scholarly journals Automated Vehicle’s Overtaking Maneuver with Yielding to Oncoming Vehicles in Urban Area Based on Model Predictive Control

2021 ◽  
Vol 11 (19) ◽  
pp. 9003
Author(s):  
Yan Zhang ◽  
Xun Shen ◽  
Pongsathorn Raksincharoensak
Keyword(s):  
Model Predictive Control ◽  
Predictive Control ◽  
Rapid Development ◽  
Steering Wheel ◽  
Automated Driving ◽  
Driver Assistance Systems ◽  
Passenger Cars ◽  
Safety Assurance ◽  
Safety Constraints ◽  
Reasonable Behavior

The rapid development of automated driving technology has brought many emerging technologies. The collision avoidance (CA) function by braking and/or steering maneuver of advanced driver assistance systems (ADAS), which contributes to the improvement of the safety of automated vehicles, has been playing an important role in recent modern passenger cars and commercial vehicles. When an automated vehicle needs to avoid multiple obstacles at the same time, consuming travel time and safety assurance of CA need to be carefully considered especially in the case related to unpredictable motion of obstacles. This paper proposes a feasible solution to this situation by controlling speed and the steering wheel angle. The proposed motion re-planning based on post-encroachment time (PET) provides a judgment of a function which calculates the possibility of unavoidable road accidents. Then the path re-planning layer of a novel two-layer model predictive control (TL-MPC) will re-plan a local trajectory and give a reference acceleration. Finally, the path tracking layer outputs steering wheel angle to follow the trajectory under the premise of ensuring safety constraints. The proposed control system is evaluated by co-simulations of MATLAB/Simulink and CarSim software. The results show that for various conditions of post-encroachment time, the ego vehicle adopting the proposed strategy will conduct reasonable behavior re-planning and consequently successfully avoid obstacles.

scholarly journals Human-like trapezoidal steering angle model on two-lane urban curves

2019 ◽  
Vol 16 (4) ◽  
pp. 172988141986761 ◽  
Author(s):  
Haobin Jiang ◽  
Jie Zhou ◽  
Aoxue Li ◽  
Xinchen Zhou ◽  
Shidian Ma
Keyword(s):  
Model Predictive Control ◽  
Predictive Control ◽  
Rapid Development ◽  
Vehicle Speed ◽  
Automated Vehicles ◽  
Automated Driving ◽  
Steering Angle ◽  
The Road ◽  
Human Likeness ◽  
Simulation Results

With the rapid development of automated vehicles, there is currently a significant amount of automated driving research. Giving automated vehicles capabilities similar to those of experienced drivers will allow them to share the road harmoniously with manned vehicles, especially on two-lane urban curves. To represent the steering behavior of experienced drivers, a series of curve feature distances are proposed, which is determined by multi-regression. These series of curve feature distances are used to generate a trapezoidal steering angle model which imitates the steering behavior of the experienced test drivers. To verify the feasibility and human-likeness of the proposed trapezoidal steering angle model, the model is used with constant vehicle speed to plan a human-like trajectory which is tracked using model predictive control. The simulation results show that the proposed trapezoidal steering angle model is human-like and could be used to give automated vehicles human-like driving capability when driving on two-lane curves.

Coordinative Optimization Control of Microgrid Based on Model Predictive Control

2022 ◽  
pp. 233-252
Author(s):  
Changbin Hu ◽  
Lisong Bi ◽  
ZhengGuo Piao ◽  
ChunXue Wen ◽  
Lijun Hou
Keyword(s):  
Power Generation ◽  
Model Predictive Control ◽  
Predictive Control ◽  
Unit Commitment ◽  
Feedback Mechanism ◽  
Battery Life ◽  
Operation Costs ◽  
Power Generation Technology ◽  
Reasonable Behavior ◽  
And Storage

This article describes how basing on the future behavior of microgrid system, forecasting renewable energy power generation, load and real-time electricity price, a model predictive control (MPC) strategy is proposed in this article to optimize microgrid operations, while meeting the time-varying requirements and operation constraints. Considering the problems of unit commitment, energy storage, economic dispatching, sale-purchase of electricity and load reduction schedule, the authors first model a microgrid system with a large number of constraints and variables to model the power generation technology and physical characteristics. Meanwhile the authors use a mixed logic dynamical framework to guarantee a reasonable behavior for grid interaction and storage and consider the influences of battery life and recession. Then for forecasting uncertainties in the microgrid, a feedback mechanism is introduced in MPC to solve the problem by using a receding horizon control. The objective of minimizing the operation costs is achieved by an MPC strategy for scheduling the behaviors of components in the microgrid. Finally, a comparative analysis has been carried out between the MPC and some traditional control methods. The MPC leads to a significant improvement in operating costs and on the computational burden. The economy and efficiency of the MPC are shown by the simulations.

scholarly journals Analysis of the Influence of Suspension Actuator Limitations on Ride Comfort in Passenger Cars Using Model Predictive Control

Actuators ◽  
2020 ◽  
Vol 9 (3) ◽  
pp. 77 ◽  
Author(s):  
Erik Enders ◽  
Georg Burkhard ◽  
Nathan Munzinger
Keyword(s):  
Model Predictive Control ◽  
Predictive Control ◽  
Ride Comfort ◽  
Rate Of Change ◽  
High Rate ◽  
Passenger Cars ◽  
Wheel Load ◽  
Country Road ◽  
Necessary Constraints ◽  
Vehicle Dynamics Control

