PSO-BASED PID CONTROLLER DESIGN FOR AN ENERGY CONVERSION SYSTEM USING COMPRESSED AIR

被引:6
作者
Atacak, Ismail [1 ]
Kucuk, Bayram [2 ]
机构
[1] Gazi Univ, Technol Fac, Comp Eng Dept, TR-06500 Ankara, Turkey
[2] Gazi Univ, Inst Informat, TR-06500 Ankara, Turkey
来源
TEHNICKI VJESNIK-TECHNICAL GAZETTE | 2017年 / 24卷 / 03期
关键词
compressed air-based energy conversion; optimal PID controller; particle swarm optimization algorithm; pneumatic motor; PARTICLE SWARM OPTIMIZATION; POWER-SYSTEM; SPEED CONTROL; ALGORITHM; STORAGE; MOTOR; SIMULATION;
D O I
10.17559/TV-20150310170741
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
In this study, an optimal control algorithm is proposed to overcome low performance problems arising from the non-linear characteristics of pneumatic motor in compressed air-based energy conversion systems. The effectiveness of the proposed algorithm is tested on an energy conversion system which includes a compressor, a proportional valve, a pneumatic motor (PM), a permanent magnet direct current (PMDC) generator and a control card. The control function of the system is carried out by driving the proportional valve with the control signals which is obtained depending on the PMDC generator output voltage error. In this structure, an optimal proportional-integral-derivative (PID) controller which tunes on-line its own gain parameters by particle swarm optimization (PSO) algorithm according to the operating conditions of the system used. In order to observe the effects of PSO-based PID controller on the system performance, the energy conversion system is also controlled by a discrete time PID controller. The experimental results show that PSO-based PID controller provides more robust control performance than discrete time PID controller under various operating conditions.
引用
收藏
页码:671 / 679
页数:9
相关论文
共 35 条
[1]  
[Anonymous], WORLD ACAD SCI ENG T
[2]  
Bouarroudj N., 2015, CONTROL ENG APPL INF, V17, P41
[3]   ACO-BASED LOAD BALANCING SCHEME FOR MANETS [J].
Celik, Fatih .
TEHNICKI VJESNIK-TECHNICAL GAZETTE, 2015, 22 (05) :1165-1169
[4]   PID Controller Design for MIMO Processes Using Improved Particle Swarm Optimization [J].
Chang, Wei-Der ;
Chen, Chih-Yung .
CIRCUITS SYSTEMS AND SIGNAL PROCESSING, 2014, 33 (05) :1473-1490
[5]   Application of an improved PSO algorithm to optimal tuning of PID gains for water turbine governor [J].
Fang, Hongqing ;
Chen, Long ;
Shen, Zuyi .
ENERGY CONVERSION AND MANAGEMENT, 2011, 52 (04) :1763-1770
[6]   Nonlinear Discontinuous Dynamics Averaging and PWM-Based Sliding Control of Solenoid-Valve Pneumatic Actuators [J].
Hodgson, Sean ;
Tavakoli, Mahdi ;
Minh Tu Pham ;
Leleve, Arnaud .
IEEE-ASME TRANSACTIONS ON MECHATRONICS, 2015, 20 (02) :876-888
[7]  
Hwang Y. R., 2009, IEEE INT C IND TECHN, P1, DOI [10.1109/icit.2009.4939588, DOI 10.1109/ICIT.2009.4939588]
[8]   Optimal PID control of a brushless DC motor using PSO and BF techniques [J].
Ibrahim, H. E. A. ;
Hassan, F. N. ;
Shomer, Anas O. .
AIN SHAMS ENGINEERING JOURNAL, 2014, 5 (02) :391-398
[9]   Damping of power system oscillations by tuning of PSS and SVC using particle swarm optimization [J].
Karuppiah, Natarajan ;
Malathi, Veluchamy .
Tehnicki Vjesnik, 2016, 23 (01) :221-227
[10]   Dynamic simulation of air storagebased gas turbine plants [J].
Khaitan, Siddhartha Kumar ;
Raju, Mandhapati .
INTERNATIONAL JOURNAL OF ENERGY RESEARCH, 2013, 37 (06) :558-569