Study on Optimization Control Method of the Pickling Process

2013 ◽  
Vol 397-400 ◽  
pp. 1326-1330
Author(s):  
Da Kuo He ◽  
Wei Qin ◽  
Tong Shan Liu ◽  
Qing Yun Yuan
Keyword(s):  
Prediction Model ◽  
Process Optimization ◽  
Control Method ◽  
Model Error ◽  
Operating Variables ◽  
Decision Variables ◽  
Optimization Control ◽  
Pickling Process ◽  
Simulation Results ◽  
Process Prediction

The pickling process is the important metallurgical production process. Based on pickling process prediction model, considering the max economic efficiency as the optimized objective, and seeing the operating variables as the decision variables, this paper establishes the pickling process optimization model and makes the optimized calculation to get the value of each key control circuit. At the same time, considering the pickling process prediction model error brings the uncertainty to the optimization results, based on iterative optimization control thoughts do pickling process optimization control, the simulation results verify the effectiveness of the method.

scholarly journals A Novel Graph and Safety Potential Field Theory-Based Vehicle Platoon Formation and Optimization Method

2021 ◽  
Vol 11 (3) ◽  
pp. 958
Author(s):  
Linheng Li ◽  
Jing Gan ◽  
Xu Qu ◽  
Peipei Mao ◽  
Ziwei Yi ◽  
...  
Keyword(s):  
Traffic Safety ◽  
Potential Field ◽  
Control Method ◽  
Control Strategies ◽  
Optimization Methods ◽  
Optimization Method ◽  
Optimization Strategy ◽  
Transmission Method ◽  
Optimization Control ◽  
Simulation Results

Platooning is considered to be a very effective method for improving traffic efficiency, traffic safety and fuel economy under the connected and automated environment. The prerequisite for realizing these advantages is how to form a platoon without any collisions and how to maintain and optimize the car-following behavior after platoon formation. However, most of the existing studies focus on the platoon configuration and information transmission method, while only a few attempt to address the issue of platoon formation and optimization methods. To this end, this study proposes a novel platoon formation and optimization model combining graph theory and safety potential field (G-SPF) theory for connected and automated vehicles (CAVs) under different vehicle distributions. Compared to previous studies, we innovatively incorporate the concept of the safety potential field to better describe the actual driving risk of vehicles and ensure their absolute safety. A four-step platoon formation and optimization strategy is developed to achieve platoon preliminary formation and platoon driving optimization control. Three traffic scenarios with different CAVs distributions are designed to verify the effectiveness of our proposed platoon formation method based on G-SPF theory, and the simulation results indicate that a collision-free platoon can be formed in a short time. Additionally, the G-SPF-based platoon driving optimization control method is demonstrated by comparing it with two typical control strategies. Compared with the constant spacing and constant time headway control strategies, the simulation results show that our proposed method can improve the traffic capacity by approximately 48.8% and 26.6%, respectively.

Coordinated optimization control of shield machine based on dynamic fuzzy neural network direct inverse control

2020 ◽  
pp. 014233122098027
Author(s):  
Xuanyu Liu ◽  
Wentao Wang ◽  
Yudong Wang ◽  
Cheng Shao ◽  
Qiumei Cong
Keyword(s):  
Fuzzy Neural Network ◽  
Control Method ◽  
Earth Pressure ◽  
Screw Conveyor ◽  
Inverse Control ◽  
The Earth ◽  
Coordinated Optimization ◽  
Optimization Control ◽  
Fuzzy Neural ◽  
Shield Machine

During shield machine tunneling, the earth pressure in the sealed cabin must be kept balanced to ensure construction safety. As there is a strong nonlinear coupling relationship among the tunneling parameters, it is difficult to control the balance between the amount of soil entered and the amount discharged in the sealed cabin. So, the control effect of excavation face stability is poor. For this purpose, a coordinated optimization control method of shield machine based on dynamic fuzzy neural network (D-FNN) direct inverse control is proposed. The cutter head torque, advance speed, thrust, screw conveyor speed and earth pressure difference in the sealed cabin are selected as inputs, and the D-FNN control model of the control parameters is established, whose output are screw conveyor speed and advance speed at the next moment. The error reduction rate method is introduced to trim and identify the network structure to optimize the control model. On this basis, an optimal control system for earth pressure balance (EPB) of shield machine is established based on the direct inverse control method. The simulation results show that the method can optimize the control parameters coordinately according to the changes of the construction environment, effectively reduce the earth pressure fluctuations during shield tunneling, and can better control the stability of the excavation surface.

Optimization control method for office lighting

2020 ◽  
Author(s):  
JianMin MA ◽  
Dong WEI ◽  
Shuqi JING ◽  
Qi CHEN ◽  
XU WANG ◽  
...  
Keyword(s):  
Control Method ◽  
Optimization Control ◽  
Office Lighting

Intelligent Information of TS Fuzzy PID Control System of BLDCM

2013 ◽  
Vol 846-847 ◽  
pp. 313-316 ◽  
Author(s):  
Xiao Yun Zhang
Keyword(s):  
Control System ◽  
Dynamic Model ◽  
Pid Control ◽  
Control Method ◽  
Design Method ◽  
Fuzzy Pid ◽  
Fuzzy Pid Control ◽  
Control Precision ◽  
Simulation Results ◽  
Intelligent Information

This paper presented a new method based on the Fuzzy self - adaptive PID for BLDCM. This method overcomes some defects of the traditional PID control. Such as lower control precision and worse anti - jamming performance. It dynamic model of BLDCM was built, and then design method for TS fuzzy PID model is given, At last, it compared simulation results of PID control method with TS Fuzzy PID control method. The results show that the TS Fuzzy PID control method has more excellent dynamic antistatic performances, as well as anti-jamming performance. The experiment shows that TS fuzzy PID control has the stronger adaptability robustness and transplant.

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.

Study on Direct Torque Control Applied in the Electrical Propulsion Ship

2011 ◽  
Vol 354-355 ◽  
pp. 1252-1256
Author(s):  
You Tao Zhao ◽  
Yan Cheng Liu ◽  
Jun Jie Ren
Keyword(s):  
Electric Propulsion ◽  
Control Method ◽  
Direct Torque Control ◽  
Torque Control ◽  
Regulation System ◽  
Propulsion Systems ◽  
Speed Regulation ◽  
Imple Mentation ◽  
Electrical Propulsion ◽  
Simulation Results

With the development of AC (alternating current )technique, larger power PMSM ( permanent m- agnet synchronous motor ) has been applied in the marine electric propulsion systems. In this paper the imple- mentation of the DTC (direct torque control) systems for a variable-speed 4088kW PMSM in ship electric propulsion systems has been studied. A novel control method using SVPWM (space vector pulse width mo- dulation) was proposed and a SVPWM module was designed. Then a DTC – SVPWM simulation model of PMSM with the load of propeller was found. The simulation results shows that the variable frequency speed regulation system have good response performance in the process of the motor start or speedup and through comparing the simulation results with the experiment data of the PMSM, the validity of the model is verified.

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