Search results

Filters

  • Journals
  • Authors
  • Keywords
  • Date
  • Type

Search results

Number of results: 5
items per page: 25 50 75
Sort by:
Download PDF Download RIS Download Bibtex

Abstract

The time delay element present in the PI controller brings dead-time compensation capability and shows improved performance for dead-time processes. However, design of robust time delayed PI controller needs much responsiveness for uncertainty in dead-time processes. Hence in this paper, robustness of time delayed PI controller has been analyzed for First Order plus Dead-Time (FOPDT) process model. The process having dead-time greater than three times of time constant is very sensitive to dead-time variation. A first order filter is introduced to ensure robustness. Furthermore, integral time constant of time delayed PI controller is modified to attain better regulatory performance for the lag-dominant processes. The FOPDT process models are classified into dead-time/lag dominated on the basis of dead-time to time constant ratio. A unified tuning method is developed for processes with a number of dead-time to time constant ratio. Several simulation examples and experimental evaluation are exhibited to show the efficiency of the proposed unified tuning technique. The applicability to the process models other than FOPDT such as high-order, integrating, right half plane zero systems are also demonstrated via simulation examples.
Go to article

Bibliography

[1] A. Ingimundarson and T. Hagglund: Robust tuning procedures of deadtime compensating controllers. Control Engineering Practice, 9(11), (2001), 1195–1208, DOI: 10.1016/s0967-0661(01)00065-x.
[2] A. O’Dwyer: Handbook of PI and PID Controller Tuning Rules. Imperial College Press, London. 2006.
[3] A.R. Pathiran and J. Prakash: Design and implementation of a modelbased PI-like control scheme in a reset configuration for stable single-loop systems. The Canadian Journal of Chemical Engineering, 92(9), (2014), 1651–1660, DOI: 10.1002/cjce.22014.
[4] B.D. Tyreus and W.L. Luyben: Tuning PI controllers for integrator/dead time processes. Industrial & Engineering Chemistry Research, 31(11), (1992), 2625–2628, DOI: 10.1021/ie00011a029.
[5] D. Efimov, A. Polyakov, L. Fridman,W. Perruquetti, and J.P. Richard: Delayed sliding mode control. Automatica, 64 (2016), 37–43, DOI: 10.1016/j.automatica.2015.10.055.
[6] D.E. Rivera, M. Morari, and S. Skogestad: Internal model control: PID controller design. Industrial & Engineering Chemistry Process Design and Development, 25(1), (1986), 252–265, DOI: 10.1021/i200032a041.
[7] F. Gao, M. Wu, J. She, and Y. He: Delay-dependent guaranteedcost control based on combination of Smith predictor and equivalentinput- disturbance approach. ISA Transactions, 62, (2016), 215–221, DOI: 10.1016/j.isatra.2016.02.008.
[8] F.G. Shinskey: PID-deadtime control of distributed processes. Control Engineering Practice, 9(11), (2001), 1177–1183. DOI: 10.1016/s0967- 0661(01)00063-6.
[9] F.G. Shinskey: Process Control Systems – Application, Design, and Tuning. McGraw-Hill, New York. 1998.
[10] I.L. Chien: IMC-PID controller design-an extension. IFAC Proceedings, 21(7), (1988), 147–152, DOI: 10.1016/s1474-6670(17)53816-1.
[11] J. Lee and T.F. Edgar: Improved PI controller with delayed or filtered integral mode. AIChE Journal, 48(12), (2002), 2844–2850, DOI: 10.1002/aic.690481212.
[12] J. Na, X. Ren, R. Costa-Castello, and Y. Guo: Repetitive control of servo systems with time delays. Robotics and Autonomous Systems, 62(3), (2014), 319–329, DOI: 10.1016/j.robot.2013.09.010.
[13] J.E. Normey-Rico, C. Bordons and E.F. Camacho: Improving the robustness of dead-time compensating PI controllers. Control Engineering Practice, 5(6), (1997), 801–810, DOI: 10.1016/s0967-0661(97)00064-6.
[14] J.E.Normey-Rico, R. Sartori, M. Veronesi, and A. Visioli: An automatic tuning methodology for a unified dead-time compensator. Control Engineering Practice, 27, (2014), 11–22, DOI: 10.1016/j.conengprac.2014.02.001.
[15] J.E. Normey-Rico, R.C.C. Flesch, T.L.M. Santos and E.F. Camacho: Comments on A novel dead time compensator for stable processes with long dead times. Journal of Process Control, 22(7), (2012), 1404–1407, DOI: 10.1016/j.jprocont.2012.05.009.
[16] K. Kirtania and M.A.A.S. Choudhury: A novel dead time compensator for stable processes with long dead times. Journal of Process Control, 22(3), (2012), 612–625, DOI: 10.1016/j.jprocont.2012.01.003.
[17] K.J. Astrom and T. Hagglund: Advanced PID Control. Instrument Society of America, Research Triangle Park, N.C. 2006.
[18] K.J. Åstrom and T. Hagglund: The future of PID control. Control Engineering Practice, 9(11), (2001), 1163–1175, DOI: 10.1016/s0967- 0661(01)00062-4.
[19] R. Arun, R. Muniraj, and M.S. Willjuice Iruthayarajan: A new controller design method for single loop internal model control systems. Studies in Informatics and Control, 29(2), (2020), 219–229, DOI: 10.24846/v29i2y202007.
[20] R. Gudin and L. Mirkin: On the delay margin of dead-time compensators. International Journal of Control, 80(8), (2007), 1316–1332, DOI: 10.1080/00207170701316616.
[21] T. Hagglund: An industrial dead-time compensating PI controller. Control Engineering Practice, 4(6), (1996), 749–756, DOI: 10.1016/0967- 0661(96)00065-2.
[22] W.K. Ho, C.C. Hang, and L.S. Cao: Tuning of PID controllers based on gain and phase margin specifications. Automatica, 31(3), (1995), 497–502, DOI: 10.1016/0005-1098(94)00130-b.
[23] X. Sun, J. Xu, and J. Fu: The effect and design of time delay in feedback control for a nonlinear isolation system, Mechanical Systems and Signal Processing, 87, (2017), 206–217, DOI: 10.1016/j.ymssp.2016.10.022.
[24] Y. Wang, F. Yan, S. Jiang, and B. Chen: Time delay control of cabledriven manipulators with adaptive fractional-order nonsingular terminal sliding mode. Advances in Engineering Software, 121, (2018), 13–25, DOI: 10.1016/j.advengsoft.2018.03.004.
Go to article

