A5065278245- Advanced Control Systems Design
- Fuzzy Logic and Control Systems
- Magnetic Bearings and Levitation Dynamics
- Fuzzy Systems and Optimization
- Frequency Control in Power Systems
- Advanced Control Systems Optimization
- Extremum Seeking Control Systems
- Vehicle Dynamics and Control Systems
- Inertial Sensor and Navigation
- Hydraulic and Pneumatic Systems
- Tribology and Lubrication Engineering
- Particle accelerators and beam dynamics
- Advanced Data Processing Techniques
- Advanced Algorithms and Applications
- Fractional Differential Equations Solutions
- Engineering and Technology Innovations
- Electric Motor Design and Analysis
- Neural Networks and Applications
Kyungpook National University
2023-2024
Indian Institute of Technology Kharagpur
2017-2022
Birla Institute of Technology, Mesra
2016
In this paper, the design of a Proportional-Integral-Derivative (PID) controller for cruise control system has been proposed. The system, which is highly nonlinear, linearized around equilibrium point. designed model, by taking dominant pole concept in closed loop characteristic equation. PID parameters, i.e. proportional, integral and derivative parameters have tuned using Genetic Algorithm (GA). study, performance compared with that conventional PID, state space Fuzzy logic based...
This article is about the design of controllers for magnetic levitation (Maglev) system in both simulation and real time. Local linearization around equilibrium point has been done nonlinear Maglev to obtain a linearized model transfer function. In this study, integral-tilted-derivative (I-TD) controller proposed its performance compared with conventional tilted-integral-derivative (TID) controller. TID parameters have optimized through genetic algorithm (GA) those set values employed I-TD A...
Designing a suitable controller for nonlinear and unstable plant is always very challenging to the control system practitioners. In this article, Integral - Proportional Derivative (I-PD) has been designed implemented in simulation real time Magnetic levitation (Maglev) which both nature. The Maglev linearized around equilibrium point obtain model transfer function. objective function, formulated by taking modulus of characteristic polynomial along with at dominant pole location, minimized...
In this paper, 1-Degree of Freedom (1-DOF) and 2-Degree (2-DOF) Integer Order (IO) Fractional (FO) Proportional–Integral–Derivative (PID) Controller has been designed for the Magnetic Levitation (Maglev) system. Maglev is one most versatile research-oriented laboratory instruments in field control systems engineering. The controller system such a way that ferromagnetic ball can precisely levitate controlled electromagnetic with particular design specifications. parameters be appropriately...
Over the last three decades, finding mathematical models of fuzzy controllers has become an interesting area research in control community. The model a controller gives clear insight into analytical structure and helps to understand problem framework well-defined theory. Because modelling computational complexities, from literature, it seems authors that three-input PID rarely been attempted using Center Gravity (CoG) defuzzification. purpose present manuscript is unveil exact nonlinear CoG...
Designing a controller for the Twin Rotor MIMO System (TRMS) is challenging task due to presence of high non-linearity and cross-coupling between different elements. In this paper, Fractional Order Integral–Proportional Derivative (FOI-PD) has been realized implemented in both simulation real-time control pitch yaw angle TRMS. The novelty present work lies implementation robust FOI-PD controller, which not yet explored by researchers TRMS kit best authors' knowledge. nonlinear interior point...
The purpose of this manuscript is to show the applicability a recently developed simplest fuzzy PI/PD controller in simulation and real-time. An unstable plant with large time-delay controlled using PI controller, nonlinear magnetic levitation system real-time help PD controller. results are compared existing usefulness newly designed
In the last fifteen years, field of fuzzy controller modeling has witnessed a substantial transformation as research focus been switched from type-1 (T1) controllers to type-2 (T2) and interval (IT2) ones. Due complexity, however, only few models IT2 proportional-integral-derivative (IT2FPID) are found in literature, with majority them Mamdani type. Further, no existing work deals mathematical Takagi-Sugeno (TS) fractional order IT2FPID controllers. To bridge this gap, present study develops...
From the literature, it appears that combination of Mamdani Minimum (MM) inference and Centre Area (CoA) defuzzification was rarely used for modelling Simplest Fuzzy (SF) two-term (PI/PD) controllers. In this work, to reduce gap, mathematical models three SF controllers are unveiled via MM CoA defuzzification. Apart from modelling, properties newly derived analysed. Finally, illustrate applicability developed in article, a simulation example real-time study provided.
From the last decade, modelling of Interval Type-2 (IT2) fuzzy controllers has become an exciting area research in field control systems engineering. The input-output relationship controller gives insights into exact structure controller. literature, it is observed that IT2 handle plant uncertainty a better way than their Type 1 (T1) counterparts due to presence additional Degree Freedom (DoF) provided by Footprint Uncertainty (FoU) present membership functions Fuzzy Sets (IT2FSs). Further,...