Efficient Sky Luminance Model Parameters Optimization Scheme based on Improved Continuous Ant Colony Algorithm

2012 ◽  
Vol 4 (15) ◽  
pp. 470-479 ◽  
Author(s):  
Ping Guo ◽  
LingLing Bu ◽  
Lin Zhu ◽  
Ying He
Keyword(s):  
Ant Colony Algorithm ◽  
Parameters Optimization ◽  
Ant Colony ◽  
Model Parameters ◽  
Optimization Scheme

Optimization on NoC Mapping Based on Improved Ant Colony Algorithm

2014 ◽  
Vol 539 ◽  
pp. 280-285 ◽  
Author(s):  
Dong Li
Keyword(s):  
Power Consumption ◽  
Ant Colony Algorithm ◽  
Simulation Experiment ◽  
Local Optimization ◽  
Ant Colony ◽  
Optimal Solutions ◽  
Optimization Scheme ◽  
Tabu List ◽  
Mapping Algorithm ◽  
Improved Ant Colony Algorithm

Traditional ant colony mapping algorithm not only has big power consumption, but also is easy to be trapped into local optimization on NoC mapping, for which the paper proposes an optimization scheme based on improved ant colony algorithm. Firstly, the parameters are for initialization operation. Secondly, tabu list is used to solve them, and the solutions are for local optimization of optimal solutions by using 2-opt algorithm. Lastly, pheromone rules are updated. Simulation experiment indicates that compared with traditional ant colony mapping algorithm, NoC mapping optimization scheme based on improved ant colony algorithm not only has better performance on mapping power consumption, but also is not easy to be trapped into local optimization.

Ant Colony Algorithm Application In Glass Fiber Textile Machine Parameter Tuning

2012 ◽  
Vol 462 ◽  
pp. 71-76 ◽  
Author(s):  
Li Hong Zhang ◽  
Shu Qian Chen ◽  
Gui Zhi Bai
Keyword(s):  
Glass Fiber ◽  
Pid Control ◽  
Ant Colony Algorithm ◽  
Control Process ◽  
Parameter Tuning ◽  
Integral Function ◽  
Parameters Optimization ◽  
Ant Colony ◽  
Control Parameters ◽  
Optimization Strategy

In glass fiber textile process, non-axis volume cloth drive motor with glass fabric volume increases, increasing the pressure on the drive shaft, moreover, because of cloth non-axis volume makes the pressure in the process of change is evident, that causes the motor load changing constantly, the traditional PID control system controller cannot timely tracking response. In order to solve the problem which the control parameters optimizes, improves the system performance, proposed a new Ant colony algorithm PID parameters optimization strategy, this solution can combine characteristics that Ant colony algorithm can fast find the most superior parameter solution stably and PID can precise adjustment. In the control process, taken the PID parameters as a colony of ants, used to control the absolute error integral function as the optimization objective, dynamically adjust the PID control parameters in the control process, so as to realize the PID parameters on-line tuning.

Coordinated Ramp Metering Based on Ant Colony Optimization

2011 ◽  
Vol 97-98 ◽  
pp. 990-993
Author(s):  
Xin Rong Liang ◽  
Jian Xiong
Keyword(s):  
Control System ◽  
Ant Colony Optimization ◽  
Traffic Flow ◽  
Ant Colony Algorithm ◽  
Ant Colony ◽  
Macroscopic Model ◽  
Traffic Density ◽  
Model Parameters ◽  
Ramp Control ◽  
Control Layer

Hierarchy control strategy and ant colony optimization are proposed for coordinated ramp control. The macroscopic model to describe the evolution of freeway traffic flow is firstly established. Then the coordinated ramp control system is designed. There are two layers in this coordinated control system: the coordination control layer to select traffic models, to adjust the model parameters, and to determine the desired traffic density in each freeway section according to the current traffic status; and the direct control layer to keep the actual values of state variables in the vicinity of the desired state points via PI controllers. Ant colony algorithm is used to find the optimal PI control parameters. Simulation results show that the control system is of good performance. It can eliminate traffic jams, maintain traffic flow stability, and make vehicles travel more efficiently and safely.

Ant Colony Algorithm Application in Water Treatment Control System Parameter Tuning

2012 ◽  
Vol 433-440 ◽  
pp. 4354-4360
Author(s):  
Shu Qian Chen ◽  
Li Hong Zhang
Keyword(s):  
Control System ◽  
Water Treatment ◽  
Pid Control ◽  
Ant Colony Algorithm ◽  
Thermal Power ◽  
Control Process ◽  
Parameters Optimization ◽  
Ant Colony ◽  
Control Parameters ◽  
Treatment Control

In Thermal Power Generation and heating Water Treatment process, duo to the water supply pipeline pressure and flow changes, the traditional PID control system controller cannot the prompt track response, PH value of water changes in a larger range, increased damage to the boiler pipes. In order to solve the problem which the control parameters optimizes, improves the system performance, proposed a new Ant colony algorithm PID parameters optimization strategy, this solution can combine characteristics that Ant colony algorithm can fast find the most superior parameter solution stably and PID can precise adjustment. In the control process, taken the PID parameters as a colony of ants, used to control the absolute error integral function as the optimization objective, dynamically adjust the PID control parameters in the control process, so as to realize the PID parameters on-line tuning, to improve real-time of the water treatment control system, improved the stability of the system, and achieve a better control effect.

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