Generalized Predictive PI Controller: Analysis and Design for Time Delay Systems

Briones, Oscar A.; Rojas, Alejandro J.; Sbárbaro, Daniel

doi:10.23919/acc50511.2021.9482789

Cited by 7 publications

(7 citation statements)

References 11 publications

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“…The study in [20], discusses the application of PI compensators in several systems, highlighting their importance in achieving stability, improved performance, and effective control. The article discusses the use of PI compensators in systems such as robotic manipulators, industrial processes, and thermal plants.…”

Section: Control System Designmentioning

confidence: 99%

“…From the information extracted in [19][20][21] and taking into account [10,11,17], it can be seen that choosing PI compensators over other control strategies is a reasoned decision based on a thorough evaluation of the benefits and drawbacks, taking into account the specific characteristics of the vaporizer process and the desired control objectives. A comprehensive analysis can be done as follow:…”

Section: Control System Designmentioning

confidence: 99%

“…Evaluating (20), the values found for the tuning parameters are kc = 1.533•10 16 and τi = 3.33•10 -4 s. These initial values operate as a starting point for effective configuration of the PI compensator. However, it is important to note that these parameters are subject to refinement once the PI compensator is integrated into the system simulator, for example.…”

Section: Lc Control Loop Designmentioning

confidence: 99%

See 2 more Smart Citations

Cascade Control Applied to a Single-Component Single-Stage Vaporizer—Modeling and Simulation

Campos-Salazar,

Lecaros,

Sandoval

2023

J. Electron. Electric. Eng.

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This comprehensive research addresses a gap in the literature by providing an extensive examination of a single-component single-stage vaporizer process. The research involves sophisticated analyses such as dynamic modeling, comprehensive control system design and performance evaluation. The study systematically derives a linear state-space model from complex nonlinear dynamic models, laying the basis for the development of two highly effective control systems specifically designed for vaporizer level and temperature control. The simulations of these control structures demonstrate notable properties, including fast disturbance rejection, minimal overshoot, and virtually no steady-state error, emphasizing their robustness and precision. This research focuses on the stability and response of the system and provides insight into its transient behavior during disturbances and setpoint changes. The study's broad implications extend beyond the results and provide a path for future improvements. The results indicate ways to refine the start-up stage, minimize initial overshoot during system initialization, and further improve control strategies. This work has the potential to make a difference in advancing the field of vaporization processes, providing engineers and researchers with the tools and insights needed to improve system reliability and performance in industrial applications.

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Section: Control System Designmentioning

confidence: 99%

Section: Control System Designmentioning

confidence: 99%

Section: Lc Control Loop Designmentioning

confidence: 99%

See 1 more Smart Citation

Cascade Control Applied to a Single-Component Single-Stage Vaporizer—Modeling and Simulation

Campos-Salazar,

Lecaros,

Sandoval

2023

J. Electron. Electric. Eng.

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show abstract

“…Many control solutions have been created to mitigate the effect caused by long delays in industrial processes . We can mention model predictive controller (MPC), fuzzy logic controller (FLC), sliding mode control (SMC), robust control, internal model control (IMC), Smith predictor (SP) modifications, and combinations of them. ,− These control methods are useful for reducing the effects of long delays on stable and unstable systems.…”

Section: Introductionmentioning

confidence: 99%

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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“…In terms of rapidity, robustness, and stability, the control result of GPC is more notable than that of traditional PID control [ 8 , 9 ]. Nowadays, most scholars improve GPC in two aspects: The establishment of the prediction model and the improvement of the optimization method.…”

Section: Introductionmentioning

confidence: 99%

Improved Particle Swarm Optimization Based on Entropy and Its Application in Implicit Generalized Predictive Control

Zhang

Zhai

Han

et al. 2021

Entropy

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Setting sights on the problem of input-output constraints in most industrial systems, an implicit generalized predictive control algorithm based on an improved particle swarm optimization algorithm (PSO) is presented in this paper. PSO has the advantages of high precision and fast convergence speed in solving constraint problems. In order to effectively avoid the problems of premature and slow operation in the later stage, combined with the idea of the entropy of system (SR), a new weight attenuation strategy and local jump out optimization strategy are introduced into PSO. The velocity update mechanism is cancelled, and the algorithm is adjusted respectively in the iterative process and after falling into local optimization. The improved PSO is used to optimize the performance index in predictive control. The combination of PSO and gradient optimization for rolling-horizon improves the optimization effect of the algorithm. The simulation results show that the system overshoot is reduced by about 7.5% and the settling time is reduced by about 6% compared with the implicit generalized predictive control algorithm based on particle swarm optimization algorithm (PSO-IGPC).

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Generalized Predictive PI Controller: Analysis and Design for Time Delay Systems

Cited by 7 publications

References 11 publications

Cascade Control Applied to a Single-Component Single-Stage Vaporizer—Modeling and Simulation

Cascade Control Applied to a Single-Component Single-Stage Vaporizer—Modeling and Simulation

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

Improved Particle Swarm Optimization Based on Entropy and Its Application in Implicit Generalized Predictive Control

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