Modelling and control of heat exchanger by using bio-inspired algorithm

• Main Author: Daud, Nur Atiqah
• Format: Thesis
• Language: English; English; English
• Published: 2014
• Subjects: TJ Mechanical engineering and machinery; TJ255-265 Heat engines
• Online Access: http://eprints.uthm.edu.my/1621/1/24p%20NUR%20ATIQAH%20DAUD.pdf; http://eprints.uthm.edu.my/1621/2/NUR%20ATIQAH%20DAUD%20COPYRIGHT%20DECLARATION.pdf; http://eprints.uthm.edu.my/1621/3/NUR%20ATIQAH%20DAUD%20WATERMARK.pdf; http://eprints.uthm.edu.my/1621/

Heat exchanger is a heat transfer device that is used for transfer of thermal energy between two or more fluids available at different temperature. Based on the previous study referred, the same data of heat exchanger had been used but different types of model were used to find the structural model of heat exchanger. The main objective of this study is to obtain structural model using ARMAX equation and optimize the value of PID parameters. In this study, data from heat exchanger experiment was used to determine the parameter of ARMAX equation and by using GA and PSO, all the parameters were optimized. Transfer function obtained will be used for plant modelling. Validation test used to validate between normalised data input and error. Validation test used were autocorrelation and cross-correlation. Finally, applying PID controller onto plant modelling to optimize the value of Kp, Ki and Kd. The analysis shows that MSE value produce from GA is 0.0035473 while PSO‟s MSE value is 0.0043595. ARMAX parameters were obtained by using GA and PSO with 4 inputs (a0, a1, a2, and a3) and 4 outputs (b0, b1, b2 and b3). For GA, the inputs are -0.000214, -0.000728, - 0.0020, and -0.000804 while the outputs are -1.0000, -0.1783, -0.1473 and 0.3248. For PSO, the inputs are 0.0104, -0.0122, -0.0067 and 0.0118 while the outputs are -0.4274, -0.1256, -0.1865 and-0.2614. From the validation test, GA produced smoother and effective result compared to PSO with less noise exists. By attaching PID controller, all the parameters value (Kp, Ki, and Kd) was optimized. For GA, the parameters are -0.5567, -54.1127 and 0.0005. For PSO, the parameters are - 0.2846, -56.4346 and 0.0010. Even though both algorithms produced different simulation results, both of them succeed to reduce the result before attaching PID controller. As a conclusion, GA produces better result compared to PSO.