Stochastic Model Predictive Control for Urban Traffic Networks

Ye, Bao-Lin; Wu, W.; Gao, H. Oliver; Lu, Yonglin; Cao, Qianqian; Zhu, Lijun

doi:10.3390/app7060588

Cited by 23 publications

(13 citation statements)

References 38 publications

(78 reference statements)

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“…Normally, the thyristor will generate a small amount of third, fifth, and seventh harmonic currents when it is under phase-shifting control. The magnitudes of these harmonic currents are closely related to the trigger angle α of thyristor [29]. Figure 6 shows the curve of the fundamental current and harmonic current in the secondary winding of electromagnetic coupling reactor changing with trigger angle.…”

Section: Influence Of Structure Of Electromagnetic Coupling Reactor Omentioning

confidence: 99%

A Novel Electromagnetic Coupling Reactor Based Passive Power Filter with Dynamic Tunable Function

2018

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Along with massive applications of power electronic equipment and non-linear loads, harmonic pollutions are becoming more serious than ever. This paper describes a novel electromagnetic coupling reactor based passive power filter with dynamic tuning to quickly eliminate harmony. Firstly, the structure and mathematic model of electromagnetic coupling reactor are presented; secondly, the employed parameters, including electromagnetic coupling reactance converter, primary winding coil, and secondary winding coil are designed based on a stable structure of data; then, the test plat of passive dynamic tunable filter is introduced, as well as the performance test. According to the experimental results, the newly designed electromagnetic coupling reactor can effectively eliminate the harmonies generated by the nonlinear load, greatly reducing the harm caused by harmonics on the grid. By fine-tuning the electromagnetic coupling reactor, the dissonance caused by the change of capacitance and other issues can be effectively solved. Finally, the detailed discussion of this paper is presented, and challenges and new future research are discussed.

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Section: Influence Of Structure Of Electromagnetic Coupling Reactor Omentioning

confidence: 99%

A Novel Electromagnetic Coupling Reactor Based Passive Power Filter with Dynamic Tunable Function

2018

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“…Currently, the urban transport community is one of the biggest problems [33]. This paper's primary function is to model and minimize the queue length and the oscillation of green time in urban traffic using predictive model control and neural networks in a genetic algorithm [34].…”

Section: Urban Traffic By Using Predictive Model Controlmentioning

confidence: 99%

Designing the Controller-Based Urban Traffic Evaluation and Prediction Using Model Predictive Approach

2022

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As society grows, the urbanized population proliferates, and urbanization accelerates. Increasing traffic problems affect the normal process of the city. The urban transportation system is vital to the effective functioning of any city. Science and technology are critical elements in improving traffic performance in urban areas. In this paper, a novel control strategy based on selecting the type of traffic light and the duration of the green phase to achieve an optimal balance at intersections is proposed. This balance should be adaptable to fixed behavior of time and randomness in a traffic situation; the goal of the proposed method is to reduce traffic volume in transportation, the average delay for each vehicle, and control the crashing of cars. Due to the distribution of urban traffic and the urban transportation network among intelligent methods for traffic control, the multi-factor system has been designed as a suitable, intelligent, emerging, and successful model. Intersection traffic control is checked through proper traffic light timing modeled on multi-factor systems. Its ability to solve complex real-world problems has made multiagent systems a field of distributed artificial intelligence that is rapidly gaining popularity. The proposed method was investigated explicitly at the intersection through an appropriate traffic light timing by sampling a multiagent system. It consists of many intersections, and each of them is considered an independent agent that shares information with each other. The stability of each agent is proved separately. One of the salient features of the proposed method for traffic light scheduling is that there is no limit to the number of intersections and the distance between intersections. In this paper, we proposed method model predictive control for each intersection’s stability; the simulation results show that the predictive model controller in this multi-factor model predictive system is more valuable than scheduling in the fixed-time method. It reduces the length of vehicle queues.

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“…The most famous explanation is called "Open Loop Optimal Feedback" (Alamir and Allgöwer, 2008;Diego and Carrasco, 2011;Forbes MG et al, 2015). It richly illustrates the four layers of modeling, control, optimization, and logistics in the MPC control method and their relationship (Mayne, 2016;Shiliang Zhang et al, 2017;Sopasakis and Sarimveis, 2017;Ye et al, 2017). In recent years, the application of MPC to PSSs has gradually attracted the attention of scholars.…”

Section: Introductionmentioning

confidence: 99%

A Machine Learning-Based Model Predictive Control Method for Pumped Storage Systems

et al. 2021

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Integrated systems required for renewable energy use are under development. These systems impose more stringent control requirements. It is quite challenging to control a pumped storage system (PSS), which is a key component of such power systems. Because of the S-characteristic area of the PSS pump turbine, traditional proportional-integral-derivative (PID) control induces considerable speed oscillation under medium and low water heads. PSSs are difficult to model because of their nonlinear characteristics. Therefore, we propose a machine learning (ML)-based model predictive control (MPC) method. The ML algorithm is based on Koopman theory and experimental data that includes PSS state variables, and is used to establish linear relationships between the variables in high-dimensional space. Subsequently, a simple, accurate mathematical PSS model is obtained. This mathematical model is used via the MPC method to obtain the predicted control quantity value quickly and accurately. The feasibility and effectiveness of this method are simulated and tested under various operating conditions. The results demonstrate that the proposed MPC method is feasible. The MPC method can reduce the speed oscillation amplitude and improve the system response speed more effectively than PID control.

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Stochastic Model Predictive Control for Urban Traffic Networks

Cited by 23 publications

References 38 publications

A Novel Electromagnetic Coupling Reactor Based Passive Power Filter with Dynamic Tunable Function

A Novel Electromagnetic Coupling Reactor Based Passive Power Filter with Dynamic Tunable Function

Designing the Controller-Based Urban Traffic Evaluation and Prediction Using Model Predictive Approach

A Machine Learning-Based Model Predictive Control Method for Pumped Storage Systems

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