Stabilization of mobile inverted pendulum using fuzzy PID controllers

Paliwal, Sankalp; Chopra, Vikram; Singla, Sunil Kumar

doi:10.1109/iicpe.2016.8079537

Cited by 4 publications

(2 citation statements)

References 8 publications

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“…Two fuzzy-PI controllers adjust PI parameters with two control inputs, and the third input adapts to satisfy the controlling condition of Equation (26).…”

Section: Simulation Resultsmentioning

confidence: 99%

“…Fuzzy logic can be used in control systems which cannot be easily or accurately modeled [23] to eliminate the uncertainties of the system [24] or to encompass the nonlinearities of the system [25]. The most straightforward way to increase robustness of systems with determined systematic feedback is to use a fuzzy logic supervisor for coefficients of a simple proportional-integral-derivative (PID) controller [26]. In control systems, the Fuzzy-PI controller uses fuzzy logic algorithms to effectively eliminate the steady state error by adaptively adjusting proportional and integral coefficients of PI controller [27].…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

An Underactuated Bio-Inspired Helical Swimming Microrobot Using Fuzzy-PI Controller with Novel Error Detection Method for 5-DOF Micromanipulation

Pourmand

Taghvaei

Vatankhah

et al. 2018

Designs

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The potential of microrobots to bring about revolutionary changes over micro-operation demands is increasing day to day. This paper presents a controller to provide 5 degrees of freedom for an underactuated bio-inspired helical swimming microrobot. The considered system is a helical swimming microrobot with three flagella in a low Reynolds performance environment. Control of the considered system is performed to reach any desired location, roll angle and pitch angle. The proposed controlling error definition extracted from the system geometry is general for similar actuation configurations. An error detection method for multi-propulsion-unit systems is utilized for 5-DOF micromanipulation of an underactuated bio-inspired helical swimming microrobot by fuzzy-PI controller. A fuzzy-PI controller is proposed to use modified experimental data of PI controller debugging to maintain a suitable efficient control. The comparison of two other possible controllers and the proposed fuzzy-PI controller is discussed, and the performance of trajectory tracking is evaluated by simulations.

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“…Two fuzzy-PI controllers adjust PI parameters with two control inputs, and the third input adapts to satisfy the controlling condition of Equation (26).…”

Section: Simulation Resultsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%