scholarly journals A Novel Graph and Safety Potential Field Theory-Based Vehicle Platoon Formation and Optimization Method

2021 ◽  
Vol 11 (3) ◽  
pp. 958
Author(s):  
Linheng Li ◽  
Jing Gan ◽  
Xu Qu ◽  
Peipei Mao ◽  
Ziwei Yi ◽  
...  
Keyword(s):  
Traffic Safety ◽  
Potential Field ◽  
Control Method ◽  
Control Strategies ◽  
Optimization Methods ◽  
Optimization Method ◽  
Optimization Strategy ◽  
Transmission Method ◽  
Optimization Control ◽  
Simulation Results

Platooning is considered to be a very effective method for improving traffic efficiency, traffic safety and fuel economy under the connected and automated environment. The prerequisite for realizing these advantages is how to form a platoon without any collisions and how to maintain and optimize the car-following behavior after platoon formation. However, most of the existing studies focus on the platoon configuration and information transmission method, while only a few attempt to address the issue of platoon formation and optimization methods. To this end, this study proposes a novel platoon formation and optimization model combining graph theory and safety potential field (G-SPF) theory for connected and automated vehicles (CAVs) under different vehicle distributions. Compared to previous studies, we innovatively incorporate the concept of the safety potential field to better describe the actual driving risk of vehicles and ensure their absolute safety. A four-step platoon formation and optimization strategy is developed to achieve platoon preliminary formation and platoon driving optimization control. Three traffic scenarios with different CAVs distributions are designed to verify the effectiveness of our proposed platoon formation method based on G-SPF theory, and the simulation results indicate that a collision-free platoon can be formed in a short time. Additionally, the G-SPF-based platoon driving optimization control method is demonstrated by comparing it with two typical control strategies. Compared with the constant spacing and constant time headway control strategies, the simulation results show that our proposed method can improve the traffic capacity by approximately 48.8% and 26.6%, respectively.

scholarly journals Data Driven Robust Energy and Reserve Dispatch Based on a Nonparametric Dirichlet Process Gaussian Mixture Model

Energies ◽  
2020 ◽  
Vol 13 (18) ◽  
pp. 4642
Author(s):  
Li Dai ◽  
Dahai You ◽  
Xianggen Yin
Keyword(s):  
Robust Optimization ◽  
Dirichlet Process ◽  
Forecast Error ◽  
Optimization Methods ◽  
Optimization Method ◽  
Gaussian Mixture ◽  
Data Driven ◽  
Uncertainty Sets ◽  
Uncertainty Set ◽  
Simulation Results

Traditional robust optimization methods use box uncertainty sets or gamma uncertainty sets to describe wind power uncertainty. However, these uncertainty sets fail to utilize wind forecast error probability information and assume that the wind forecast error is symmetrical and independent. This assumption is not reasonable and makes the optimization results conservative. To avoid such conservative results from traditional robust optimization methods, in this paper a novel data driven optimization method based on the nonparametric Dirichlet process Gaussian mixture model (DPGMM) was proposed to solve energy and reserve dispatch problems. First, we combined the DPGMM and variation inference algorithm to extract the GMM parameter information embedded within historical data. Based on the parameter information, a data driven polyhedral uncertainty set was proposed. After constructing the uncertainty set, we solved the robust energy and reserve problem. Finally, a column and constraint generation method was employed to solve the proposed data driven optimization method. We used real historical wind power forecast error data to test the performance of the proposed uncertainty set. The simulation results indicated that the proposed uncertainty set had a smaller volume than other data driven uncertainty sets with the same predefined coverage rate. Furthermore, the simulation was carried on PJM 5-bus and IEEE-118 bus systems to test the data driven optimization method. The simulation results demonstrated that the proposed optimization method was less conservative than traditional data driven robust optimization methods and distributionally robust optimization methods.

