Liang Xiaoyin, Qu Beimin · 2002
The paper introduces in detail the derivation of a control algorithm. In this algorithm, a fuzzy controller is applied to the PID control method and a self-optimal regulating factor is added to the control rule, thus the controller not only has quick dynamic response and allows overswing properties of the fuzzy controller, but also has the high stationary precision property of the PID controller. Because of the adoption of self-optimal regulation, a faster and robust design is obtained and the dynamic response and robustness of the controller are strengthened.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">></ETX>
Cited by 3
Christian Mayr · 2021
Cited by 0
Han Jiang · 1994
In the paper, by using the nonlinear Tracking-Differentiator and nonlinear combination, we improve the classical PID regulator in order to enhance its adaptability and robustness.
Cited by 96
Algirdas Baškys, V. Zlosnikas · Proceedings of the Annual Conference of the IEEE Industrial Electronics Society · 2006
The controller for plants that are characterized by the different dynamics during the rise and decay of the plant output parameter has been suggested and analyzed. The control algorithm used in the proposed controller is modification of the PID control method. The characteristic property of the algorithm is that parameters of the controller are changed when the sign of the error changes. This feature enables achieving good response of the analyzed control system in case of plants with the asymmetric dynamics. The results of the investigation of the concrete control system based on the proposed controller are presented. The investigation was performed using the electronic circuit simulation program Spice
Cited by 13
Hélène Panagopoulos · Lund University Publications (Lund University) · 1998
[abstract missing]
Cited by 86Open access
Macháček, Jiří, Drábek, Oldřich, Krejčí, Stanislav · Digitální knihovna Univerzity Pardubice (Univerzity Pardubice) · 1995
The Ziegler–Nichols method was used for the testing of controller parameters. The ultimate (critical) gain and period have been calculated from the discrete model of the szstem obtained from on-line identification. The application of the adaptive controller has been made with good results on distillation column.
Cited by 0Open access
Gribble, J.J., Chen, W-H., Ballance, D.J. · ENLIGHTEN (Jurnal Bimbingan dan Konseling Islam) · 1999
A new class of nonlinear PID controllers are derived for nonlinear systems using a nonlinear generalised predictive control (NGPC) approach. First, the disturbance decoupling ability of the NGPC is discussed. For a nonlinear system where the disturbance cannot be decoupled, a nonlinear observer is designed to estimate the offset. By selecting the nonlinear gain function in the observer, it is shown that the closed-loop system under optimal generalised predictive control with the nonlinear observer is asymptotically stable. It is pointed out that this composite controller is equivalent to a nonlinear controller with integral action. As a special case, for a nonlinear system with a low relative degree, the proposed nonlinear controller reduces to a nonlinear PI or PID predictive controller, which consists of a nonlinear PI or PID controller and a prediction controller. The design method is illustrated by an example nonlinear mechanical system
Cited by 0
Amil Daraz (9667034), Suheel Abdullah Malik (9667037), Ihsan Ul Haq (9667040) et al. · Figshare · 2020
Cited by 0Open access
Toru Yamamoto · Advances in industrial control · 2012
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Hassan Kazemian · Mathematical modelling: theory and applications · 2007
Cited by 11
Minh Tri Nguyen · Theseus (Ammattikorkeakoulujen) · 2021
The brushless DC motors have an unlimited number of applications nowadays, many of which require the motor speeds to be controlled. The PID controllers is the answer for the mentioned problem. This project implemented a PID algorithm to regulate a brushless DC motor speed using a programmed microcontroller unit. \nIn this project, a NUCLEO-152RE development board was used as a controller unit and a X-NUCLEO-IHM07M1 expansion board served as a motor driver and power \nunit. The selected BLDC motor was the Nanotec DF45M024053-A2 model coming \nwith the hall-effect sensors. This project was built based on C Embedded Project using Atollic TrueSTUDIO 9.3.0 IDE. It implemented a six-step algorithm serving the purpose of driving the BLDC motor and PID algorithm to control the motor speed. \nThe results yielded showed that the PID controller eliminated the need of manual \ncontrol (by human) but slightly decreased the system stability. The impact of PID controller also decreased with an increasing target speed value due to the maximum angular acceleration of the motor.
