Abstract
System identification is a very powerful tool for determining the system model and parameters from sets of observable input and output data. Once the system parameters are obtained, the system dynamic behavior, including all the system characteristics (time constant, overshoot, settling time, etc.) can be accessed and evaluated. Despite the difficulty and communication channel lag, online parameter estimation outperforms offline system identification due to the ability to remotely monitor and control the system as well as improve the system's controller, making it more accurate and reliable. With the extreme development in technology, the importance of combining wireless networks with closed automatic control systems has emerged. This connection facilitates communication processes between the different units in the control for remotely controlled of the output. However, there are some errors affecting such system resulted from communication channel, A/D and D/A conversion process, identification process, or the existence of adaptive weight Gaussian noise. In this paper, the errors were investigated using real system, and then a suitable controller was tuned and optimized in order to reduce and eliminate various errors. The results show excellent dynamic behavior of the system under transmitting and receiving process.
Highlights
Since online system identification has a number of benefits, such as estimating parameters in real time while the system is operating as well as gaining the ability to monitor and operate the system remotely, it has a number of challenges. These challenges include (1) analog system discretization with the proper sampling time depending on the system dynamics (2) use a communication channel to send and receive data (3) using the regression method to find the new approximate parameters based on the nature of the measured data (4) deploying the identification process algorithm to determine the new estimated parameters (5) fine-tune an appropriate controller to reduce or remove all identification process errors, this paper focuses on the online parameters estimation for a DC-DC chopper circuit by applying the measured input and output data to the identification algorithm via OPC (Open Platform Communication) after being modeled in the form of ARMAX model(autoregressive-moving average with exogenous terms)
Sampling time will be investigated, and the effect of changing Ts on the identification process will be determined, the parameters value for the DC-DC Converter will be as in the Table II
Conclusion is that assuming Ts =.001 is better for this system, considering the response time and dynamic behavior for our system (DC Converter circuit), Table VII compares the sampling time with the system characteristic, delay time, and the identification error in general, the ability to tune a controller to overcome the identification error
Summary
Since online system identification has a number of benefits, such as estimating parameters in real time while the system is operating as well as gaining the ability to monitor and operate the system remotely, it has a number of challenges These challenges include (1) analog system discretization with the proper sampling time depending on the system dynamics (2) use a communication channel to send and receive data (3) using the regression method to find the new approximate parameters based on the nature of the measured data (4) deploying the identification process algorithm to determine the new estimated parameters (5) fine-tune an appropriate controller to reduce or remove all identification process errors, this paper focuses on the online parameters estimation for a DC-DC chopper circuit by applying the measured input and output data to the identification algorithm via OPC (Open Platform Communication) after being modeled in the form of ARMAX model(autoregressive-moving average with exogenous terms). The Z Transform is a similar tool that can be used with digital signals It saves us a lot of time manipulating difference equations.
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callMore From: International Journal of Advanced Computer Science and Applications
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