A novel global harmony search method based off-line tuning of RFNN for adaptive control of uncertain nonlinear systems

2015 ◽  
Vol 8 (1) ◽  
pp. 69-98 ◽  
Author(s):  
Fouad Allouani ◽  
Djamel Boukhetala ◽  
Fares Boudjema ◽  
Gao Xiao-Zhi
Keyword(s):  
Nonlinear System ◽  
Nonlinear Systems ◽  
Control Method ◽  
Harmony Search ◽  
Optimization Method ◽  
Uncertain Nonlinear Systems ◽  
Content Type ◽  
Supervisory Controller ◽  
Fuzzy Neural ◽  
Simulation Results

Purpose – The two main purposes of this paper are: first, the development of a new optimization algorithm called GHSACO by incorporating the global-best harmony search (GHS) which is a stochastic optimization algorithm recently developed, with the ant colony optimization (ACO) algorithm. Second, design of a new indirect adaptive recurrent fuzzy-neural controller (IARFNNC) for uncertain nonlinear systems using the developed optimization method (GHSACO) and the concept of the supervisory controller. Design/methodology/approach – The novel optimization method introduces a novel improvization process, which is different from that of the GHS in the following aspects: a modified harmony memory representation and conception. The use of a global random switching mechanism to monitor the choice between the ACO and GHS. An additional memory consideration selection rule using the ACO random proportional transition rule with a pheromone trail update mechanism. The developed optimization method is applied for parametric optimization of all recurrent fuzzy neural networks adaptive controller parameters. In addition, in order to guarantee that the system states are confined to the safe region, a supervisory controller is incorporated into the IARFNNC global structure. Findings – First, to analyze the performance of GHSACO method and shows its effectiveness, some benchmark functions with different dimensions are used. Simulation results demonstrate that it can find significantly better solutions when compared with the Harmony Search (HS), GHS, improved HS (IHS) and conventional ACO algorithm. In addition, simulation results obtained using an example of nonlinear system shows clearly the feasibility and the applicability of the proposed control method and the superiority of the GHSACO method compared to the HS, its variants, particle swarm optimization, and genetic algorithms applied to the same problem. Originality/value – The proposed new GHS algorithm is more efficient than the original HS method and its most known variants IHS and GHS. The proposed control method is applicable to any uncertain nonlinear system belongs in the class of systems treated in this paper.

Fractional PIλDμ Control for Steer-by-Wire System

2011 ◽  
Vol 279 ◽  
pp. 423-428 ◽  
Author(s):  
Jie Tian ◽  
Jin Wu ◽  
Ning Chen
Keyword(s):  
Control System ◽  
Control Method ◽  
Optimization Method ◽  
Front Wheel ◽  
Design Parameters ◽  
Computational Simulations ◽  
System A ◽  
Steer By Wire ◽  
Simulation Results ◽  
Wire System

According to the design demands of the steer-by-wire system, a PIlDm controller based on fractional calculus was proposed. Aligning controller and steering controller were respectively designed to achieve the aligning and steering function of the front wheel steering module, which can ensure the robust of the steer-by-wire system during the special ranges of frequency. The five design parameters of fractional PIlDm controller were achieved by optimization method. Oustaloup method was used to approximate the fractional PIlDm controller and simulation model was achieved, which can be used in Matlab/Simulink. Computational simulations of the control system were carried out and simulation results showed the effectiveness of the control method to improve the robust of the steering-by-wire system.

Research on Control Method of Expressway Off-Ramp Based on Q-Learning Algorithm and Extension Control

2012 ◽  
Vol 433-440 ◽  
pp. 6033-6037
Author(s):  
Xiao Ming Liu ◽  
Xiu Ying Wang
Keyword(s):  
Queue Length ◽  
Control Method ◽  
Learning Algorithm ◽  
Control Strategies ◽  
Traffic Light ◽  
Q Learning ◽  
Reward Function ◽  
Movement Characteristics ◽  
Queue Lengths ◽  
Simulation Results

