Application Research of PID Control Optimized by GBLB-PSO in HVAC System

2011 ◽  
Vol 219-220 ◽  
pp. 1325-1328 ◽  
Author(s):  
Qi Liu ◽  
Yuan Dong Du
Keyword(s):  
Pid Control ◽  
Hot Spot ◽  
Pso Algorithm ◽  
Research Field ◽  
Good Effect ◽  
Hvac System ◽  
Optimization Strategy ◽  
Control Effect ◽  
Method Performance ◽  
Parameter Values

Parameter optimization of PID control is always a hot spot in the research field of control, and control effect of PID depends on the parameter values: proportion, integral and differentiation. This paper puts forward a global best and local best PSO algorithm, which is an optimization strategy of PID, the result of this method making the system have small overshoot and short adjusting time. The optimization scheme of this paper will be used in the control of HVAC system. through simulation, it is shown that there is good effect, such as non-overshoot and short adjusting time. Compared with the traditional method, performance of this algorithm is well improved and optimized objective function is decreasing.

The Optimization for PID Controller Parameters Based on Genetic Algorithm

2014 ◽  
Vol 513-517 ◽  
pp. 4102-4105 ◽  
Author(s):  
Xiang Jie Niu
Keyword(s):  
Genetic Algorithm ◽  
Pid Control ◽  
Pid Controller ◽  
Integral Function ◽  
Research Field ◽  
System Stability ◽  
Control Parameters ◽  
Optimization Strategy ◽  
Control Effect ◽  
Operation Speed

as an important research field of automatic control problems, PID parameter optimization's control effect depends on the proportional, integral and derivative values. Using trial and error testing to manually realize optimization PID parameters, the traditional ways are often time-consuming and difficult to meet the requirements of real-time control. In order to solve the problems and improve system performance, the paper proposes a PID parameter optimization strategy based on genetic algorithm. The paper establishes the PID controller parameter model through genetic algorithm, uses the PID parameters as individuals in genetic algorithm during the control process, and takes the integral function of absolute error control time as the optimization object to dynamically adjust the three PID control parameters, thus realize online optimization for PID control parameters. Simulation results show that the introduction of genetic algorithms for PID control system improves the dynamic performance, enhance system stability and operation speed, and get better control effect.

scholarly journals Position Control of Ultrasonic Motor Using IMC-PID Combined with Tribes Type NN Algorithm

2011 ◽  
Vol 2-3 ◽  
pp. 12-17
Author(s):  
Sheng Lin Mu ◽  
Kanya Tanaka
Keyword(s):  
Neural Network ◽  
Particle Swarm Optimization ◽  
Pid Control ◽  
Position Control ◽  
Back Propagation ◽  
Particle Swarm ◽  
Pso Algorithm ◽  
Ultrasonic Motor ◽  
Swarm Optimization

In this paper, we propose a novel scheme of IMC-PID control combined with a tribes type neural network (NN) for the position control of ultrasonic motor (USM). In this method, the NN controller is employed for tuning the parameter in IMC-PID control. The weights of NN are designed to be updated by the tribes-particle swarm optimization (PSO) algorithm. This method makes it possible to compensate for the characteristic changes and nonlinearity of USM. The parameter-free tribes-PSO requires no information about the USM beforehand; hence its application overcomes the problem of Jacobian estimation in the conventional back propagation (BP) method of NN. The effectiveness of the proposed method is confirmed by experiments.

Energy Efficiency and Tracking Performance Evaluation for Dual-Mode Model Predictive Control of HVAC Systems

2018 ◽  
Vol 10 (4) ◽  
Author(s):  
Zicheng Cai ◽  
Asad A. Ul Haq ◽  
Michael E. Cholette ◽  
Dragan Djurdjanovic
Keyword(s):  
Energy Consumption ◽  
Predictive Control ◽  
Pid Control ◽  
Control Structure ◽  
Tracking Performance ◽  
System Control ◽  
Hvac System ◽  
Dual Mode ◽  
Different Types ◽  
Predictive Controller

This paper presents evaluation of the energy consumption and tracking performance associated with the use of a recently introduced dual-mode model predictive controller (DMMPC) for control of a heating, ventilation, and air conditioning (HVAC) system. The study was conducted using detailed simulations of an HVAC system, which included a multizone air loop, a water loop, and a chiller. Energy consumption and tracking performance are computed from the simulations and evaluated in the presence of different types and magnitudes of noise and disturbances. Performance of the DMMPC is compared with a baseline proportional-integral-derivative (PID) control structure commonly used for HVAC system control, and this comparison showed clear and consistent superiority of the DMMPC.

scholarly journals Comparison of cascade P-PI controller tuning methods for PMDC motor based on intelligence techniques

2022 ◽  
Vol 12 (1) ◽  
pp. 1
Author(s):  
Kareem Ghazi Abdulhussein ◽  
Naseer Majeed Yasin ◽  
Ihsan Jabbar Hasan
Keyword(s):  
Classical Method ◽  
Pso Algorithm ◽  
Pi Controller ◽  
Load Effect ◽  
Ga Algorithm ◽  
Tuning Methods ◽  
Parameter Values ◽  
Permanent Magnet Dc Motor ◽  
Tracking Trajectory ◽  
Best Parameters

