Log in

Relevant bibliographies by topics / PID-Fuzzy hybrid controller

Contents

Journal articles

Academic literature on the topic 'PID-Fuzzy hybrid controller'

Author: Grafiati

Published: 4 June 2021

Last updated: 1 February 2022

Create a spot-on reference in APA, MLA, Chicago, Harvard, and other styles

Select a source type:

Consult the lists of relevant articles, books, theses, conference reports, and other scholarly sources on the topic 'PID-Fuzzy hybrid controller.'

Next to every source in the list of references, there is an 'Add to bibliography' button. Press on it, and we will generate automatically the bibliographic reference to the chosen work in the citation style you need: APA, MLA, Harvard, Chicago, Vancouver, etc.

You can also download the full text of the academic publication as pdf and read online its abstract whenever available in the metadata.

Journal articles on the topic "PID-Fuzzy hybrid controller"

1

S.R. Krishnam Naidu, R., and U. Salma. "Real- time implementation of parallel type fuzzy- PID controller for effective control of hybrid Pole self bearing Switched reluctance motor." International Journal of Engineering & Technology 7, no. 2.21 (2018): 112. http://dx.doi.org/10.14419/ijet.v7i2.21.11847.

Full text

Abstract:

This paper presents a hybrid intelligent and design in a real time for the rapid prototyping of a robust fuzzy controller along with conventional Proportional– Integral and Derivative (PID) controller that allows quick insight of these integrated designs. The design procedure of the parallel fuzzy PID and its combination with the traditional PID in a universal control scheme are extended. The structural design of the parallel fuzzy PID controller is composed of three fuzzy sub controllers which are connected in parallel. These parallel sub controllers are assembled to get the proposed parallel fuzzy type PID controller. The hybrid fuzzy PID gains are expressed in the error domain. Hence, the structural design presents an alternative to control schemes employed so far. This hybrid intelligent controller is formulated and executed in real world hardware for position as well as speed control of a Hybrid Pole Self Bearing Switched Reluctance Motor (HPSBSRM) drive system. The design of the parallel fuzzy PID controller, implementation and finally analysis all are carried out using MATLAB/Simulink environment. Software results concluded that the novel hybrid intelligent parallel fuzzy PID controller generates better control action when compared to traditional PID controller, predominantly in system nonlinearities and in external load variations.

APA, Harvard, Vancouver, ISO, and other styles

2

Wibawa, Hari, Oyas Wahyunggoro, and Adha Imam Cahyadi. "DC Motor Speed Control Using Hybrid PID-Fuzzy with ITAE Polynomial Initiation." IJITEE (International Journal of Information Technology and Electrical Engineering) 3, no. 1 (2019): 7. http://dx.doi.org/10.22146/ijitee.46590.

Full text

Abstract:

DC motors are widely applied in industrial sector, especiallyprocesses of automation and robotics. Given its role in the sector, DC motor operation needs to be optimized. One of optimization steps is controlling speed using several control methods, for example conventional PID methods, PID Ziegler Nichols, PID based on ITAE polynomials, and Hybrid PID-Fuzzy. From these methods, Hybrid PID-Fuzzy was chosen as a method to be proposed in this paper because it can anticipate shortcomings of PID controllers and fuzzy controllers so as to produce system responses that are fast and adaptive to errors. This paper aimed to design a Hybrid PID-Fuzzy system based on ITAE polynomials (Hybrid-ITAE), to analyze its performance parameters values, and tp compare Hybrid-ITAE performance with conventional PID method. Working parameters being reviewed include overshoot, rise time, settling time, and ITAE. First of all, JGA25-370 DC motor was modeled in a form of a third order transfer function equation. Based on the transfer function, PID parameters were calculated using PID Output Feedback and ITAE polynomial methods. The best ITAE polynomial PID controllers were then be combined with a Fuzzy Logic Controller to form a Hybrid-ITAE system. Simulation and experimental stages were carried out in two conditions, namely no load and loaded. Simulation and experimental results showed that Hybrid-ITAE (l = 0.85) was the best controller for no-load simulation conditions. For loaded simulation Hybrid-ITAE (l=1) was a better controller. In no-loads experiment, the best controller was Hybrid PID-Ziegler Nichols, while for loaded condition the best controller was Hybrid PID-Ziegler Nichols.

