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Procedia Engineering
Procedia Engineering 00 (2011) 000–000 Procedia Engineering 15 (2011) 969 – 973 www.elsevier.com/locate/procedia
Advanced in Control Engineeringand Information Science
Fuzzy Sliding-Mode Variable Structure Control for Fan Filter Units’ Motor Speed Regulation System Yiwang Wang ∗a,Jia Songa,Bo Zhanga a
Suzhou Vocational University,No.1158 Wuzhong Road,Suzhou 215104,China
Abstract
Aiming at the characteristics of nonlinear, time variant and complex multivariable of fan filter units’(FFU) motor speed regulation process control system. A fuzzy sliding mode variable structure control which combines advantages of sliding mode variable structure control is presented and designed for FFU motor speed regulation, to guarantee system control performance and robust stability.The experiment results showed that this proposed scheme can implement speed control, which effectively improve the system robustness and transient response. © 2011 Published by Elsevier Ltd. Open access under CC BY-NC-ND license. Selection and/or peer-review under responsibility of [CEIS 2011] Keywords: Fan filter unit(FFU); fuzzy control; sliding mode control;speed regulation;
1. Introduction With the development of clean technologies, the fan filter units(FFU) as a purification equipment have been widely used in industrial applications, e.g., electronics, pharmaceutical, food, biotechnology, medical, laboratory and other areas.The FFU is a combination of fan motor with high efficiency filter (HEPA / ULPA) air circulation and filtration equipment, which has the advantages of a low investment, rapid construction, economic operation , combination convenience, the process of change adaptability,
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1877-7058 © 2011 Published by Elsevier Ltd. Open access under CC BY-NC-ND license. doi:10.1016/j.proeng.2011.08.179
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Yiwang et al. / Procedia Engineering 15 (2011) 969 – 973 Yiwang WangWang ，et al/ Procedia Engineering 00 (2011) 000–000
ease of management, etc. The fan motor and its controller are the key components of FFU,the motor generally use a single-phase AC induction motor (SPIM). Due to the characteristics of serious nonlinear, time variant and complex multivariable of SPIM,so that its electro-magnetic relationship is hard to analyze. Therefore, to the FFU motor speed regulation system the control strategies are very important. The conventional FFU control methods such as proportional–integral–derivative(PID)-type or proportional–integral (PI)-type controllers are not easy accomplish this control task, which robustness are very weak,it is very difficult to obtain satisfactory control effect.The fuzzy sliding mode variable structure control,which combination the advantages of fuzzy control andsliding mode variable structure control, which has the advantage of a short adjustment time, anti-interference ability, robustness and good in the FFU motor speed regulation systems to achieve good control results. In this paper, a fuzzy sliding mode variable structure controller is designed for the SPIM speed regulation tracking control of a FFU fan motor system. Finally, the experiment results showed that this proposed scheme can implement speed control, and had more robustness and better performance than the traditional control strategies. 2. FFU motor and Control system structure FFU motor used a SPIM as the fan,the SPIM usually contain two types of capacitor-run single-phase inductor motor (CR-SPIM) and capacitor-start single-phase inductor motor (CS-SPIM).The CR-SPIM is commonly used in our daily life[2]. The advantages of this inductor motor are: cheap, reliable and longlasting.In this paper,the FFU system also use the CR-SPIM as fan motor,the structure schematic main three parts.That is main windinig, auxiliary winding and run capacitor.The speed of the CR-SPIM is directly proportional to the supply frequency and the number of poles of the motor.Since the number of poles is fixed by design, the best way to vary the speed of the induction motor is by varying the supply frequency[4].In this paper also use the variable frequency power supply to achieve the speed regulation control of the FFU’s fan motor. M a i n w i n d i n g A u x i l i a r y w i n d i n g R u n
L 1
c a p a c ito r
C
L 2
A C I n~p u t
Fig.1 The schematic structure of SPIM
In this paper,the proposed FFU motor speed regulation tracking control system block diagram is shown in Fig. 2,where includes the main circuit and control system circuit.In the main circuit the single phase AC input,and pass the filter circuit be rectified DC ouput,then singlephase bridge inverter variable frequency AC output and connecting to CS-SPIM,which accomplished the speed regulation of CS-SPIM. The output voltage and speed feedback compared to the reference voltage and speed input,and the difference as the fuzzy sliding variable structure control inputs, the controller output variable control the duty and period of SPWM signals, to adjust the output voltage and inverter frequency, then the control regulation SPIM A C In p u t output speed. C o n tr o l sy ste m C o n tr o l p o w e r s u p p ly
n re f+ n-
R e c tif ie r/f ilte r c ir c u its
S lid in g -m o d e v a r ia b le
o
V
+
s tr u c tu r e c o n tr o lle r
re f
-
V
SPW M m o d u la tio n
F u z z y c o n tr o lle r
o
V o lta g e / sp e ed fee d b a c k
Fig.2.The block diagram of the proposed control scheme
S in g le -p h a s e in v e r te r
S P IM
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Yiwang Wang et al./ Procedia / ProcediaEngineering Engineering0015(2011) (2011)000–000 969 – 973 Author name
