scholarly journals Automatic Train Operation Speed Profile Optimization and Tracking with Multi-Objective in Urban Railway

2019 ◽  
Vol 48 (1) ◽  
pp. 57-64 ◽  
Author(s):  
Xiaomin Zhu ◽  
Qian Pu ◽  
Qian Zhang ◽  
Runtong Zhang
Keyword(s):  
Fuzzy Controller ◽  
Speed Profile ◽  
Control Effect ◽  
Multi Objective ◽  
Operation Speed ◽  
Train Operation ◽  
Objective Model ◽  
Simulation Results ◽  
Profile Optimization ◽  
Automatic Train Operation

Besides energy-efficiency, people also want train operation to be comfortable, punctual and parking precise. In this paper, a multi-objective model for automatic train operation in urban railway is proposed by unifying dimensions of different objectives firstly. This model is built by applying multi-objective decision with the penalty function, based on the analysis of train performance and its operation environment. Then a genetic algorithm is developed to solve this model and obtain the optimal recommended speed profiles. Thirdly, fuzzy controller is designed to achieve track recommended speed profiles. Finally, with the help of Matlab software, control effect is verified based on simulation. From the simulation results, it can be seen this strategy can meet the requirement of multi-objective, which are energy-saving, parking precisely, running punctually and comfort.

scholarly journals Multi-Objective Hybrid Optimization Algorithm Using a Comprehensive Learning Strategy for Automatic Train Operation

Energies ◽  
2019 ◽  
Vol 12 (10) ◽  
pp. 1882
Author(s):  
Longda Wang ◽  
Xingcheng Wang ◽  
Kaiwei Liu ◽  
Zhao Sheng
Keyword(s):  
Optimization Algorithm ◽  
Learning Strategy ◽  
Optimization Algorithms ◽  
Hybrid Optimization ◽  
Multi Objective ◽  
Chaotic Mapping ◽  
Hybrid Optimization Algorithm ◽  
Whale Optimization ◽  
Train Operation ◽  
Automatic Train Operation

Aiming at the problem of easy-to-fall-into local convergence for automatic train operation (ATO) velocity ideal trajectory profile optimization algorithms, an improved multi-objective hybrid optimization algorithm using a comprehensive learning strategy (ICLHOA) is proposed. Firstly, an improved particle swarm optimization algorithm which adopts multiple particle optimization models is proposed, to avoid the destruction of population diversity caused by single optimization model. Secondly, to avoid the problem of random and blind searching in iterative computation process, the chaotic mapping and the reverse learning mechanism are introduced into the improved whale optimization algorithm. Thirdly, the improved archive mechanism is used to store the non-dominated solutions in the optimization process, and fusion distance is used to maintain the diversity of elite set. Fourthly, a dual-population evolutionary mechanism using archive as an information communication medium is designed to enhance the global convergence improvement of hybrid optimization algorithms. Finally, the optimization results on the benchmark functions show that the ICLHOA can significantly outperform other algorithms for contrast. Furthermore, the ATO Matlab/simulation and hardware-in-the-loop simulation (HILS) results show that the ICLHOA has a better optimization effect than that of the traditional optimization algorithms and improved algorithms.

Study of Fuzzy Control for Intelligent Cantilever Beam Based on Genetic Algorithm

2011 ◽  
Vol 204-210 ◽  
pp. 25-30 ◽  
Author(s):  
Jing Jun Zhang ◽  
Xiao Pin Guo ◽  
Li Li He ◽  
Rui Zhen Gao
Keyword(s):  
Genetic Algorithm ◽  
Fuzzy Control ◽  
Cantilever Beam ◽  
Fuzzy Controller ◽  
Controller Design ◽  
Fitness Function ◽  
Fuzzy Rules ◽  
Control Effect ◽  
The Core ◽  
Simulation Results

