A Hybrid Sliding Mode Torque Controller for Switched Reluctance Motor Yong Cheng School of Electrical and Control Engineering, Xi’an University of Science and Technology,Xi’an,China ([email protected]) Abstract - In the paper, a new closed loop system was proposed for torque controlling, which was based on sliding mode control (SMC) in switched reluctant motor(SRM). Analyzing direct instantaneous torque control method and SRM, SMC was introduced in control algorithm with detailed derivations. Relative outgoing phase torque compensation algorithm was proposed. Finally, simulation results indicate this method is validity of eliminating torque ripple in SRM. Keywords - torque ripple, direct instantaneous torque control (DITC), hybrid sliding mode control(HSMC), torque compensation I. INTRODUCTION Switched reluctance motor (SRM) has simple structure and strong robust. It was widely used in different fields. However, doubly salient structure[1] has made strong nonlinear and torque ripple, which has effect SRM usage. In terms of torque, many scholars has designed different strategies to minimize torque ripple from different theory[2][3].So scholars proposed modified structure of SRM to reduce torque ripple. Another method was controlling strategy. Current control, switching angle and intelligent control were used in torque ripple reducing. But this method has made progress limitedly. Sliding Mode controller was a useful theory in nonlinear system, which has been made great progress in pass years[4-9]. In this fields, SMC(sliding mode controlling) had unique advantage. SMC has robust controlling, which need not accurate arithmetic modeling of nonlinear system. In the paper, a hybrid SMC(HSMC) was used on torque ripple reducing, which has been proposed to reduce torque ripple at different stages. Controlling system has been set up with torque close loop with DITC(direct instantaneous torque control). By this method, torque was reduced obviously in final simulation. II. ANALYSIS OF HSMC 1) Controlling strategy on DITC: DITC was generally acknowledged and effective method of torque control, which took feedback torque as control variety. DITC was used different instantaneous voltage to control output torque in plus torque output area. Here, HSMC was introduced to reduce torque ripple at single phase and commutation region, which composed of SMC and compensate algorithm of commutation region as figure 1. In figure 1, phase (K-1) and phase K meant outgoing phase and incoming phase. In single conductive driving, asymmetry half-bridge circuit was typical circuits, which has three states +1,0 and -1. In single conductive module, there were single phase and two phases working. In the switching region Z1, phase C and phase B were incoming phase and outgoing phase. In commutation region, incoming phase will go into single phase working stage .Outgoing stage will turn off, which has larger current. In figure3, a turn-off strategy was proposed at commutation region. For continuity of SMC, incoming phase will work on independently in single phase. So, it took main role at commutation region, which meant increasing output torque. Outgoing phase will step into turn-off. For reducing torque ripple, outgoing phase took main role at decreasing output torque state, which will corporate with incoming phase. Figure 3 showed controlling strategy of T ,system need increased output outgoing phase. If err T , torque,at which outgoing turn on at +1 state. If err system need decreased output torque, at which outgoing Terr ,incoming phase can turn off at -1 state. If output enough torque ,which meant outgoing deceased slowly at freewheeling state. commutation region Incoming phase Tref + T Terr SMC outgoing phase Compensation algorithm SMC - sensor Driving circuit SRM Single phase region T(i, ) sensor i Fig.1. structure of control scheme L Commutation region A B C D Z1 Con Boff Single phase region A (°) Don Coff Aon Doff Bon Aoff Fig.2. Relation of induction and position angle Sk-1 1 0 -1 Terr Fig.3. scheme of torque compensation 2) SMC: Consider the following dynamical system as: x1 x2 x2 f ( x) b( x)u (1) where x [ x1 x2 ]T is the state