The movement characteristics of traffic flow nearby have the important influence on the main line. The control method of expressway off-ramp based on Q-learning and extension control is established by analyzing parameters of off-ramp and auxiliary road. First, the basic description of Q-learning algorithm and extension control is given and analyzed necessarily. Then reward function is gained through the extension control theory to judge the state of traffic light. Simulation results show that compared to the queue lengths of off-ramp and auxiliary road, control method based on Q-learning algorithm and extension control greatly reduced queue length of off-ramp, which demonstrates the feasibility of control strategies.

scholarly journals Performance comparison of different control strategies for the regulation of DC-DC negative output super-lift luo-converter

2020 ◽  
Vol 10 (6) ◽  
pp. 5785
Author(s):  
Hassan Jassim Motlak ◽  
Ahmed S. Rahi
Keyword(s):  
Sliding Mode Control ◽  
Control Method ◽  
Sliding Mode ◽  
Control Strategies ◽  
Current Mode ◽  
Performance Comparison ◽  
Primary Control ◽  
Mode Control ◽  
Simulation Results ◽  
Negative Output

In last years, dc-dc converters solve the most issues in the industrial application in the area of power electronics, especially renewable energy, military applications and affiliated engineering developments. They are used to convert the DC input that unregulated to regulated output perhaps larger or smaller than input according to the type of converters. This paper presents three primary control method used for negative output Super lift Luo DC-DC converter. These methods include a Voltage mode control (VMC), Current mode control (CMC), and Sliding mode control (SMC). The goal of this article is to study and selected an appropriate and superior control scheme for negative DC-DC converters. The simulation results show the effectiveness of Sliding mode control for enhancing the performance of the negative dc-dc converter. Also, this method can keep the output voltage constant under load conditions. simulation results obtained by the MATLAB/Simulink environment.

scholarly journals Selection of settings of PID regulators for quadrocopter with the use of optimization methods in the Wolfram MATHEMATICA software

2018 ◽  
Vol 19 (6) ◽  
pp. 780-785
Author(s):  
Krzysztof Wieczorkowski ◽  
Leszek Cedro
Keyword(s):  
Optimization Methods ◽  
Optimization Method ◽  
Lagrange Equations ◽  
Wolfram Mathematica ◽  
Simulation Results ◽  
Mathematica Software ◽  
Selection Of

The article presents the method of modeling the dynamics of a quadrocopter and presents a method for the selection of PID regulators. The quadrocopter's dynamics were derived based on the Lagrange equations of the second type. In the form of graphs, the simulation results were presented for the settings selected using the optimization method using the Wolfram Mathematica package

scholarly journals Multiobjective Optimal Formulations for Bus Fleet Size of Public Transit under Headway-Based Holding Control

2019 ◽  
Vol 2019 ◽  
pp. 1-14 ◽  
Author(s):  
Shidong Liang ◽  
Minghui Ma ◽  
Shengxue He
Keyword(s):  
Optimization Model ◽  
Control Method ◽  
Control Strategies ◽  
Optimization Method ◽  
Service Level ◽  
Optimal Number ◽  
Service Reliability ◽  
Fleet Size ◽  
Bus Bunching ◽  
Guaranteed Service

In recent years, with the development of advanced technologies for data collection, real-time bus control strategies have been implemented to improve the daily operation of transit systems, especially headway-based holding control which is a proven strategy to reduce bus bunching and improve service reliability for high-frequency bus routes, with the concept of regulating headways between successive buses. This hot topic has inspired the reconsideration of the traditional issue of fleet size optimization and the integrated bus holding control strategy. The traditional headway-based control method only focused on the regulation of bus headways, without considering the number of buses on the route. The number of buses is usually assumed as a given in advance and the task of the control method is to regulate the headways between successive buses. They did not consider the bus fleet size problem integrated with headway-based holding control method. Therefore, this work has presented a set of optimal control formulations to minimize the costs for the passengers and the bus company through calculating the optimal number of buses and the dynamic holding time, taking into account the randomness of passenger arrivals. A set of equations were formulated to obtain the operation of the buses with headway-based holding control or the schedule-based control method. The objective was to minimize the total cost for the passengers and the bus company in the system, and a Monte Carlo simulation based solution method was subsequently designed to solve the optimization model. The effects of this optimization method were tested under different operational settings. A comparison of the total costs was conducted between the headway-based holding control and the schedule-based holding control. It was found that the model was capable of reducing the costs of the bus company and passengers through utilizing headway-based bus holding control combined with optimization of the bus fleet size. The proposed optimization model could minimize the number of buses on the route for a guaranteed service level, alleviating the problem of redundant bus fleet sizes caused by bus bunching in the traditional schedule-based control method.