Active suspension systems help to deliver superior ride comfort and can be used to resolve the objective conflict between ride comfort and road-holding. Currently, there exists no method for analyzing the influence of actuator limitations, such as maximum force and maximum rate of change, on the achievable ride comfort. This research paper presents a method that is capable of doing this. It uses model predictive control to eliminate the influence of feedback controller performance and to integrate both actuator limitations and necessary constraints on dynamic wheel-load variation and suspension travel. Various scenarios are simulated, such as driving over a speed bump and inner city driving, as well as driving on a country road and motorway driving, using a state-of-the-art quarter-car model, parameterized for a luxury class vehicle. It is analyzed how comfort, or in one scenario road-holding, can be improved with consideration for the actuator limitations. The results indicate that actuator rate limitation has a strong influence on vertical vehicle dynamics control system performance, and that relatively small maximum forces of around 1000 to 2000 N are sufficient to successfully reject disturbances from road irregularities, provided the actuator is capable of supplying the forces at a sufficiently high rate of change.

Coordinative Optimization Control of Microgrid Based on Model Predictive Control

2018 ◽  
Vol 9 (3) ◽  
pp. 57-75 ◽  
Author(s):  
Changbin Hu ◽  
Lisong Bi ◽  
ZhengGuo Piao ◽  
ChunXue Wen ◽  
Lijun Hou
Keyword(s):  
Power Generation ◽  
Model Predictive Control ◽  
Predictive Control ◽  
Unit Commitment ◽  
Feedback Mechanism ◽  
Battery Life ◽  
Power Generation Technology ◽  
Reasonable Behavior ◽  
And Storage ◽  
Generation Technology

This article describes how basing on the future behavior of microgrid system, forecasting renewable energy power generation, load and real-time electricity price, a model predictive control (MPC) strategy is proposed in this article to optimize microgrid operations, while meeting the time-varying requirements and operation constraints. Considering the problems of unit commitment, energy storage, economic dispatching, sale-purchase of electricity and load reduction schedule, the authors first model a microgrid system with a large number of constraints and variables to model the power generation technology and physical characteristics. Meanwhile the authors use a mixed logic dynamical framework to guarantee a reasonable behavior for grid interaction and storage and consider the influences of battery life and recession. Then for forecasting uncertainties in the microgrid, a feedback mechanism is introduced in MPC to solve the problem by using a receding horizon control. The objective of minimizing the operation costs is achieved by an MPC strategy for scheduling the behaviors of components in the microgrid. Finally, a comparative analysis has been carried out between the MPC and some traditional control methods. The MPC leads to a significant improvement in operating costs and on the computational burden. The economy and efficiency of the MPC are shown by the simulations.

scholarly journals Model Predictive Control Tuning: Methods and Issues. Application to steering wheel position control

2017 ◽  
Vol 50 (1) ◽  
pp. 11331-11336 ◽  
Author(s):  
Sergey Abrashov ◽  
Tudor Bogdan Airimitoaie ◽  
Patrick Lanusse ◽  
François Aioun ◽  
Rachid Malti ◽  
...  
Keyword(s):  
Model Predictive Control ◽  
Predictive Control ◽  
Position Control ◽  
Steering Wheel ◽  
Tuning Methods

Visual Servoing of Automatic Alignment System Using Model Predictive Control

2014 ◽  
Vol 625 ◽  
pp. 627-632
Author(s):  
Chi Ying Lin ◽  
Yu Sheng Zeng
Keyword(s):  
Model Predictive Control ◽  
Predictive Control ◽  
Visual Servoing ◽  
Optimization Problem ◽  
Rapid Development ◽  
Economic Benefits ◽  
Image Feature ◽  
Alignment System ◽  
Control Command ◽  
Automatic Alignment

Over the past few decades, vision based alignment has been accepted as an important technique to achieve higher economic benefits for precision manufacturing and measurement applications. Also referred to as visual servoing, this technique basically applies the vision feedback information and drives the moving parts to the desired target location using some appropriate control laws. Although recently rapid development of advanced image processing algorithms and hardware have made this alignment process an easier task, some fundamental issues including inevitable system constraints and singularities, still remain as a challenging research topic for further investigation. This paper aims to develop a visual servoing method for automatic alignment system using model predictive control (MPC). The reason for using this optimal control for visual servoing design is because of its capability of handling constraints such as motor and image constraints in precision alignment systems. In particular, a microassembly system for peg and hole alignment application is adopted to illustrate the design process. The goal is to perform visual tracking of two image feature points based on a XYθ motor-stage system. From the viewpoint of MPC, this is an optimization problem that minimizes feature errors under given constraints. Therefore, a dynamic model consisting of camera parameters and motion stage dynamics is first derived to build the prediction model and set up the cost function. At each sample step the control command is obtained by solving a quadratic programming optimization problem. Finally, simulation results with comparison to a conventional image based visual servoing method demonstrate the effectiveness and potential use of this method.

Rapid development of modular and sustainable nonlinear model predictive control solutions

2017 ◽  
Vol 60 ◽  
pp. 51-62 ◽  
Author(s):  
Sergio Lucia ◽  
Alexandru Tătulea-Codrean ◽  
Christian Schoppmeyer ◽  
Sebastian Engell
Keyword(s):  
Model Predictive Control ◽  
Predictive Control ◽  
Nonlinear Model ◽  
Rapid Development ◽  
Nonlinear Model Predictive Control
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