APA, Harvard, Vancouver, ISO, and other styles

3

Zheng, Xue Qin. "Control of Hybrid Stepping Motor Drive Using Computational Verb PID Controllers." Advanced Materials Research 853 (December 2013): 428–34. http://dx.doi.org/10.4028/www.scientific.net/amr.853.428.

Full text

Abstract:

Thanks to the development of microprocessors, hybrid stepping motors have been widely used in many areas where they perform positioning operations. However, the stepping motor suffers from system variations, low performance and lack of adaptability to load variations, which slow down their responding speed of high-precision positioning operations. In this paper, a computational verb PID controller is proposed to control the position of a stepping motor drive. The simulation results show that the computational verb PID controller has better performances than conventional and fuzzy PID controllers. The simulation results also show that the responding speed and positioning accuracy of the controlled hybrid stepping motor were greatly improved. Computational verb PID controller has much less computational complexity than fuzzy PID controller.

APA, Harvard, Vancouver, ISO, and other styles

4

Sun, Lan. "Fuzzy Self-Tuning PID Controller in SEHS." Applied Mechanics and Materials 214 (November 2012): 765–70. http://dx.doi.org/10.4028/www.scientific.net/amm.214.765.

Full text

Abstract:

Because of the existing hybrid fuzzy PID controller does not perform, using electric hydraulic servo system application (SEHS). Therefore, when the system parameters change will require a new adjustment of PID controller variable. Therefore, a hybrid fuzzy and fuzzy self-tuning PID control was put forward. With this control scheme was divided into two parts, and the fuzzy controller and fuzzy self-tuning PID controller. Fuzzy controller is used to control the output of the system of the values of the system away from target value. We proved that the performance of the control scheme through the experiment of the motor speed control SEHS. The experimental results show that the proposed a hybrid fuzzy PID controller and fuzzy self-tuning effect is better than that of a hybrid fuzzy and PID controller.

APA, Harvard, Vancouver, ISO, and other styles

5

Dong, Li Hong. "Application of Hybrid Fuzzy-PID Control with Coupled Rules in the Hydraulic Positioning System." Applied Mechanics and Materials 220-223 (November 2012): 402–5. http://dx.doi.org/10.4028/www.scientific.net/amm.220-223.402.

Full text

Abstract:

According to the nonlinearity and time-variation of the positioning control in hydraulic system, a kind of Hybrid Fuzzy-PID Controller with Coupled Rules (HFPIDCR) is proposed. In this control system, the bulk modulus is considered as a variable. The novelty of this controller is to combine the fuzzy logic and PID controllers in a switching condition. Simulation results of the HFPIDCR are compared with the results of traditional PID, Fuzzy Logic Controller (FLC), and Hybrid Fuzzy-PID Controller (HFPID). It is demonstrated that the HFPIDCR has fast response, short adjustment time, high control precision and other advantages, and it can meet the requirements of the positioning control in hydraulic system.

APA, Harvard, Vancouver, ISO, and other styles

6

Zhang, Sheng Yi, and Xin Ming Wang. "Study of Fuzzy-PID Control in MATLAB for Two-Phase Hybrid Stepping Motor." Applied Mechanics and Materials 341-342 (July 2013): 664–67. http://dx.doi.org/10.4028/www.scientific.net/amm.341-342.664.

Full text

Abstract:

two-phase hybrid stepping motor is widely used for driving part in industry controlling, the research for control algorithm applied in stepping motor becomes more and more important. The mathematic model of the two-phase hybrid stepping motor and the structure of Fuzzy-PID controller are detailed, and the simulation model of Fuzzy-PID controller in MATLAB/simulink is also founded. Finally, the simulation is done separately for a conventional PID controller and the Fuzzy-PID controller, and the result shows that the setting time and the maximum overshoot value is greatly reduced for the fuzzy-PID controller, and the performance of fuzzy-PID controller is better than conventional PID algorithm.

APA, Harvard, Vancouver, ISO, and other styles

7

Zhang, Da Wei, Yan Ling Tian, and Bing Yan. "Application of Hybrid Fuzzy PID Control to Auxiliary Workpiece Table." Materials Science Forum 471-472 (December 2004): 264–68. http://dx.doi.org/10.4028/www.scientific.net/msf.471-472.264.

