GA-Based Optimization for Multivariable Level Control System: A Case Study of Multi-Tank System

This paper presents a systematic way to determine the trade-off optimized controller tunings using computation optimization technique for both servo and regulatory controls of the Multi-Tank System, as one of the applications under the multivariable loop principle. The paper describes an improved way to obtain the best Proportional-Integral (PI) controller tunings in reducing the dependency on engineering knowledge, practical experiences and complex mathematical calculations. Relative Gain Array (RGA) calculation justified the degree of relation and the best pairing for both interacted control loops. Genetic Algorithm (GA), as one of the most prestigious techniques, was used to analyze the best controller tunings based on factor parameters of iterations, populations and mutation rates to the applied First Order plus Dead Time (FOPDT) models in the multivariable loop. Amid simulation analysis, GA analysis’s reliability was justified by comparing its performance with the Particle Swarm Optimization (PSO) analysis. The research outcome was visualized by generating the process responses from the LOOP-PRO’s multi-tank function, whereby the GA tunings’ responses were compared with the conventional tuning methods. In conclusion, the result exhibits that the GA optimization analysis has successfully demonstrated the most satisfactory performance for both servo and regulatory controls

A study of process identification, frequency response analysis and optimum proportional-integral tunings for an identified temperature control system

Single loop feedback control is commonly used in many industrial applications due to low cost. However, it still deserved an optimum control for the good performance of the controlled process to avoid failures and shutdown of the plants. A good control should have a proper process identification to imply the process dynamic behavior. This paper presents the process identification, frequency response analysis and an optimal PI tuning of a single loop controlled system without involving the complicated stage in determining the best PI tunings for both the servo and regulatory control problems at a nominal point. In realizing the objective, a temperature control function of the Process Control Simulator is chosen. Process identification of the First Order Plus Dead Time is obtained through the developed algorithm. Meanwhile, frequency analysis and the optimal PI tunings are studied by using MATLAB simulation tools. It is found that the produced responses are varied by adjusting the compensator ratio where the optimal PI tunings for a stable and aggressive control is eventually determined

Frequency response analysis and optimum tuning for temperature control system

The paper presents frequency responce analysis of temperature control system through Bode Diagram. From the open loop manual test, First Order Plus Dead Time model reflects open loop process behavior. SISOTOOL function in Matlab is utilized for designing the Proportional and Integral Controller. Besides, this paper proposes Routh-Hurwitz stability criterion to calculate stability margin and Compensator Ratio for obtaining optimized controller settings and the analysis were justified through Process Control Simulator, SE-201. It was found that Compensator ratio of 0.095 is the optimized tuning, which gives proportional gain of 16.2% and time constant is 65s for both servo and regulatory control