vector, u is the system control input and f(x) and b(x) are nonlinear functions. Now, consider a given desired trajectory x1d (t ) and the error e(t ) x1 (t ) x1d (t ) . SM control forces the system, after a reaching phase, to the following sliding line: s ( x) e e between VDC and -VDC , voltage can be adjusted by duty cycle of PWM. However, equivalent control can easily produce chatter close to boundary. So switching control was selected by error , which was different value within error bands or not to minimize chatter in SMC. Terr Terr VDC u Terr sgn(T ) V err DC (2) where x2 d (t ) x1d (t ) and the sliding constant is strictly positive. At steady state the system follows the desired trajectory once s=0. Hence, a suitable control action is to be designed for the system to hit the sliding surface (2). We select the Lyapunov function: 1 V s2 (3) 2 with control making it meeting: 1 d 2 V S 0 2 dt According to high dynamic performance and direct instantaneous torque control, switch function was defined as: S Terr Tref T (4) (12) III. SIMULATION RESULTS In simulation, Matlab7.6.0 was used as simulating software for SRM 8/6 research, at which turn-on and turnoff angles were set as 6° and 27°. For details of research, waveform were focused on A, B and C phases. The control system was designed with DITC structure[10]. So sampling torque was derived from table of T ( , i) , in which angle and current signal were captured from simulating module in MATLAB. 4 Total 总 torque 转 矩 Torque C 相 in 转phase 矩 C Torque A 相 in 转phase 矩 A Torque B 相in转phase 矩 B 3.5 3 转T矩/ N . m di 1 d ( ) (u iR ) (10) dt i dt From functions above, there was: T d T 1 d ueq ( )( ) ( ) iR (11) dt i i dt Equivalent voltage ueq were influenced by current and derivation between flux , current and angle. In controlling, saturation of voltage was VDC .If ueq was 2.5 2 1.5 1 Supposing d Tref 0 , there was: dt d T (Tref T ) 0 dt 0.5 0 0.2 0.21 0.22 0.23 0.24 0.25 time间 / s 时 Fig.4. torque and current curve at refered torque changing When speed was 600r/m , there was 0.1N.m. So output torque has these waveforms as figure below. 7.4 7.2 转矩 /N.m T/N.m where Terr was error of torque, Tref was reference torque, T is feedback torque. And the control was: u U 0 sgn( S ) (5) All u must meet : 1 d 2 S 0 (6) 2 dt From equation (5), there was : d (7) dt (Tref T ) (Tref T ) 0 7 6.8 (8) 6.6 0.4 0.42 0.44 0.46 0.48 0.5 时间/s Time/s 0.52 0.54 0.56 0.58 0.6 Fig.5. torque curve at steady state under hybrid SMC Torque was function with current and angle, so: T i T T (i, ) i t t With prime voltage function , there was (9) 7.4 转矩 /N.m T/N.m 7.2 7 6.8 6.6 0.4 0.42 0.44 0.46 0.48 0.5 0.52 0.54 0.56 0.58 0.6 时间/s Time/s Fig.6. torque curve at steady state under switching type SMC From figures above, HSMC can limit torque error between error bands. HSMC has performed better than switching SMC, because HSMC has designed algorithm for output torque, especially in commutation region. In results, there were two testing parts, which were changing at desired torque changing and details of torque. In first part, there was 0.05N.m, and desired torque was changed from 3N.m to 1N.m. System has perfect dynamic performance. V. CONCLUSION A new torque control base SMC was proposed in the paper. With detailed derivation, HSMC was proposed, which was also proved to be convergent and steady. Simulating results showed HSMC were valid in SRD to reduce torque ripple. REFERENCES [1] Miller T J E.Switched reluctance motors and their control[M].Oxford:Magna Physics Publishing and Oxford University Press,1993. [2] Cheok A D, Ertugrul N. Use of fuzzy logic for modeling, estimation, and prediction in switched reluctance motor drives[J]. IEEE Trans. Ind. Electron.,1999, 46(6) :1207~ 1224. [3] Lin Z,Reay D S,Williams B W.Torque ripple reduction in switched reluctance motor drives using B-spline Neural networks[C].14th IAS Annual Meeting,2005:2726-2733. [4] Utkin V I. Variable structure systems with sliding modes[J] . IEEE Transactions on Automatic Control , 1977 , 22 (2) : 212-222. [5] M. Zak. Terminal Attractors for Addressable Memory in Neural Network. 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