Dynamic traffic light optimization and Control System using model-predictive control method

2016 ◽  
Author(s):  
You-Ren Chen ◽  
Keng-Pin Chen ◽  
Pao-Ann Hsiungy
Keyword(s):  
Control System ◽  
Model Predictive Control ◽  
Predictive Control ◽  
Control Method ◽  
Dynamic Traffic ◽  
Traffic Light ◽  
Optimization And Control ◽  
And Control

scholarly journals Self-Triggered Model Predictive Control for Linear Systems Based on Transmission of Control Input Sequences

2016 ◽  
Vol 2016 ◽  
pp. 1-7 ◽  
Author(s):  
Koichi Kobayashi
Keyword(s):  
Control System ◽  
Model Predictive Control ◽  
Linear Systems ◽  
Communication Networks ◽  
Predictive Control ◽  
Control Method ◽  
Input Sequence ◽  
Networked Control System ◽  
Control Input ◽  
Sampled Data

A networked control system (NCS) is a control system where components such as plants and controllers are connected through communication networks. Self-triggered control is well known as one of the control methods in NCSs and is a control method that for sampled-data control systems both the control input and the aperiodic sampling interval (i.e., the transmission interval) are computed simultaneously. In this paper, a self-triggered model predictive control (MPC) method for discrete-time linear systems with disturbances is proposed. In the conventional MPC method, the first one of the control input sequence obtained by solving the finite-time optimal control problem is sent and applied to the plant. In the proposed method, the first some elements of the control input sequence obtained are sent to the plant, and each element is sequentially applied to the plant. The number of elements is decided according to the effect of disturbances. In other words, transmission intervals can be controlled. Finally, the effectiveness of the proposed method is shown by numerical simulations.

scholarly journals Dual Quaternion Based Close Proximity Operation for In-Orbit Assembly via Model Predictive Control

2021 ◽  
Vol 2021 ◽  
pp. 1-14
Author(s):  
Chuqi Sun ◽  
Yan Xiao ◽  
Zhaowei Sun ◽  
Dong Ye
Keyword(s):  
Control System ◽  
Model Predictive Control ◽  
Predictive Control ◽  
Coupling Effect ◽  
Suboptimal Control ◽  
Dual Quaternion ◽  
Close Proximity ◽  
The Stability ◽  
Six Degree Of Freedom ◽  
And Control

This paper studies the problem of guidance and control for autonomous in-orbit assembly. A six-degree-of-freedom (6-DOF) motion control for in-orbit assembly close proximity operation between a service satellite and a target satellite is addressed in detail. The dynamics based on dual quaternion are introduced to dispose the coupling effect between translation and rotation in a succinct frame, in which relevant perturbation and disturbance are involved. With the consideration of economical principle for fuel consume, a generic control system based on model predictive control (MPC) is then designed to generate a suboptimal control sequence for rendezvous trajectory considering actuator output saturation. The stability and robustness issues of the MPC-based control system are analyzed and proved. Numerical simulations are presented to demonstrate the effectiveness and robustness of the proposed control scheme, while additional comparisons for diverse horizons of the MPC are further conducted.

scholarly journals Desired Terminal State Concept in Model Predictive Control: A Case Study

2019 ◽  
Vol 2019 ◽  
pp. 1-7
Author(s):  
František Dušek ◽  
Daniel Honc
Keyword(s):  
Model Predictive Control ◽  
Predictive Control ◽  
Control Method ◽  
Optimization Methods ◽  
Terminal State ◽  
Online Optimization ◽  
Transient Behaviour ◽  
The Stability ◽  
Transport Problems ◽  
And Control

The paper deals with an online optimization control method for dynamical processes called Model Predictive Control (MPC). It is a popular control method in industry and frequently treated in academic areas as well. The standard predictive controllers usually do not guarantee stability especially for the case of short horizons and large control error penalization. Terminal state is one way to ensure stability or at least increase the controller robustness. In the paper, deviation of the predicted terminal state from the desired terminal state is considered as one term of the cost function. Effect of the stability and control quality is demonstrated in the simulated experiments. The application area for online optimization methods is very broad including various logistics and transport problems. If the dynamics of the controlled processes cannot be neglected, the optimization problem must be solved not only for steady state but also for transient behaviour, e.g., by MPC.

A Novel Optimization and Control Method for Signalized Traffic Network

2011 ◽  
Vol 403-408 ◽  
pp. 3229-3234
Author(s):  
Xiao Feng Chen ◽  
Zhong Ke Shi
Keyword(s):  
Dynamic Optimization ◽  
Control Method ◽  
Control Period ◽  
Optimization Method ◽  
Dynamic Traffic ◽  
Arterial Network ◽  
Real Coded Genetic Algorithm ◽  
Optimization And Control ◽  
Multi Phase ◽  
And Control

For the dynamic optimization and control problem of the signalized arterial network in urban, a dynamic traffic flow model based on multi-phase control is firstly formulated, in which the total number of the retained vehicles through the arterial during the control period is adopted as the optimization objective and the green times and offsets as the control variables. Then a hybrid optimization method based on real-coded genetic algorithm and local search technique is designed to solve the optimization problem. For examining the validity of the optimization and control method proposed, it is applied to a case study with dynamic traffic demands and a large number of simulations show that the dynamic optimization and control method proposed in this paper can work well for the signalized arterial network.

Control of coagulation process by dual wavelength article analyzer

1997 ◽  
Vol 36 (4) ◽  
pp. 135-142 ◽  
Author(s):  
Norihito Tambo ◽  
Yoshihiko Matsui ◽  
Ken-ichi Kurotani ◽  
Masakazu Kubota ◽  
Hirohide Akiyama ◽  
...  
Keyword(s):  
Water Quality ◽  
Control System ◽  
Predictive Control ◽  
Control Method ◽  
Feedforward Control ◽  
Raw Water ◽  
Floc Size ◽  
Coagulation Process ◽  
Series Of Experiments ◽  
Size Data

A coagulation process for water purification plants mainly uses feedforward control based on raw water quality and empirical data and requires operator's help. We developed a new floc sensor for measuring floc size in a flush mixer to be used for floc control. A control system using model predictive control was developed on the floc size data. A series of experiments was performed to confirm controllability of settled water quality by controlling flush mixer floc size. An automatic control with feedback from the coagulation process was evaluated as practical and reliable. Finally this new control method was applied for actual plant and evaluated as practical.

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