Full text

Abstract:

In order to eliminate the non-linearity of a grinding auxiliary workpiece table, a hybrid fuzzy PID controller has been developed. The two-dimensional fuzzy control with self-tuning factor is utilized to improve the performance. The Max-Min inference mechanism and COG defuzzification method are used to obtain the crisp output of the fuzzy controller. To eliminate the oscillation at balance position, the conventional PID controller is used in the small range of the error and the switch between two controllers can automatically realize according the preset value. Simulation and experimental testing have been carried out to validate the performance of the hybrid fuzzy PID controller.

APA, Harvard, Vancouver, ISO, and other styles

8

Chen, Minyou, and D. A. Linkens. "A hybrid neuro-fuzzy PID controller." Fuzzy Sets and Systems 99, no. 1 (1998): 27–36. http://dx.doi.org/10.1016/s0165-0114(96)00401-0.

Full text

APA, Harvard, Vancouver, ISO, and other styles

9

Lal, Deepak Kumar, and Ajit Kumar Barisal. "Grasshopper Algorithm Optimized Fractional Order Fuzzy PID Frequency Controller for Hybrid Power Systems." Recent Advances in Electrical & Electronic Engineering (Formerly Recent Patents on Electrical & Electronic Engineering) 12, no. 6 (2019): 519–31. http://dx.doi.org/10.2174/2352096511666180717142058.

Full text

Abstract:

Background: Due to the increasing demand for the electrical power and limitations of conventional energy to produce electricity. Methods: Now the Microgrid (MG) system based on alternative energy sources are used to provide electrical energy to fulfill the increasing demand. The power system frequency deviates from its nominal value when the generation differs the load demand. The paper presents, Load Frequency Control (LFC) of a hybrid power structure consisting of a reheat turbine thermal unit, hydropower generation unit and Distributed Generation (DG) resources. Results: The execution of the proposed fractional order Fuzzy proportional-integral-derivative (FO Fuzzy PID) controller is explored by comparing the results with different types of controllers such as PID, fractional order PID (FOPID) and Fuzzy PID controllers. The controller parameters are optimized with a novel application of Grasshopper Optimization Algorithm (GOA). The robustness of the proposed FO Fuzzy PID controller towards different loading, Step Load Perturbations (SLP) and random step change of wind power is tested. Further, the study is extended to an AC microgrid integrated three region thermal power systems. Conclusion: The performed time domain simulations results demonstrate the effectiveness of the proposed FO Fuzzy PID controller and show that it has better performance than that of PID, FOPID and Fuzzy PID controllers. The suggested approach is reached out to the more practical multi-region power system. Thus, the worthiness and adequacy of the proposed technique are verified effectively.

APA, Harvard, Vancouver, ISO, and other styles

10

Narmadha, T. Velayudham, Chackaravarthy Baskaran, and K. Sivakumar. "Comparison of Performance Measures of Speed Control for a DC Motor Using Hybrid Intelligent Controller and Optimal LQR." Applied Mechanics and Materials 622 (August 2014): 23–31. http://dx.doi.org/10.4028/www.scientific.net/amm.622.23.

Full text

Abstract:

-In this paper , performance of fuzzy PD , fuzzy PI , fuzzy PD+I , fuzzy PID controllers are evaluated and compared. This paper also describes the speed control based on Linear Quadratic Regulator (LQR) technique. The comparison is based on their ability of controlling the speed of DC motor, which merely focuses on performance index of the controllers, and also time domain specifications such as rise time, settling time and peak overshoot. The controller is modelled using MATLAB software, the simulation results shows that the fuzzy PID controllers are the best performing candidates in all aspects but it as higher overshoot and IAE in comparison with optimal LQR. The Fuzzy PI controller exhibited null offset but suffers from poor stability and peak overshoot, whereas the fuzzy PD controller has fast rise time, with no overshoots but the IAE is much greater. Thus, the comparative analysis recommends fuzzy PID controller but it is usually associated with complicated rule base and tedious tuning. To circumvent these problems, the proposed LQR controller gives better performance than the other controllers.

APA, Harvard, Vancouver, ISO, and other styles

More sources

We offer discounts on all premium plans for authors whose works are included in thematic literature selections. Contact us to get a unique promo code!