Study on Optimization Control Method of the Pickling Process

2013 ◽  
Vol 397-400 ◽  
pp. 1326-1330
Author(s):  
Da Kuo He ◽  
Wei Qin ◽  
Tong Shan Liu ◽  
Qing Yun Yuan
Keyword(s):  
Prediction Model ◽  
Process Optimization ◽  
Control Method ◽  
Model Error ◽  
Operating Variables ◽  
Decision Variables ◽  
Optimization Control ◽  
Pickling Process ◽  
Simulation Results ◽  
Process Prediction

The pickling process is the important metallurgical production process. Based on pickling process prediction model, considering the max economic efficiency as the optimized objective, and seeing the operating variables as the decision variables, this paper establishes the pickling process optimization model and makes the optimized calculation to get the value of each key control circuit. At the same time, considering the pickling process prediction model error brings the uncertainty to the optimization results, based on iterative optimization control thoughts do pickling process optimization control, the simulation results verify the effectiveness of the method.

OPTIMIZATION OF ICE START-STOP BASED ON MPC FOR AN HEV TO IMPROVE FUEL ECONOMY

2017 ◽  
Vol 41 (3) ◽  
pp. 355-374
Author(s):  
Aiyun Gao ◽  
Xiaozhong Deng ◽  
Zhumu Fu ◽  
Mingzhu Zhang
Keyword(s):  
Internal Combustion Engine ◽  
Predictive Control ◽  
Fuel Economy ◽  
Hybrid Electric Vehicle ◽  
Combustion Engine ◽  
Control Strategies ◽  
Fuel Efficiency ◽  
Optimization Method ◽  
Simulation Results ◽  
Operating Points

To improve hybrid electric vehicle (HEV) fuel efficiency further, the decision as to whether the internal combustion engine (ICE) should start or stop is important. This paper presents a novel optimization method of the ICE start-stop by using the model predictive control (MPC) based on equivalent consumption minimization strategy (ECMS). The optimization method and flow of the ICE start-stop are described in detail. Three torque-split control strategies are proposed for the comparison purpose. From the ICE operating points, the fuel consumption and the battery SOC, simulation results reveal that the transient MPC strategy with ICE start-stop has a huge potential for improving the overall fuel economy.

CSVS Method for Spacecraft with Two Flexible Appendages during Attitude Maneuver

2014 ◽  
Vol 1049-1050 ◽  
pp. 939-944
Author(s):  
Guan Yu Wang ◽  
Wei Ping Ge ◽  
Guang Wei Yang ◽  
Sheng Chao Wang
Keyword(s):  
Control Strategy ◽  
Vibration Suppression ◽  
Control Method ◽  
Control Strategies ◽  
Rigid Motion ◽  
Vibration Modes ◽  
Attitude Maneuver ◽  
Dc Motor Control ◽  
Simulation Results ◽  
Flexible Appendages

An angle maneuver control strategy of spacecraft with two flexible appendages based on component synthesis vibration suppression (CSVS) method is put forward. Unwanted flexible vibration modes can be eliminated while desired rigid motion can be achieved by this method. Jet device and Momentum wheel system are used as the actuator of the spacecraft’s angle maneuver. Several time-fuel control strategies are designed for spacecraft with flexible appendages. Simulation results validate the feasibility of the CSVS method. The DC motor control method is researched in order to combine momentum wheel system with CSVS method.

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