{"title":"Hardware Design and Implementation of Optoelectronic Pod Control System Based on DSP","authors":"Zhigang Feng, M. Jin","doi":"10.14257/ijhit.2017.10.8.03","DOIUrl":null,"url":null,"abstract":"The optoelectronic pod always works in complicated environment, so it was impacted inevitably on various of elements such as Windage, Mechanical vibration, Load disturbance and so on. These random factors and nonlinear factors led to reduce the control precision, so much so that it can damage the hard-system of the optoelectronic pod. Traditional control system of optoelectronic pod always adopts PID control algorithm to eliminate errors between control target and actual feedback. However, the traditional PID can’t track variational variables such in the complicated environment. It can led to lower the control precision and slow the speed of response. Self-adaption control system of optoelectronic pod adopts active disturbance rejection control (ADRC) technique which can track the mutational disturbance, estimates it and compensates it. In this paper, optoelectronic pod control system is designed and implemented by using TMS320F28335 to acquire the sensor signals, execute control algorithm, and drive the DC torque motor. The angular displacement sensors acquire the attitude angular displacement and the gyroscope acquires the attitude angular speed. The system can get attitude information of the optoelectronic pod with them. The motor diverters detect the driven current of motor to complete control feedback of DC torque motor. The EEPROM stores control parameters and sends relevant parameters according to DSP instructions. Experimental results indicate that DSP data processing unit can acquire the inner sensors data correctly in normal state, and perform control algorithms steadily in the disturbed environment.","PeriodicalId":170772,"journal":{"name":"International Journal of Hybrid Information Technology","volume":"96 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2017-08-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of Hybrid Information Technology","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.14257/ijhit.2017.10.8.03","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
The optoelectronic pod always works in complicated environment, so it was impacted inevitably on various of elements such as Windage, Mechanical vibration, Load disturbance and so on. These random factors and nonlinear factors led to reduce the control precision, so much so that it can damage the hard-system of the optoelectronic pod. Traditional control system of optoelectronic pod always adopts PID control algorithm to eliminate errors between control target and actual feedback. However, the traditional PID can’t track variational variables such in the complicated environment. It can led to lower the control precision and slow the speed of response. Self-adaption control system of optoelectronic pod adopts active disturbance rejection control (ADRC) technique which can track the mutational disturbance, estimates it and compensates it. In this paper, optoelectronic pod control system is designed and implemented by using TMS320F28335 to acquire the sensor signals, execute control algorithm, and drive the DC torque motor. The angular displacement sensors acquire the attitude angular displacement and the gyroscope acquires the attitude angular speed. The system can get attitude information of the optoelectronic pod with them. The motor diverters detect the driven current of motor to complete control feedback of DC torque motor. The EEPROM stores control parameters and sends relevant parameters according to DSP instructions. Experimental results indicate that DSP data processing unit can acquire the inner sensors data correctly in normal state, and perform control algorithms steadily in the disturbed environment.