Faculty Publications

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    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.
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    Variable speed wind turbine for maximum power capture using adaptive fuzzy integral sliding mode control
    (2014) RAJENDRAN, S.; Jena, D.
    This paper presents a nonlinear control approach to variable speed wind turbine (VSWT) with a wind speed estimator. The dynamics of the wind turbine (WT) is derived from single mass model. In this work, a modified Newton Raphson estimator has been considered for exact estimation of effective wind speed. The main objective of this work is to extract maximum energy from the wind at below rated wind speed while reducing drive train oscillation. In order to achieve the above objectives, VSWT should operate close to the optimal power coefficient. The generator torque is considered as the control input to achieve maximum energy capture. From the literature, it is clear that existing linear and nonlinear control techniques suffer from poor tracking of WT dynamics, increased power loss and complex control law. In addition, they are not robust with respect to input disturbances. In order to overcome the above drawbacks, adaptive fuzzy integral sliding mode control (AFISMC) is proposed for VSWT control. The proposed controller is tested with different types of disturbances and compared with other nonlinear controllers such as sliding mode control and integral sliding mode control. The result shows the better performance of AFISMC and its robustness to input disturbances. In this paper, the discontinuity in integral sliding mode controller is smoothed by using hyperbolic tangent function, and the sliding gain is adapted using a fuzzy technique which makes the controller more robust. © 2014, The Author(s).
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    Validation of an integral sliding mode control for optimal control of a three blade variable speed variable pitch wind turbine
    (Elsevier Ltd, 2015) RAJENDRAN, S.; Jena, D.
    Reduction in cost of wind energy requires most efficient control technology which can able to extract optimum power from the wind. This paper mainly focuses on the control of variable speed variable pitch wind turbine (VSVPWT) for maximization of extracted power at below rated wind speed (region 2) and regulation of extracted power when operating at above rated wind speed (region 3). To extract maximum power at below rated wind speed torque control is used whereas to regulate rated power at above rated wind speed pitch control is used. In this paper a nonlinear control i.e. integral sliding mode control (ISMC) is proposed for region 2 whereas a conventional proportional-integral (PI) control is adapted for region 3 of a VSVPWT. The proposed controller is combined with modified Newton Raphson (MNR) wind speed estimator to estimate the wind speed. The stability of the proposed ISMC is analyzed using Lyapunov stability criterion and the control law is derived for region 2 which is also adapted for the transition period between region 2 and region 3 (region 2.5). The dynamic simulations are tested with nonlinear FAST (Fatigue, Aerodynamics, Structures, and Turbulence) wind turbine (WT). The simulation results of ISMC are presented and the control performance is compared with conventional SMC and existing controllers such as aerodynamic torque feed forward control (ATF) and Indirect speed control (ISC). It is seen that especially in region 2.5, ISMC gives better performance compared to all other controllers. © 2015 Elsevier Ltd.
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    Backstepping sliding mode control of a variable speed wind turbine for power optimization
    (2015) RAJENDRAN, S.; Jena, D.
    To optimize the energy capture from the wind, wind turbine (WT) should operate at variable speed. Based on the wind speed, the operating regions of the WT are divided into two parts: below and above the rated wind speed. The main aim at below rated wind speed is to maximize the energy capture from the wind with reduced oscillation on the drive train. At above rated wind speed, the aim is to maintain the rated power by using pitch control. This paper presents the control of WT at below rated wind speed by using backstepping sliding mode control (BSMC). In BSMC, generator torque is considered as the control input that depends on the optimal rotor speed. Usually, this optimal rotor speed is derived from effective wind speed. In this paper, effective wind speed is estimated from aerodynamic torque and rotor speed by using the modified Newton Rapshon (MNR) algorithm. Initially, a conventional sliding mode controller (SMC) is applied to the WT, but the performance of the controller was found to be less robust with respect to disturbances. Generally, WT external disturbance is not predictable. To overcome the above drawback, BSMC is proposed and both the controllers are tested with mathematical model and finally validated with the fatigue, aerodynamics, structures, and turbulence (FAST) WT simulator in the presence of disturbances. From the results, it is concluded that the proposed BSMC is more robust than conventional SMC in the presence of disturbances. © 2015, The Author(s).
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    Nonlinear control of wind turbine with optimal power capture and load mitigation
    (Springer Verlag service@springer.de, 2016) RAJENDRAN, R.; Jena, D.
    The main control objectives associated with the variable speed wind turbine is to extract maximum power at below rated wind speed (region 2) and to regulate the power at above rated wind speed (region 3). This paper proposes a nonlinear framework to achieve the above two control objectives. The paper discusses about the application of an integral sliding mode control (ISMC) in region 2 and a fuzzy based proportional integral (PI) control in region 3. Same ISMC is adopted for the stable switching between operating regions (transition region 2.5) and the control input maintains the continuity at the instant of switching. Lyapunov stability criterion is used to prove the stability of ISMC. The controllers are tested for different wind speed profiles with different turbulence component. Finally the performances of the proposed controllers are tested with nonlinear Fatigue, Aerodynamics, Structures, and Turbulence WT model and the results are compared with the existing baseline + PI controllers. © 2015, Springer-Verlag Berlin Heidelberg.
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    Control Strategy to Maximize Power Extraction in Wind Turbine
    (Taylor and Francis Inc. 325 Chestnut St, Suite 800 Philadelphia PA 19106, 2016) RAJENDRAN, R.; Jena, D.
    This article deals with nonlinear control of variable speed wind turbine (VSWT), where the dynamics of the wind turbine (WT) is obtained from a single mass model. The main objective of this work is to maximize the energy capture form the wind with reduced oscillation on the drive train. The generator torque is considered as the control input to the WT. In general the conventional control techniques such as Aerodynamic Torque Feed-Forward (ATF) and Indirect Speed Control (ISC) are unable to track the dynamic aspect of the WT. To overcome the above drawbacks the nonlinear controllers such Sliding Mode Controller (SMC) and SMC with integral action (ISMC) with the estimation of effective wind speed are proposed. The Modified Newton Raphson (MNR) is used to estimate the effective wind speed from aero dynamic torque and rotor speed. The proposed controller is tested with different wind profiles with the presence of disturbances and model uncertainty. From the results the proposed controller was found to be suitable in maintaining a trade-off between the maximum energy capture and reduced transient on the drive train. Finally both the controllers are validated by using FAST (Fatigue, Aerodynamics, Structures, and Turbulence) WT simulator. © Association of Energy Engineers (AEE).
  • Item
    Intelligent adaptive observer-based optimal control of overhead transmission line de-icing robot manipulator
    (Robotics Society of Japan ar@rsj.or.jp, 2016) Vijay, M.; Jena, D.
    [No abstract available]
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    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 Ltd