scholarly journals Conflicting Multi-Objective Compatible Optimization Control

10.5772/8050 ◽  
2010 ◽  
Author(s):  
Lihong Xu ◽  
Qingsong Hu ◽  
Haigen Hu ◽  
Erik Goodm
Keyword(s):  
Multi Objective ◽  
Optimization Control

Urban Oversaturated Traffic Network Control Based on Preference Multi-Objective Compatible Optimization Control

2011 ◽  
Vol 317-319 ◽  
pp. 1373-1384 ◽  
Author(s):  
Juan Chen ◽  
Chang Liang Yuan
Keyword(s):  
Control Problem ◽  
Control Algorithm ◽  
Control Method ◽  
Network Control ◽  
Feasible Region ◽  
Traffic Network ◽  
Total Delay ◽  
Multi Objective ◽  
Optimization Control ◽  
Objective Control

To solve the traffic congestion control problem on oversaturated network, the total delay is classified into two parts: the feeding delay and the non-feeding delay, and the control problem is formulated as a conflicted multi-objective control problem. The simultaneous control of multiple objectives is different from single objective control in that there is no unique solution to multi-objective control problems(MOPs). Multi-objective control usually involves many conflicting and incompatible objectives, therefore, a set of optimal trade-off solutions known as the Pareto-optimal solutions is required. Based on this background, a modified compatible control algorithm(MOCC) hunting for suboptimal and feasible region as the control aim rather than precise optimal point is proposed in this paper to solve the conflicted oversaturated traffic network control problem. Since it is impossible to avoid the inaccurate system model and input disturbance, the controller of the proposed multi-objective compatible control strategy is designed based on feedback control structure. Besides, considering the difference between control problem and optimization problem, user's preference are incorporated into multi-objective compatible control algorithm to guide the search direction. The proposed preference based compatible optimization control algorithm(PMOCC) is used to solve the oversaturated traffic network control problem in a core area of eleven junctions under the simulation environment. It is proved that the proposed compatible optimization control algorithm can handle the oversaturated traffic network control problem effectively than the fixed time control method.

scholarly journals The multi-objective optimization of tunneling boring machine control based on geological conditions identification

2020 ◽  
Vol 1 (1) ◽  
pp. 87-105
Author(s):  
Hongyuan Wang ◽  
Jingcheng Wang
Keyword(s):  
Objective Function ◽  
Nearest Neighbor ◽  
Tunnel Boring Machine ◽  
Geological Condition ◽  
Content Type ◽  
Multi Objective ◽  
Tunnel Boring ◽  
Geological Conditions ◽  
Optimization Control ◽  
Accuracy Of Prediction

PurposeThe purpose of this paper aims to design an optimization control for tunnel boring machine (TBM) based on geological identification. For unknown geological condition, the authors need to identify them before further optimization. For fully considering multiple crucial performance of TBM, the authors establish an optimization problem for TBM so that it can be adapted to varying geology. That is, TBM can operate optimally under corresponding geology, which is called geology-adaptability.Design/methodology/approachThis paper adopted k-nearest neighbor (KNN) algorithm with modification to identify geological conditions. The modification includes adjustment of weights in voting procedure and similarity distance measurement, which at suitable for engineering and enhance accuracy of prediction. The authors also design several key performances of TBM during operation, and built a multi-objective function. Further, the multi-objective function has been transformed into a single objective function by weighted-combination. The reformulated optimization was solved by genetic algorithm in the end.FindingsThis paper provides a support for decision-making in TBM control. Through proposed optimization control, the advance speed of TBM has been enhanced dramatically in each geological condition, compared with the results before optimizing. Meanwhile, other performances are acceptable and the method is verified by in situ data.Originality/valueThis paper fulfills an optimization control of TBM considering several key performances during excavating. The optimization is conducted under different geological conditions so that TBM has geological-adaptability.

Multi-objective optimization control method for multi-user multi-service access in heterogeneous wireless networks

2019 ◽  
Vol 34 (7) ◽  
pp. 708-715
Author(s):  
董晓庆 DONG Xiao-qing ◽  
程良伦 CHENG Liang-lun ◽  
陈洪财 CHEN Hong-cai ◽  
郑耿忠 ZHENG Geng-zhong ◽  
谢森林 XIE Sen-lin
Keyword(s):  
Wireless Networks ◽  
Control Method ◽  
Heterogeneous Wireless Networks ◽  
Service Access ◽  
Multi Objective Optimization ◽  
Multi Objective ◽  
Optimization Control

Determination of Multi-Objective Optimization Control Variable Domain Value in Coordinated Control System of Coal-Fired Unit

2011 ◽  
Vol 282-283 ◽  
pp. 726-730
Author(s):  
Jun Jie Gu ◽  
Zhi Yang ◽  
Yan Ling Ren
Keyword(s):  
Control System ◽  
Fitness Function ◽  
Control Variable ◽  
Physical Significance ◽  
Multi Objective Optimization ◽  
Multi Objective ◽  
Control Value ◽  
Optimization Control ◽  
System Variables

The accuracy of the variables variation scope in fitness function of the multi-objective optimization have an important influence to multi-objective optimization results. Take a 300 MW coal-fired unit as an example, according to the system mechanism builds a boiler-turbine dynamic model. And put forward a method, in this paper, which is using the iteration way and observing its physical significance to determine control system variables scope. The simplified model uses fuel value, turbine value and feedwater value as the inputs, and uses power, feedwater flow and absorbed heat of water wall as the outputs, to get the boundary of the pressure and the control value of the inputs during 50%-100% load.

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