysztof S Sibilski ◽  
Kaiyu Qin ◽  
Gun Li ◽  
Wiesław A Wróblewski
Keyword(s):  
Model Predictive Control ◽  
Motion Control ◽  
Predictive Control ◽  
Relative Motion ◽  
Control Algorithm ◽  
Optimization Problem ◽  
Control Method ◽  
Nonlinear Model Predictive Control ◽  
Model Predictive Control Algorithm ◽  
Control Trajectory

This investigation deals with the problem of spacecraft relative motion control, which is typically associated with the spacecraft rendezvous and proximity maneuvers. Relative position and linear velocity are considered. A distinguishing attribute of the presented approach is consideration of definitely larger relative distance between the satellites than it is commonly addressed in the literature. The presented control method is applicable in the case where the chief satellite moves in a known, highly elliptical orbit. A quasi-optimal control is found by a model predictive control algorithm, where the nonlinear optimization problem is reduced to quadratic optimization by preliminary estimation of the future control trajectory. Significance of the method has been verified using a computer simulation.

Model predictive control for integrated longitudinal and lateral stability of electric vehicles with in-wheel motors

2020 ◽  
Vol 14 (18) ◽  
pp. 2741-2751
Author(s):  
Lin Zhang ◽  
Hong Chen ◽  
Yanjun Huang ◽  
Hongyan Guo ◽  
Haobo Sun ◽  
...  
Keyword(s):  
Model Predictive Control ◽  
Predictive Control ◽  
Electric Vehicles ◽  
Lateral Stability
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