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Experimental Validation of Frequency Response Model Matching Method for Processes with Dead-Time

By: Contributor(s): Publication details: New Delhi Journals Pub 2019Edition: Vol.5(1), Jan-JunDescription: 30-40pSubject(s): Online resources: In: International journal of embedded systems and emerging technologiesSummary: ABSTRACT This paper addresses proportional-integral- derivative (PID) controller design for singleinput, single-output (SISO) process. The controller design is based on the frequency response model matching method. Tuned parameters of PID controller are found by two methods. A double feedback loop configuration is considered. In the first method, The inner loop is designed with a stabilizing gain while the outer loop is designed using frequency response matching between the closed loop system and the reference model for obtaining parameters of PID controller. In the second method, the reference model is selected for a load disturbance rejection. In both the methods, two low-frequency points are considered for matching the frequency response, thereby giving linear algebraic equations for controller parameters. To demonstrate the effectiveness, these methods are experimentally validated. For better understanding, experimental results are compared with MATLAB simulation results.
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ABSTRACT This paper addresses proportional-integral- derivative (PID) controller design for singleinput, single-output (SISO) process. The controller design is based on the frequency response model matching method. Tuned parameters of PID controller are found by two methods. A double feedback loop configuration is considered. In the first method, The inner loop is designed with a stabilizing gain while the outer loop is designed using frequency response matching between the closed loop system and the reference model for obtaining parameters of PID controller. In the second method, the reference model is selected for a load disturbance rejection. In both the methods, two low-frequency points are considered for matching the frequency response, thereby giving linear algebraic equations for controller parameters. To demonstrate the effectiveness, these methods are experimentally validated. For better understanding, experimental results are compared with MATLAB simulation results.

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