Self-tuned Fuzzy-PD Control for QNET 2.0 Rotary Inverted Pendulum using lab-view
Engr. Amjad Ali1, Arbab Nighat2
1Engr. Amjad Ali, Department of Electronics Engineering, Mehran UET Jamshoro, Pakistan.
2Dr. Arbab Nighat, Department of Electronics Engineering, Mehran UET Jamshoro, Pakistan.
Manuscript received on February 01, 2020. | Revised Manuscript received on February 05, 2020. | Manuscript published on February 30, 2020. | PP: 625-631 | Volume-9 Issue-3, February, 2020. | Retrieval Number: C5323029320/2020©BEIESP | DOI: 10.35940/ijeat.C5323.029320
Open Access | Ethics and Policies | Cite | Mendeley
© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: An Inverted pendulum is a nonlinear system and broadly utilized as automated arm. The challenge is to balance the pendulum that can rotate in only two ways, either to the positive or to the negative direction ±180 Degree. This research work is aiming to design a controller based on self-tuned fuzzy logic and (Fuzzy-PD) for QNET-2.0 Rotary Inverted Pendulum using lab-view. This self-tuned fuzzy PD control is responsible to generate computer based signals for stable outputs and can works on errors. Rotary Inverted pendulum (RIP) is used as real time model where self- tuned fuzzy PD control is applied for stabilization. There are two aspects to the control objectives for the inverted pendulum: swing-up and balance in a typical PD system, the balancing controller is generated using a fuzzy logic controller, instead of the proportional term. the swing-up controller is generated in a standard proportional controller by using a fuzzy logic system, instead of the proportional term. To build Lab-VIEW approaches, a software development technique is used to help programmers produce code that has greater potential to solve a problem as opposed to writing code without a design. This approach also helps make coding more accessible, more flexible, and more changeable. Rotary Inverted pendulum systems were operated and managed by means of the PD module and the Fuzzy PD Module in Lab-VIEW. The fuzzy controllers are added into the system after the design of the standard PD and P controllers. The two types of controllers the fuzzy P and the fuzzy P-D, and the common proportional and standard PD, are finally implemented and evaluated on the actual inverted pendulum hardware, and also the Control system output is compared between two different control methods.
Keywords: Rotary, Inverted Pendulum, Fuzzy Logic, PD control, Self-tuned Fuzzy Controller.