Proportional-Integral-Derivative (PID) Temperature Control & Data Acquisition System for Faraday Filter based Sodium Spectrometer Vardan Semerjyan, Undergraduate Researcher Tao Yuan, Faculty Mentor Control Algorithm For precise temperature reading, the Resistance - Temperature function parameters were calibrated with the commercial thermometer. For finding the optimal control gains, steady-state error (the difference between the output and the desired output) criteria were used. Sodium (Na) Faraday filters based spectrometer is a relatively new instrument to study sodium nightglow [Harrell et al., 2010] as well as atmospheric chemistry in the mesopause region. Successful spectrometer measurement demands highly accurate control of filter temperature. The ideal operation site for this Na spectrometer would be an isolated location with minimum nocturnal sky background. Thus, the remote and automatic control of the filter temperature is a requirement for such operation, whereas current temperature controllers can only be adjusted manually by the operator. The proposed approach is aimed not only to enhance the accuracy of the temperature control but also to achieve spectrometer’s remote and automatic operation. In the meantime, the redesign should relieve the burden of the cost for multiple temperature controllers. The new design will also enable the monitoring the filter’s temperature variations, and logging the data during the operation. The real-time observation results will be posted online after the observation is completed. This approach also can be a good substitute for the temperature control system currently used to run the LIDAR system [Chen, 1999] at Utah State University (USU). Control user interface gives to the user ability to control and monitor the temperature readings. The implementation of the proposed temperature control has shown the success of controlling the Na Faraday filter based spectrometer by using LabVIEW combined with much more cost efficient data acquisition board NI DAQ (USB-6008). The first result shows close to satisfactory results. But there is still room for improvement to achieve better performance. The next phases of this project will be 1.) Temperature calibration of the new design will be done by comparing the reading temperature in the LabVIEW program with the one by the existing temperature controller. 2.) Finding the ideal filter temperature for the Na nightglow measurement 3.) Finalizing data taking program for Na spectrometer field test Faraday Filter Based Spectrometer Abstract Temperature Control and Data Acquisition System Implementation in LabVIEW Conclusions and Future Work In the center of the Faraday filter is a metal vapor cell containing metallic Sodium (Na). The cell is put in an aluminum oven and heated to a desirable temperature for appropriate filter transmission. To improve filter’s temperature stability, good thermo isolation and temperature control algorithm should be implemented. This research will mainly focus on the temperature control. Faraday Filter spectrometer consists of six important units Faraday Filter Blocks Chopper Wheels Photo Multiplier Tubes (PMT) Temperature Control Unit Data Acquisition Cards Control Computer Temperature Control Unit The current temperature control unit consists of two temperature controllers and relays for one filter. Based on the readings from the thermocouples inside the filter, thermo controller decides turn the voltage on or off to adjust the temperature to the set value. Limitations Manual Temperature Setting Expensive Unable to Store Temperature History Software Controlled Approach PID control algorithm Voltage to Resistance Resistance- Temp. Function Thermometer Measured Temperature Used once for calibration Temperature Settings PID parameters Temperature Diagram Power Diagram Signal to control heaters (Defines the power output) Temp. Value Voltage Ni-DAQ Calibrate PID if needed References Harrell, S. D., Chiao-Yao She, Tao Yuan, David A. Krueger, J.M.C. Plane, Tom Slanger (2010) “ The Faraday Filter-Based Spectrometer for observing sodium nightglow and studying atomic molecular oxygen associated with the sodium chemistry in the mesopause region. "Journal of Atmospheric and Solar-Terrestrial Physics Chen, S. “Sodium/Potassium Faraday Filter for Daytime Lidar Temperature observations and Study of Tidal Waves in the Mesopause Region of the Atmosphere ”Diss. Colorado State U,1999. Sheets, D. C., Z. S. Roth, and J. W. Snyder. "Auto tune of PID Temperature Control Based on Closed-loop Step Response Tests." AIP Conference Proceedings (2006): Special thanks to the Xuewu Cheng for his valuable advices and support To control the cell temperature inside the filter head, a PID algorithm [Sheets, et al., 2006] was implemented using the NI LabVIEW software. The program also provides user friendly environment for the operator to control and monitor temperature. Figure 4 shows the basic working schematic of the temperature control and data acquisition system. The change of resistance in thermo sensors will affect the voltage reading, which will be detected by the sampling on the NI DAQ card. The software will convert the voltage into temperature. The PID algorithm will use the difference between the reading temperature and the set point to decide the output power to the heaters. Variable power output of the heathers is implemented by controlling the percentage of the time it is on in unit time. Figure 9. Plots of Temp. vs. Time Figure 7. User Interface Figure 8. Block Diagram of Temperature reading and PID control Figure 4. Block Diagram of Temperature control and Data Acquisition reading and PID control First results show ±1 C° temperature oscillation which can be the result of the noise in the voltage reading. Also considering the small size of the cell rapid cooling or heating properties can have its impact as well. Figure 6. Block Diagram of Temperature control and Data Acquisition reading and PID control Figure 2. Faraday Filter based Spectrometer Head (exploded view) Figure 1. Spectrometer Figure 3. Temperature Control Unit Currently in use where K P - Proportional gain K I - Integral gain K D - Derivative gain e - Temperature error Figure 5. Implemented PID Temperature Control Unit