Stabilization and PID tuning algorithms for second-order unstable processes with time-delays

Seer, Qiu Han; Nandong, Jobrun

doi:10.1016/j.isatra.2017.01.017

Cited by 45 publications

(33 citation statements)

References 24 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Qiu Han Seer et al [23] have presented stabilization through second order unstable processes PID controller. The PID controller specified as SODUP and SODTUP which was operated through essential and enough basis on the analysis of Routh-Hurwitz stability.…”

Section: Recent Related Work: An Overviewmentioning

confidence: 99%

See 1 more Smart Citation

An Effective Technique for Tuning the Time Delay System with PID Controller-Ant Lion Optimizer Algorithm with ANN Technique

George

Ganesan

2020

IJEAT

View full text Add to dashboard Cite

Nowadays, the PID controller is very common controller as well as very important controller in industrial utilizations. In the paper, proposed an ALO algorithm and ANN controller is utilized to enhance PID controller performance and control the tuning of TDS. TDS stands for Time delay system. ALO stands for Ant lion optimizer and ANN stands for Artificial neural network. In terms of parameters controlling, the time delay system is controlled and for different delay events low overshoot and fast time settling is reached. The novelty of the presented method is enhancing the PID controller performance by optimizing the PID gain parameters and controlling the highorder TDS. The performance of time delay system can be enhanced through decreasing error, tracking, time delay & error, rapid and exactly for their corresponding reference values. For parameter controlling of time delay system along optimal values, can be significantly enhanced the performance. To analyze the characteristics of the presented method, the various time delay systems are analyzed. The input and gain parameters were utilized to evaluate the objective function from tuning system. Based on proposed method, the optimal result is achieved and evaluated the increae time, settling time, overshoot as well as steady state error in TDS. The suggested controller is executed in MATLAB/Simulink work site and the presented technique performance examined through performance indexes and time domain specifications are evaluated using presented method compared to previous methods like ABC (Artificial Bee colony) algorithm, GSA (Gravitational Search Algorithm) ,FA (Firefly Algorithm).

show abstract

Section: Recent Related Work: An Overviewmentioning

confidence: 99%

“…The ant's random style decreased with radius of the hyper sphere to model this conduct. Equations (23) and (24) , current iteration specifies t , maximum number of iterations specifies S and constant whose value represents w . The objective function is computed in this step.…”

Section: ) the Alo Algorithm For Selecting Optimal Training Datasetmentioning

confidence: 99%

An Effective Technique for Tuning the Time Delay System with PID Controller-Ant Lion Optimizer Algorithm with ANN Technique

George

Ganesan

2020

IJEAT

View full text Add to dashboard Cite

show abstract

“…Δ PD (jω) has been given by (7). In (16), N E ,N O are the even and odd parts of N respectively, and D E ,D O are the even and odd parts of D, respectively.…”

Section: Pi Controller Designmentioning

confidence: 99%

“…The procedures for determining the complete sets of stabilizing PID controllers are presented for three classes of second-order integrating systems with time delay in [12]. Stabilization by PID controller for second-order unstable processes is performed via the necessary and sufficient criteria of Routh-Hurwitz stability analysis in [16]. Computation of stabilizing PI and PID controllers using the stability boundary locus method is given in [11].…”

Section: Introductionmentioning

confidence: 99%

“…For this example, the PID controller and set point pre-filter based on Cho, Lee, and Edgar [44] are C s ð Þ ¼ 4:7408 1 þ 1 9:1627s þ 1:6975s and F r (s) = (4.6656s 2 +4.32s+1)/(15.5539s 2 +9.1627s+1), respectively. The third-order process is reduced to a second-order form by approximating the third (smallest)time constant in the denominator using the first-order Taylors series, which gives G p1 (s) = e −s /(5s − 1)(2s+1)[16]. The PID controller and set point pre-filter suggested by Seer and Nandong[16] are C 613s+1), respectively.…”

mentioning

confidence: 99%

See 1 more Smart Citation

PI‐PD controller design for time delay systems via the weighted geometrical center method

Özyetkin

Onat

Tan

2019

Asian Journal of Control

View full text Add to dashboard Cite

In this study, a PI‐PD controller tuning method is presented using the weighted geometrical center method, which is based on the calculation of the weighted geometric center of the stability region obtained by the stability boundary locus method. The proposed method for tuning of PI‐PD controller parameters (kd,kf,kp and ki) is performed in three steps. In the first step, the (kd,kf) parameter region for the inner loop with PD controller is obtained, and then the weighted geometric center of this region is calculated. In the second step, the inner PD loop is reduced to a single block using the numerical values of (kd,kf) that are obtained in the first step. Then, the (kp,ki) values of the external loop with PI controller are determined by the same procedure. This tuning method has some advantages over other tuning methods in terms of simplicity and robustness. The simulation examples show that a PI‐PD controller designed using the proposed method provides good performance results when compared to other tuning methods presented in the literature.

show abstract

Optimal design of non‐fragile PID controller

Elsisi

2019

Asian Journal of Control

View full text Add to dashboard Cite

This paper solves the controller gains uncertainty problem, which may lead to undesirable responses and an unstable system when implemented. A non‐fragile or resilient controller can overcome this problem. The paper suggests a new method to design a non‐fragile proportional‐integral‐derivative (PID) controller for voltage regulation. This method is carried out by applying a constrained genetic algorithm (GA) as a powerful optimization technique to determine the optimal gains of the PID controller. In addition, new developed conditions from the Routh– Kharitonov theorem are taken into account during the optimization operation to ensure system stability and system response. A new time domain objective function is proposed to establish the optimal permissible limits of controller gains to ensure a constraint of good response. The results of the proposed non‐fragile PID controller are compared with the non‐constrained GA‐based PID controller, artificial bee colony (ABC) algorithm‐based PID controller, and Ziegler Nichols (ZN)‐based PID controller. This achieves better results compared with different methods. The controller gains uncertainties test is applied to ensure the non‐fragility of the proposed controller. Furthermore, the system parameters variation test is applied to check the robustness of the controller based on the suggested method. The designed PID controller by this method is more resilient and less design time is required. The proposed controller and the system are carried out and studied by utilizing MATLAB/Simulink.

show abstract

Stabilization and PID tuning algorithms for second-order unstable processes with time-delays

Cited by 45 publications

References 24 publications

An Effective Technique for Tuning the Time Delay System with PID Controller-Ant Lion Optimizer Algorithm with ANN Technique

An Effective Technique for Tuning the Time Delay System with PID Controller-Ant Lion Optimizer Algorithm with ANN Technique

PI‐PD controller design for time delay systems via the weighted geometrical center method

Optimal design of non‐fragile PID controller

Contact Info

Product

Resources

About