一种磁性液体加速度传感器模型的参数辨识方法
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摘要
针对磁性液体加速度传感器模型的参数辨识问题,提出一种改进混沌粒子群算法。该算法利用改进的logistic映射对粒子群进行混沌初始化,并采用抛物线规律对迭代过程中的惯性权重进行实时调节,算法最终辨识出了传感器中磁芯吸附磁性液体后的等效长度、等效半径及等效相对磁导率。实验结果表明,该方法辨识出的参数相对误差小于0.85%,且辨识曲线与参考曲线的拟合度在94.37%以上。
Aiming at the parameter identification of ferrofluid acceleration sensor model,an improved chaotic particle swarm optimization algorithm is proposed. The algorithm uses the improved logistic mapping to initialize the particle swarm chaos,and adopts the parabolic law to adjust the inertia weight in the iterative process in real time. The algorithm finally identifies the equivalent length,the equivalent radius and the equivalent relative permeability when the magnetic core adsorbed ferrofluids in the sensor. The experimental results show that the relative error of the parameters identified by this method is less than 0.85%,and the fitting degree between identification curve and the reference curve is above 94.37%.
Aiming at the parameter identification of ferrofluid acceleration sensor model,an improved chaotic particle swarm optimization algorithm is proposed. The algorithm uses the improved logistic mapping to initialize the particle swarm chaos,and adopts the parabolic law to adjust the inertia weight in the iterative process in real time. The algorithm finally identifies the equivalent length,the equivalent radius and the equivalent relative permeability when the magnetic core adsorbed ferrofluids in the sensor. The experimental results show that the relative error of the parameters identified by this method is less than 0.85%,and the fitting degree between identification curve and the reference curve is above 94.37%.
引文
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[2]Raj K,Moskowitz R.Commercial Applications of Ferrofluids[J].Journal of Magnetism&Magnetic Materials,1990,85(1):233-245.
[3]AndòB,Baglio S,Beninato A.A Flow Sensor Exploiting Magnetic Fluids[J].Sensors&Actuators A Physical,2013,189:17-23.
[4]Olaru R,Petrescu C,Hertanu R.A Novel Double-Action Actuator Based on Ferrofluid and Permanent Magnets[J].Journal of Intelligent Material Systems&Structures,2012,23(14):1623-1630.
[5]AndòB,Baglio S,Beninato A.A Inertial Sensor Exploiting a Spike Shaped Ferrofluid[C]//Instrumentation and Measurement Technology Conference,Warsaw:IEEE,2011.1-5.
[6]Chitnis G,Ziaie B.A Ferrofluid-Based Wireless Pressure Sensor[J].Journal of Micromechanics&Microengineering,2013,23(12):5031.
[7]Yao J,Huang C,Li D.Research on a Novel Ferrofluid Inertial Sensor with Levitating Nonmagnetic Rod[J].IEEE Sensors Journal,2016,16(5):1130-1135.
[8]Xiao X,Xu Q,Wang Y,et al.Parameter Identification of Interior Permanent Magnet Synchronous Motors Based on Genetic Algorithm[J].Transactions of China Electrotechnical Society,2014,29(3):21-26.
[9]Xing X,Wei W,Long C.Parameter Identification of Electrochemical Model for Vehicular Lithium Ion Battery Based on Genetic Algorithm[J].Automotive Engineering,2017,39(7):813-821,838.
[10]Montazeri A,West C,Monk S D,et al.Dynamic Modelling and Parameter Estimation of a Hydraulic Robot Manipulator Using a Multi-Objective Genetic Algorithm[J].International Journal of Control,2017,90(4):661-683.
[11]Alfi A,Modares H.System Identification and Control Using Adaptive Particle Swarm Optimization[J].Applied Mathematical Modelling,2011,35(3):1210-1221.
[12]Alfi A,Fateh M M.Intelligent Identification and Control Using Improved Fuzzy Particle Swarm Optimization[J].Expert Systems with Applications,2011,38(10):12312-12317.
[13]Hodashinsky I A,Bardamova M B.Tuning Fuzzy Systems Parameters with Chaotic Particle Swarm Optimization[C]//International Conference on Information Technologies in Business and Industry,IOP,2017.012053.
[14]Huynh D C,Dunnigan M W.Parameter Estimation of an Induction Machine Using a Chaos Particle Swarm Optimization Algorithm[C]//Iet International Conference on Power Electronics,Machines and Drives,Brighton:IET,2010:1414-1419.
[15]李强,李德才,何新智,等.磁性液体与加速度传感器的输出特性关系研究[J].电子测量与仪器学报,2011,25(3):246-252.
[16]Iusan V Z,Stanci A G.Inertial Magnetofluidic Sensor[J].IEEETransactions on Magnetics,1994,30(2):1104-1106.
[17]Stanci A,Iusan V,Buioca C D.Magnetofluidic Sensor for Volume Measurement[J].Sensors&Actuators A Physical,2000,84(3):246-249.
[18]高鹰,谢胜利.混沌粒子群优化算法[J].计算机科学,2004,31(8):13-15.
[19]刘军民,高岳林.混沌粒子群优化算法[J].计算机应用,2008,28(2):322-325.
[20]高尚,杨静宇.混沌粒子群优化算法研究[J].模式识别与人工智能,2006,19(2):266-270.
[21]El-Latif A A A,Li L,Zhang T,et al.Digital Image Encryption Scheme Based on Multiple Chaotic Systems[J].Sensing&Imaging An International Journal,2012,13(2):67-88.
[22]吕振肃,侯志荣.自适应变异的粒子群优化算法[J].电子学报,2004,32(3):416-420.