Delayed Model Approximation and Control Design for Under-Damped Systems

Rodríguez, David Fernando Novella; Muro-Cuéllar, Basilio del; Hernandez-Hernández, German; Márquez‐Rubio, Juan Francisco

doi:10.1016/j.ifacol.2017.08.127

Cited by 7 publications

(6 citation statements)

References 12 publications

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“…As can be seen from the previous relations, in the implemented controller, three frequency characteristic points are determined for proportional systems, which allows estimating up to five model parameters. Due to the great versatility supported by published results, e.g., [28,29] From the steady state waveforms of the manipulated variable u, the controlled variable y obtained during the identification phase, and the calculated auxiliary variables u 2 and y 2 , the points G(jω), ω = 0, 2π/T p , 4π/T p of the Nyquist frequency characteristics of the controlled process are determined using the following relations:…”

Section: Relay Feedback Identificationmentioning

confidence: 99%

Self-Tuning Controller Using Shifting Method

Hofreiter,

Moučka,

Trnka

2023

Mathematics

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This paper presents a newly implemented self-tuning PID controller that uses a relay feedback identification using a recently designed relay shifting method to determine the mathematical model of the process and subsequently adjust the controller parameters. The controller is applicable to proportional and integrating systems and is even applicable to systems with transport delays if steady-state oscillation can be achieved in the relay control of the system. After briefly introducing the relay shifting method, the current paper describes the hardware (HW) and software (SW) of the proposed controller in detail. The relay feedback identification and control of a laboratory setup by an automatically tuned controller is demonstrated on a real laboratory device called “Hot air tunnel”. The evaluation of the experiment and the characteristics of the controller are presented at the end of the paper. The advantage of the relay method is that it is not as computationally intensive as other identification methods. It can thus be implemented on more energy-efficient microcontrollers, which is very important nowadays.

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Section: Relay Feedback Identificationmentioning

confidence: 99%

Self-Tuning Controller Using Shifting Method

Hofreiter,

Moučka,

Trnka

2023

Mathematics

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“…The SOTD model is very versatile and can be used to describe most non-oscillating or oscillating proportional systems with or without a transport delay (see [22,23]). This model has only four parameters-a 2 , a 1 , K, and T d , which can be estimated from the frequency response points G(0) and G(jω k ), k = 1, 2, .…”

Section: Model Fittingmentioning

confidence: 99%

“…The lag-dominated oscillatory proportional process considered in [23] is given by the following transfer function:…”

Section: Lag-dominated Oscillatory Proportional Processmentioning

confidence: 99%

“…If we know the process model, we need to determine the parameters of the controller. There are a number of recommendations for PID controller tuning that can be used for control of a process described by transfer function (9) (see, for example, Åström and Hägglund [25], Skogestad and Grimholt [26], Novella-Rodriguex et al [23], and O'Dwyer [27]).…”

Section: Pid Controller Tuningmentioning

confidence: 99%

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Relay Identification Using Shifting Method for PID Controller Tuning

Hofreiter

2021

Energies

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The aim of this study was to present a relay shifting method for relay feedback identification of dynamical systems suitable for PID controller tuning. The proposed technique uses a biased relay to determine frequency response points from a single experiment without any assumptions about a model transfer function. The method is applicable for open-loop stable, unstable, and integration processes, even with a delay, and regardless of whether they are oscillating or non-oscillating. The core of this technique was formed by the so-called relay shifting filter. In this study, the method was applied to a parameter estimation of a second-order time-delayed (SOTD) model that can describe, with acceptable accuracy, the dynamics of most processes (even with a transport delay) near the operating point. Simultaneously, a parameter setting for the PID controller was derived based on the model parameters. The applicability of the proposed method was demonstrated on various simulated processes and tested on real laboratory apparatuses.

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“…In the literature, there are investigations in which identification techniques have been used in overdamped and underdamped systems. In the work done in [17], a PID tuning methodology was proposed to obtain the mathematical model of high-order plants with oscillating dynamics. The researchers in [18] used different non-parametric identification methods applied in a linear pressure process.…”

Section: Introductionmentioning

confidence: 99%

Evaluation of non-parametric identification techniques in second order models plus dead time

Robles-Algarín

Rodríguez

Ospino

2020

IJECE

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In this paper, a set of non-parametric identification techniques are used in order to obtain second order models plus dead time for an underdamped system. Initially, non-parametric techniques were used to identify the system from the temperature data of a coal-heated oven. In this case, the identification techniques proposed by Stark, Jahanmiri - Fallahi and Ogata were used, which require obtaining two or three points of the step response for the system under study. In addition, the Matlab PID Tuner app was used to identify the underdamped system and compare the results with the other methods. The results show that the PID Tuner and the method proposed by Ogata are the ones that best represent the dynamics of the underdamped system, taking into account the values for the Integral Absolute Error (IAE) and the correlation coefficient. With the Stark method an IAE of 181.56 was obtained, while with the PID Tuner the best performance was achieved with an IAE of 21.59. In terms of the results obtained with the cross correlation, the best performance was achieved with the PID tuner and the Stark method.

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Delayed Model Approximation and Control Design for Under-Damped Systems

Cited by 7 publications

References 12 publications

Self-Tuning Controller Using Shifting Method

Self-Tuning Controller Using Shifting Method

Relay Identification Using Shifting Method for PID Controller Tuning

Evaluation of non-parametric identification techniques in second order models plus dead time

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