Faculty Publications
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Item Optimal GA based SMC with adaptive PID sliding surface for robot manipulator(Institute of Electrical and Electronics Engineers Inc., 2015) Vijay, M.; Jena, D.Different types of robotic manipulator controllers are developed to acquire dynamic properties and improve the global stability. In this paper a control strategy for robotic manipulator based on the coupling of the Artificial Neuro Fuzzy Inference System (ANFIS) with sliding mode control (SMC) approach has been presented. Initially, the Proportional Integral Derivative (PID) controller has developed for three different control strategies (IATE, ISE and ISTE) using GA. SMC has developed for best optimal criterion by using GA. The main objectives of these controller are to provide stability, good disturbance rejection and small tracking error. Finally, we have trained an ANFIS network, which can generate the adaptive PID control signal to the SMC of robot manipulator. The stability of the system is guaranteed by the checking of the Lyapunov stability theorem. Numerical simulations using the dynamic model of 2 DOF planner rigid robot manipulator with input torque disturbance shows the effectiveness in trajectory tracking problem and disturbance rejection. The simulation results of these controllers are compared with various torque disturbances in terms of path tracking and disturbance rejection. The proposed ANFIS adaptive SMC controller can achieve favorable tracking performance and it is robust with regard to disturbances in input torque. © 2014 IEEE.Item Backstepping terminal sliding mode control of robot manipulator using radial basis functional neural networks(Elsevier Ltd, 2018) Vijay, M.; Jena, D.This paper examines an observer-based backstepping terminal sliding mode controller (BTSMC) for 3 degrees of freedom overhead transmission line de-icing robot manipulator (OTDIRM). The control law for tracking of the OTDIRM is formulated by the combination of BTSMC and neural network (NN) based approximation. For the precise trajectory tracking performance and enhanced disturbance rejection, NN-based adaptive observer backstepping terminal sliding mode control (NNAOBTSMC) is developed. To obviate local minima problem, the weights of both NN observer and NN approximator are adjusted off-line using particle swarm optimization. The radial basis function neural network-based observer is used to estimate tracking position and velocity vectors of the OTDIRM. The stability of the proposed control methods is verified with the Lyapunov stability theorem. Finally, the robustness of the proposed NNAOBTSMC is checked against input disturbances and uncertainties. © 2017 Elsevier LtdItem Enhanced PID Controller for Non-Minimum Phase Second Order plus Time Delay System(De Gruyter peter.golla@degruyter.com, 2019) Patil, P.; Sankar Rao, C.A tuning method is developed for the stabilization of the non-minimum phase second order plus time delay systems. It is well known that the presence of positive zeros pose fundamental limitations on the achievable control performance. In the present method, the coefficients of corresponding powers of s, s2 and s3 in the numerator are equated to ?, ? and ?times those of the denominator of the closed-loop system. The method gives three simple linear equations to get the PID parameter. The optimal tuning parameters ?, ? and ?are estimated by minimizing the Integral Time weighted Absolute Error (ITAE) for servo problem using fminsearch MATLAB solver aimed at providing lower maximum sensitivity function and keeping in check with the stability. The performance under model uncertainty is also analysed considering perturbation in one model parameter at a time using Kharitonov's theorem. The closed loop performance of the proposed method is compared with the methods reported in the literature. It is observed that the proposed method successfully stabilizes and improves the performance of the uncertain system under consideration. The simulation results of three case studies show that the proposed method provides enhanced performance for the set-point tracking and disturbance rejection with improved time domain specifications. © 2019 Walter de Gruyter GmbH, Berlin/Boston.Item Dynamic performance evaluation of automated QFT robust controller for grid-tied fuel cell under uncertainty conditions(Elsevier Ltd, 2020) Gudimindla, H.; K, M.S.Power flow control and peak point tracking are significant in grid-tied renewable energy systems to improve power factor and efficient energy extraction. In this paper, the design of robust controllers for the power electronic converters of the grid-connected PEM fuel cell with thermal modeling is deliberated. Further, the transfer function model of the power electronic converters is derived by considering uncertainty in system parameters. A low complexity algorithm is used to design the converter parameters from the uncertainty range. The proposed robust automated power flow controller is designed to minimize the objective function using a genetic algorithm in the quantitative feedback theory framework. The robustness and disturbance rejection with enhanced transient response of the proposed controller is evaluated under heavy and light loading conditions, DC-link voltage and grid voltage distortion uncertainty conditions are investigated. Finally, comprehensive simulations are performed to validate the proposed controller performance with the existing controller under the above-mentioned uncertainty conditions. © 2020 Elsevier Ltd