3. Fuzzy Sliding-Mode Variable Structure Control for FFU motorSpeed Regulation System 3.1. Description of the control theory Sliding mode variable structure control strategy has been widely used to deal with nonlinear systems with both system parameter variations and external disturbances, especially in motor and AC driving control system. In essence, the sliding mode variable structure control is a special class of nonlinear control, which the control characteristics can force the system to certain properties under the provisions of the state along the trajectory for small amplitude, high frequency up and down movement. However, there exist several shortcomings, e.g. the inherent chattering of control effort and infinite convergent time, when using such a conventional SMC method into EV applications [3]. Fuzzy logic control technology is a kind of modern control theory in a high-level strategies and new technologies, as intelligent control an important branch, which has several advantages such as robustness, being model free, universal approximation theorem, and rule-based algorithm [4]. However, there are still problems, such as not high accuracy, a limited ability, easy to produce oscillation in the traditional fuzzy control [9]( [9] C.Elmas, O.Deperlioglu, H.Sayan: ' Adaptive Fuzzy Logic Controller for DC-DC Converters ', Expert Systems with Aplications, pp. 1541-1548.).To resolve these shortcomings or problems, many researchers have proposed fuzzy sliding mode variable structure control, which combined both advantages of traditional fuzzy control and sliding mode control, the sliding mode control system stability and fuzzy control regulation to weaken the chattering. 3.2. Design and Implementation of Fuzzy Sliding Mode Variable Structure Controller Fuzzy control rules to adjust the size of the control variables, to reduce the chattering of sliding mode control and meet the existence conditions of sliding motion. According to a large number of FFU motor controlled experiments collected data and theoretical analysis. Define the sliding mode switching function as follows: s=ke1+e2
(1)
Where k is a given constant. e1 is error between given input and output , e2 is change rate of the error. In the structure of fuzzy sliding mode controller, fuzzy control system use dual-input and single-output form, Two input variables are s and d,where s is the movement points’ distance between the sliding surfaces, d is the speed of closer to the sliding surfaces.One output variable is u. A rule base is a set of (IF-Then) rules, which contains a fuzzy logic quantification of the expert linguistic description of how to achieve good control.In this paper the control rule base of the fuzzy controller is given by: IF s is A and d is B THEN u is C
(2)
Where A is the linguistic variable s, B is the linguistic variable d and C is the linguistic variable u. Select the input and output linguistic variable A,B and C are divided into five fuzzy levels or subsets in this design,which are PB (Positive Big), PS (Positive Small), ZZ (Zero), NS(Negative Small), and NB (Negative Big). A defuzzification strategy is aimed at producing a nonfuzzy control action that best represent the possibility distribution of an inferred fuzzy control action. The interface method used is basic and simple and is developed from the minimum operation rule as a fuzzy implementation function. In the defuzzification, the method of center gravity is used. The control rules are formulated as shown in Table. 1. Table.1 Control rule table for fuzzy sliding-mode variable structure controller u
d
s N B
N S
ZZ
PS
PB
N B
N B
N B
N B
N S
N S
N S
N B
N S
N S
ZZ
PS
ZZ
N S
N S
ZZ
PS
PS
PS
N S
N S
PS
PS
PB
PB
N S
PS
PS
PB
PB
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Yiwang et al. / Procedia Engineering 15 (2011) 969 – 973 Yiwang WangWang ，et al/ Procedia Engineering 00 (2011) 000–000
4. Experimental results and analysis According to the adove analysis and design, control system used digital signal controller(DSC) dsPIC30F2010 as the control core, to achieve the FFU motor SPWM inverter full digital control, the main switching elements used Mitsubishi IPM Module.Experimental CS-SPIM parameters: working voltage AC220V, rated power 200W and rated speed 3000r/min. Numerical speed regulation control experiments have been carried out,and test the performance of designed control system.The experimental speed tracking response curve is provided,which as shown in Fig.3, From the experimental result shown in Fig.3, the favorable FFU motor speed regulation control can be achieved,which verified the theoretical correctness of the cotrol system design.
Fig.3.Experimental result of speed response
Yiwang Wang et al./ Procedia / ProcediaEngineering Engineering0015(2011) (2011)000–000 969 – 973 Author name
5. Conclusion This paper has designed a fuzzy sliding-mode variable structure control for FFU motor speed regulation system,which combined the advantages of fuzzy logic control and sliding mode variable structure control.The system control scheme is analyzed, and fuzzy sliding mode variable structure controlregulator is designed in detail. The test experiment results show the FFU motor control system based on fuzzy sliding-mode variable structure control controller has good control performance, verified the validity of the proposed control strategy. Acknowledgements This work was supported by Jiangsu Province University Scientific Research and Industry Promotion Project, the Science and Technology Planning Project of Suzhou City. References [1]Shirai, T., Shibata, K.,Takahashi, A., Mori, K., Kasashima, N.,Ueno, Y.. Method for detecting faults in FFUs using SDP based on audio signal analysis. Proceedings 1996 IEEE Conference Emerging Technologies And Factory Automation ETFA '96, vol.1,pp: 243 - 247 [2] Yuang-Shung Lee,Te-Tsung Yang,Ming-Wang Cheng.. Measurement and Mitigation of Conducted Emission for Voltage Phase Controlled Capacitor-Run Single Phase Induction Motor. International Conference on Power Electronics and Drives Systems PEDS 2005. vol.2,pp: 1622 - 1627 [3] A. Haddoun, M. E. H. Benbouzid, D. Diallo, R. Abdessemed, J. Ghouili,and K. Srairi, “Sliding-mode control of EV electric differential system,”in Proc. 17th Int.Conf. Elect. Mach., Chania, Greece, 2006, pp. 176–182. [4] K.K. Ahn and N.B. Kha, “Internal Model Control For Shape Memory Alloy Actuators Using Fuzzy Based Preisach Model”, Sensors and Actuators A: Physical,Vol.136, No.2, pp.730-741, 2007. [5] K. K. Shyu and H. J. Shieh, “A new switching surface sliding-mode speed control for induction motor drive systems,” IEEE Trans. Power Electron., vol. 11, pp. 660–667, Jul. 1996. [6 J. Cao and B. Cao, “Fuzzy-logic-based sliding-mode controller design for position-sensorless electric vehicle,” IEEE Trans. Power Electron.,vol. 24, no. 10, pp. 2368–2378, Oct. 2009.
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