The design of fuzzy controller is the key of fuzzy control system, while the core of fuzzy controller design lies in fuzzy rules, whose performance determines the control effect of fuzzy system. General fuzzy rules are obtained from expert experience, in which much subjectivity exists. In this paper, a fuzzy controller is designed by taking an intelligent cantilever beam as the research object. And a method using the genetic algorithm to optimize fuzzy rules is proposed and the genetic coding as well as the fitness function is confirmed. Finally, the simulation model of intelligent cantilever beam is built by Matlab/Simulink, and the vibration control effects of fuzzy controller optimized by genetic algorithm are compared with those un-optimized. The simulation results indicate that the vibration amplitude of intelligent cantilever beam has a significant decrease and the vibration decay rate has a significant increase after the fuzzy rules optimized.

scholarly journals Speed profile optimization of an electrified train in Cat Linh-Ha Dong metro line based on pontryagin's maximum principle

2020 ◽  
Vol 10 (1) ◽  
pp. 233 ◽  
Author(s):  
An Thi Hoai Thu Anh ◽  
Nguyen Van Quyen ◽  
Nguyen Thanh Hai ◽  
Nguyen Van Lien ◽  
Vu Hoang Phuong
Keyword(s):  
Energy Consumption ◽  
Maximum Principle ◽  
Energy Efficient ◽  
Pontryagin’S Maximum Principle ◽  
Regenerative Braking ◽  
Speed Profile ◽  
Pontryagin's Maximum Principle ◽  
Efficient Operation ◽  
Train Operation ◽  
Profile Optimization

An urban railway is a complex technical system that consumes large amounts of energy, but this means of transportation still has been obtained more and more popularity in densely populated cities because of its features of high-capacity transportation capability, high speed, security, punctuality, lower emission, reduction of traffic congestion. The improved energy consumption and environment are two of the main objectives for future transportation. Electrified trains can meet these objectives by the recuperation and reuse of regenerative braking energy and by the energy - efficient operation. Two methods are to enhance energy efficiency: one is to improve technology (e.g., using energy storage system, reversible or active substations to recuperate regenerative braking energy, replacing traction electric motors  by energy-efficient traction system as permanent magnet electrical motors; train's mass reduction by lightweight material mass...); the other is to improve operational procedures (e.g. energy efficient driving including: eco-driving; speed profile optimization; Driving Advice System (DAS); Automatic Train Operation (ATO); traffic management optimization...). Among a lot of above solutions for saving energy, which one is suitable for current conditions of metro lines in Vietnam. The paper proposes the optimization method based on Pontryagin's Maximum Principle (PMP) to find the optimal speed profile for electrified train of Cat Linh-Ha Dong metro line, Vietnam in an effort to minimize the train operation energy consumption.

Energy-Efficient Train Operation Strategy with Speed Profiles Selection for an Urban Metro Line

2019 ◽  
Vol 2673 (4) ◽  
pp. 348-360 ◽  
Author(s):  
Pengli Mo ◽  
Lixing Yang ◽  
Ziyou Gao
Keyword(s):  
Energy Consumption ◽  
Programming Model ◽  
Computational Time ◽  
Speed Profile ◽  
Operational Environment ◽  
Passenger Demand ◽  
Proposed Model ◽  
Train Operation ◽  
Automatic Train Operation ◽  
Metro System

In the daily operations of a metro system, physical trains track the speed profiles which are embedded in the automatic train operation (ATO) system, and the speed profile plays a key role in determining both energy consumption and travel time. With consideration of the real-world operational environment and uncertain levels of passenger demand, this study specifically proposes an integer programming model with respect to energy consumption to generate a robust operational strategy which determines the speed profile choice on each segment. Because of the computational complexity of the proposed model, a heuristic algorithm is designed, which combines a genetic algorithm (GA) and a nomadic algorithm (NA), to find a good solution in acceptable computational time. Finally, numerical experiments based on the Beijing Yizhuang metro line are implemented to verify the effectiveness and efficiency of this approach.

Sign in / Sign up

Export Citation Format

Share Document