In this paper, there are two contributions: The first contribution is to design a robust cascade P-PI controller to control the speed and position of the permanent magnet DC motor (PMDC). The second contribution is to use three methods to tuning the parameter values for this cascade controller by making a comparison between them to obtain the best results to ensure accurate tracking trajectory on the axis to reach the desired position. These methods are the classical method (CM) and it requires some assumptions, the genetic algorithm (GA), and the particle swarm optimization algorithm (PSO). The simulation results show the system becomes unstable after applying the load when using the classical method because it assumes cancellation of the load effect. Also, an overshoot of about 3.763% is observed, and a deviation from the desired position of about 12.03 degrees is observed when using the GA algorithm, while no deviation or overshoot is observed when using the PSO algorithm. Therefore, the PSO algorithm has superiority as compared to the other two methods in improving the performance of the PMDC motor by extracting the best parameters for the cascade P-PI controller to reach the desired position at a regular speed.

scholarly journals A Self-Adaptive Discrete PSO Algorithm with Heterogeneous Parameter Values for Dynamic TSP

Entropy ◽  
2019 ◽  
Vol 21 (8) ◽  
pp. 738 ◽  
Author(s):  
Łukasz Strąk ◽  
Rafał Skinderowicz ◽  
Urszula Boryczka ◽  
Arkadiusz Nowakowski
Keyword(s):  
Computation Time ◽  
Pso Algorithm ◽  
Discrete Particle Swarm Optimization ◽  
Swarm Optimization ◽  
Discrete Particle ◽  
Discrete Pso ◽  
Parameter Values ◽  
Positive Effect ◽  
Uniform Parameter

This paper presents a discrete particle swarm optimization (DPSO) algorithm with heterogeneous (non-uniform) parameter values for solving the dynamic traveling salesman problem (DTSP). The DTSP can be modeled as a sequence of static sub-problems, each of which is an instance of the TSP. In the proposed DPSO algorithm, the information gathered while solving a sub-problem is retained in the form of a pheromone matrix and used by the algorithm while solving the next sub-problem. We present a method for automatically setting the values of the key DPSO parameters (except for the parameters directly related to the computation time and size of a problem).We show that the diversity of parameters values has a positive effect on the quality of the generated results. Furthermore, the population in the proposed algorithm has a higher level of entropy. We compare the performance of the proposed heterogeneous DPSO with two ant colony optimization (ACO) algorithms. The proposed algorithm outperforms the base DPSO and is competitive with the ACO.

Boiler Steam Pressure Control System Based on Fuzzy Control

2012 ◽  
Vol 462 ◽  
pp. 732-737
Author(s):  
Yi Heng Zhou ◽  
Long Yue Yang ◽  
Hai Lin Pu ◽  
Zi Yu Zhao ◽  
Fei Liu ◽  
...  
Keyword(s):  
Control System ◽  
Pid Control ◽  
Good Control ◽  
Pressure Control ◽  
Steam Pressure ◽  
Cascade Control ◽  
Normal Operation ◽  
Control Effect ◽  
Pressure Control System ◽  
Fuzzy Adaptive

Industrial boiler steam pressure is an important measure of boiler normal operation. Since there is delay and inertial part, single-loop PID control is difficult to achieve good dynamic characteristics. By analyzing the characteristics of the steam pressure controlled object, this paper presents a fuzzy adaptive PID control based on the cascade control system. Finally, in order to analyze the effect of the control system, mathematical model was constructed by MATLAB simulation to compare fuzzy adaptive PID cascade control with conventional PID control. The results prove that the former has a good control effect.

Coal Mine Safety Management Researching Situation Analysis Based on Knowledge Map

2014 ◽  
Vol 962-965 ◽  
pp. 1003-1009
Author(s):  
Hong Xia Li ◽  
Long Zhao Zhao
Keyword(s):  
Safety Management ◽  
Hot Spot ◽  
Basic Research ◽  
Development Trend ◽  
Research Field ◽  
Mine Safety ◽  
Published Data ◽  
Knowledge Map ◽  
Knowledge Mapping ◽  
Classical Literature

In order to understand the characteristics and law of development of coal research in the field of safety management, the papers published data from 1993--2013 based on Web of Science database and the Java platform development CitespaceIII visualization software for scientific knowledge map drawing is used. Through the knowledge map visualization analysis, it shows the origin of the research of international coal safety management and foundation of knowledge, and its basic and frontier disciplines. The results show that: through the visual keywords co-occurrence knowledge mapping analysis, high frequency keywords and high degree of heart keyword ranked in the top 10. It also shows the hot spot area and the development trend in the research field of coal safety management; from the literature co-citation results, classical literature and knowledge of basic research on coal safety management field, it plays an important role in the development process of the research in the field of visualization; through the journal co-citation analysis of knowledge map, it gets higher yield and literature journal, such as SAFETY SCI, COAL SCI TECHNOLOGY, CHINA COAL and the like, which shows that in the study of coal safety management field quantity of periodicals, China is the first, which explains China's leading position in the field of safety management of coal.

Boiler Combustion Control System Optimization Strategy

2013 ◽  
Vol 397-400 ◽  
pp. 1064-1068
Author(s):  
Yong Zhang ◽  
Yuan Yao ◽  
Ting Luan
Keyword(s):  
Control System ◽  
Pid Control ◽  
Dynamic Performance ◽  
Control Program ◽  
System Optimization ◽  
Optimization Strategy ◽  
Steam Quality ◽  
Control Scheme ◽  
Better Than ◽  
Fuzzy Adaptive

Optimal control of the boiler combustion system is related to the economy and stability of the entire production process. To the problem that the boiler main product steam quality and the safe operation of the boiler optimization control, the fuzzy adaptive algorithm combined with the traditional PID control in the DCS system is proposed. The method optimizes the control system parameters and improves the control program. The simulation results show that the control scheme is better than the traditional PID control, and has good dynamic performance and stability. Both the boiler outlet steam quality and the security operation of boiler are improved.

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