A comparative experimental evaluation of various Smith predictor approaches for a thermal process with large dead time

Mejía, Carlos; Salazar, Estefanía; Camacho, Oscar

doi:10.1016/j.aej.2022.03.047

Cited by 24 publications

(15 citation statements)

References 14 publications

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“…This is an excellent tool for testing different control system design techniques. 10,30,55 The TCLab is made up of two heaters, two temperature sensors, a Leonardo Arduino board, and a power supply to feed the heaters, as shown in Figure 23.…”

Section: Resultsmentioning

confidence: 99%

“…The TCLab is a portable, pocket-sized laboratory for control applications using MATLAB Simulink and Python software. This is an excellent tool for testing different control system design techniques. ,, …”

Section: Resultsmentioning

confidence: 99%

“…On the other hand, in the case of long-delay systems, the most common control structure approach used is the Smith predictor (SP) . It combines a PID controller with an inner loop that contains a process model to eliminate the long delay time in the system .…”

Section: Introductionmentioning

confidence: 99%

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Hybrid Controller Based on Numerical Methods for Chemical Processes with a Long Time Delay

et al. 2023

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A hybrid control framework is proposed as an alternative for long time delays in chemical processes. The hybrid approach mixes the numerical methods in an internal mode control (IMC) structure, which uses the particle swarm optimization (PSO) algorithm to improve the adjustment of the controller parameters. Simulation tests are carried out on linear systems of high order and inverse response, both with dominant delay, and tests on a nonlinear process (chemical reactor). The performance of the proposed controller is stable and satisfactory despite nonlinearities in various operating conditions, set-point changes, process disturbances, and modeling errors. In addition, experimental tests were performed on a setup composed of two heaters and two temperature sensors mounted on an Arduino microcontroller-based board called the Temperature Control Laboratory (TCLab), with an additional software delay introduced. The merits and drawbacks of each scheme are analyzed using radar charts, comparing the control methods with different performance measures for set-point and disturbance changes. Furthermore, the new controller uses PSO to improve the tuning parameters.

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Section: Resultsmentioning

confidence: 99%

Section: Resultsmentioning

confidence: 99%

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Hybrid Controller Based on Numerical Methods for Chemical Processes with a Long Time Delay

et al. 2023

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“…Rivera and co-workers [14] recommended Internal Model Control (IMC), which utilizes the closed-loop time constant (τ c ) to determine the extend of aggressiveness set by the controller. Later, author of paper [15] analyzed the PID controller performances by measuring the criteria of process response, controller's response and indexes. The author in paper [16] minimized the settling time and overshoot due to load changes of an uncertain physical plant.…”

Section: Literature Reviewmentioning

confidence: 99%

“…In the survival of the fittest cycle, PSO performs random selection of particles to be adopted and analyzed with a predefined objective function. The ultimate outcome is to determine the best particle position known as personal best position (P id ) and global best position (P gd ) via interactive mathematical operation of two algorithms known as Velocity update, V id(t+1) and Position update, X id(t+1) as depicted in ( 14) and (15).…”

Section: Genetic Algorithm Optimization (Ga)mentioning

confidence: 99%

Metaheuristic-based PID Control: Evaluating the Effect of Parameter Settings

Chew

Wong

Juwono

et al. 2023

Preprint

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Proportional-Integral-Derivative (PID) control method has been utilized in many industrial control applications, which has its limitations for the optimized control. Manually calculated controller tunings by using fixed formulas are only adequately to give basic control but not well-competent to non-linear process with various operating levels. Optimization analysis via metaheuristic approach has substantially obtained the best solutions and has proven its credibility to provide the better controller values. Nevertheless, the optimization analysis might provides bad result if the determinant parameter settings are not properly adjusted during the optimization analysis. This paper objectively presents a direct way to determine the best determinant parameter settings for the optimization analysis, whereby the Genetic Algorithm (GA) and Particle Swarm Optimization (PSO) are chosen for the research analysis. In detail, parameter settings that include upper and lower bounds (UB, LB), maximum iteration (MaxIt), population size (nPop), mutation rate (mu) and damping ratio (wdamp) are analyzed. Ultimately, analysis results are compared with manually calculated controller tunings by using Level Process Control Training Module, SE-207. Both performance indexes and response curves showed that PSO and GA were better performed than the conventional tunings. While comparing optimization analyses, PSO reacted more aggressively than GA corresponding to slight overshoots but both optimizations produced very close error values. In conclusion, metaheuristic approach with proper parameter settings produces better control tunings as for the controlled loop demands aggressive control action would prefer PSO, and in contrast, a stabilized control prefers to apply GA for the nonlinear process.

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A Robust Hybrid Control Approach Tuned by PSO for Long-Time Delay Nonlinear Chemical Processes

Herrera,

Benıtez,

Pérez-Pérez

et al. 2023

Communications in Computer and Information Science

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A comparative experimental evaluation of various Smith predictor approaches for a thermal process with large dead time

Cited by 24 publications

References 14 publications

Hybrid Controller Based on Numerical Methods for Chemical Processes with a Long Time Delay

Hybrid Controller Based on Numerical Methods for Chemical Processes with a Long Time Delay

Metaheuristic-based PID Control: Evaluating the Effect of Parameter Settings

A Robust Hybrid Control Approach Tuned by PSO for Long-Time Delay Nonlinear Chemical Processes

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