Authors and Affiliations

Arun R. Pathiran
1
R. Muniraj
2
ORCID: ORCID
M. Willjuice Iruthayarajan
3
ORCID: ORCID
S.R. Boselin Prabhu
4
T. Jarin
5
ORCID: ORCID

  1. Department of Electrical and Electronics Technology, Ethiopian Technical University, Addis Ababa, Ethiopia
  2. Department of Electrical and Electronics Engineering, P.S.R. Engineering College, Sivakasi, Virudhunagar District, Tamilnadu, India
  3. Department of Electrical and Electronics Engineering, National Engineering College, Kovilpatti, India
  4. Department of Electronics and Communication Engineering, Surya Engineering College, Mettukadai, India
  5. Department of Electrical and Electronics Engineering, Jyothi Engineering College, Thrissur, India
Download PDF Download RIS Download Bibtex

Abstract

Disturbance rejection performance optimization with constraints on robustness for a multivariable process is commonly encountered in industrial control applications. This paper presents the tuning of a multi-loop Proportional Integral (PI) controller method to enhance the performance of load disturbance rejection using evolutionary optimization. The proposed design methodology is formulated to minimize the load disturbance rejection response and the input control energy under the constraints of robust stability. The minimum singular value of multiplicative uncertainty is considered a multi-loop system robust stability indicator. Optimization is performed to achieve the same, or higher level than the most-explored Direct Synthesis (DS) based multi-loop PI controller, which is derived from a conventional criterion. Simulation analysis clearly proved that the proposed multi-loop PI controller tuning method gives better disturbance rejection, and either, the same or a higher level of robust stability when compared to the DS-based multi-loop PI controller.
Go to article