Cited by 0Open access
Adel Taeib, Abdelkader Châari · International Journal of Modelling Identification and Control · 2015
In this paper, a novel design method for determining the optimal proportional-integral-derivative (PID) controller parameters for nonlinear multiple-input multiple-output (MIMO) system using the particle swarm optimisation (PSO) algorithm is presented. Firstly, a nonlinear system was described based on Takagi-Sugeno (T-S) fuzzy models. Assuming that the antecedent parameters of T-S models were kept, the consequent parameters were identified online by using the weighted recursive least square (WRLS) method. Secondly, the identified parameters of fuzzy model were used to directly receive the model predicted output with direct iterative for the T-S model. The fast tuning of optimum PID controller parameters yields high-quality solution. In order to assist estimating the performance of the proposed PSO-PID controller, a new time-domain performance criterion function was also defined. Finally, the application results for continuous stirred tank reactor (CSTR) process show that the proposed algorithm is an effective control strategy with excellent tracing ability.
Cited by 13
M. Sami Fadali, Edwin E. Yaz · 2005
This paper presents a new method for designing robust multivariable PID controllers using LQR high gain feedback. The paper relates output PID feedback to PI state feedback to derive conditions for stable infinite zeros at high gain. The finite zeros of the PID system are also characterized. The high gain design is obtained by choosing stable finite zeros.
Cited by 0
이인범 · Open Access System for Information Sharing (Pohang University of Science and Technology) · 2018
Cited by 0
Black Alvares · Zenodo (CERN European Organization for Nuclear Research) · 2024
Cited by 0Open access
Igor Vinko · Repository of Faculty of Mechanical Engineering and Naval Architecture University of Zagreb · 2010
U radu je obrađen analogni PID regulator, s naglaskom na izradu elektroničkog sklopovlja, te njihovu primjenu u simulaciji i regulaciji objekta upravljanja (toplinska staza i/ili HIL model). Prikazani su postupci dobivanja parametara korištenih za simulacije u programskim paketima MATlab i NI Multisim, pri cemu je MATlab korišten za inicijalnu simulacijsku sintezu sustava upravljanja, a NI Multisim je korišten za provjeru funkcionalnosti skloplovlja PID regulatora. Nakon izrade funkcionalnih simulacijskih modela i zadovoljavajucih simulacijskih odziva pristupilo se izradi tiskanih pločica, upoznavanju izvedbe pojedinih dijelova, te testiranju izrađenog sklopovlja i snimanju odziva (na digitalnom osciloskopu) regulatora i objekta upravljanja na različite step pobude.
Cited by 0
Kshitiz Agarwal · 2015
Abstract: PID Controller is used for tuning of three constants (P,I&amp;D).It stabilize the system by reducing oscillations and settling time. In the proposed method, new tuning rules based on the exact satisfaction of gain and phase margin specifications using proportional-integral (PI) and proportional-integral-differential (PID) type controllers are used for unstable first-order plus dead-time (UFOPDT) processes. The tuning rules are given in the form of iterative algorithms, as well as in the form of accurate, analytical approximations. Moreover, several specific functions, related to the crossover frequencies of the Nyquist plot and to the feasible design specifications for a given process, are derived. These functions, which are particularly useful for the general design of PI and PID-type controllers for UFOPDT processes are accurately approximated, in order to simplify the tuning procedure. With the proposed approximations, the tuning rules require relatively small computational effort and are particularly useful for online applications.
Cited by 0
Özgür Cemil Özkan · Istanbul Technical University Academic Open Archive (Istanbul Technical University) · 2005
Tez (Yüksek Lisans) -- İstanbul Teknik Üniversitesi, Fen Bilimleri Enstitüsü, 2005
Cited by 0Open access
D. Uduehi, Andrzej Ordys, M.J. Grimble · 2002
A polynomial predictive optimal control problem is discussed for the discrete time system where the structure of the controller is assumed to be limited to a discrete PID controller. The theoretical problem to be considered is to obtain the causal, stabilising, controller of the pre-specified PID form that minimises a generalised predictive control criterion and is equivalent to a GPC control law. The underlying practical problem and aim of the work is to obtain the optimal PID controller coefficients that provide the required closed loop performance over a range of operating conditions and working points.
Cited by 4
R. Devanathan, Chan Chee Keong, T.L. Kin et al. · 2003
The authors report on the development of an expert PID (proportional-integral-differential) controller for industrial processes. It uses the optimal property of a certain region in the P, I, and D parameter space providing minimum integrated (average) error when the required damping is ensured otherwise. The expert system uses an algorithm which basically modifies the settings of a conventional real-time PID controller continually until the parameters enter the optimum region mentioned above. The optimum region for a given process depends on the characterization of that process which is carried out in a simple indentification procedure prior to convergence. The authors describe the theory, the algorithm used, the hardware, and the software aspects of the implementation of the expert system as well as the test results obtained on a simulated process control system.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">></ETX>
Cited by 8