Authors and Affiliations

R. Arun
1
ORCID: ORCID
R. Muniraj
2
ORCID: ORCID
S.R. Boselin Prabhu
3
ORCID: ORCID
T. Jarin
4
ORCID: ORCID
M. Willjuice Iruthayarajan
5
ORCID: ORCID

  1. Department of Electrical and Electronics Engineering, SriSivasubramaniya Nadar College of Engineering, Chennai, India
  2. Department of Electrical and Electronics Engineering, P.S.R Engineering College, Sivakasi, India
  3. Department ofElectronics and Communication Engineering, Surya Engineering College, India
  4. Department of Electrical and Electronics Engineering, Jyothi Engineering College, Thrissur, India
  5. Department of Electrical andElectronics Engineering, National Engineering College, Kovilpatti, India
Download PDF Download RIS Download Bibtex

Abstract

A Novel Intelligent control of a Unified Power Quality Conditioner (UPQC) coupled with Photovoltaic (PV) system is proposed in this work. The utilization of a Re-lift Luo converter in conjunction with a Cascaded Artificial Neural Network (ANN) Maximum Power Point Tracking (MPPT) method facilitates the optimization of power extraction from PV sources. UPQC is made up of a series and shunt Active Power Filter (APF), where the former compensates source side voltage quality issues and the latter compensates the load side current quality issues. The PV along with a series and shunt APFs of the UPQC are linked to a common dc-bus and for regulating a dc-bus voltage a fuzzy tuned Adaptive PI controller is employed. Moreover, a harmonics free reference current is generated with the aid of CNN assisted dq theory in case of the shunt APF. The results obtained from MATLAB simulation.
Go to article

Authors and Affiliations

Ramesh Rudraram
1
Sasi Chinnathambi
1
Manikandan Mani
2

  1. Electrical Engineering Department, Annamalai University, Annamalainagar, India
  2. Electrical and Electronics Engineering Department, Jyothishmathi Institute of Technology and Science, Karimnagr, Telangana, India
Download PDF Download RIS Download Bibtex

Abstract

The paper is a structured, in-depth analysis of dual active bridge modeling. In the research new, profound dual active bridge converter (DAB) circuit model is presented. Contrary to already described idealized models, all critical elements including numerous parasitic components were described. The novelty is the consideration of a threshold voltage of diodes and transistors in the converter equations. Furthermore, a lossy model of leakage inductance in an AC circuit is also included. Based on the circuit equations, a small-signal dual active bridge converter model is described. That led to developing control of the input and output transfer function of the dual active bridge converter model. The comparison of the idealized model, circuit simulation (PLECS), and an experimental model was conducted methodically and confirmed the high compatibility of the introduced mathematical model with the experimental one. Proposed transfer functions can be used when designing control of systems containing multiple converters accelerating the design process, and accurately reproducing the existing systems, which was also reported in the paper.
Go to article

Authors and Affiliations

Roman Barlik
1
Piotr Grzejszczak
1
Mikołaj Koszel
1

  1. Warsaw University of Technology, Warsaw, Poland
Download PDF Download RIS Download Bibtex

Abstract

Establishing the proper values of controller parameters is the most important thing to design in active queue management (AQM) for achieving excellent performance in handling network congestion. For example, the first well known AQM, the random early detection (RED) method, has a lack of proper parameter values to perform under most the network conditions. This paper applies a Nelder-Mead simplex method based on the integral of time-weighted absolute error (ITAE) for a proportional integral (PI) controller using active queue management (AQM). A TCP flow and PI AQM system were analyzed with a control theory approach. A numerical optimization algorithm based on the ITAE index was run with Matlab/Simulink tools to find the controller parameters with PI tuned by Hollot (PI) as initial parameter input. Compared with PI and PI tuned by Ustebay (PIU) via experimental simulation in Network Simulator Version 2 (NS2) in five scenario network conditions, our proposed method was more robust. It provided stable performance to handle congestion in a dynamic network.

Go to article

Authors and Affiliations

Misbahul Fajri
Kalamullah Ramli

This page uses 'cookies'. Learn more