Vinay Kumar Deolia

Bio: Vinay Kumar Deolia is an academic researcher from GLA University. The author has contributed to research in topics: Control theory & Nonlinear system. The author has an hindex of 8, co-authored 43 publications receiving 181 citations.

An Advanced Neuro-Fuzzy Tuned PID Controller for Pitch Control of Horizontal Axis Wind Turbines

Abstract: Modern power systems comprise a variety of generating systems, including conventional thermal power stations and advanced renewable generating sources, one contender being a wind energy conversion system (WECS). Blade pitch control is an important part of the highly non-linear WECS. Many control strategies have been proposed by researchers around the globe. Current research work focuses on developing a control structure for a non-linear pitch control system using an advanced neuro-fuzzy tuned PID (NF-PID) controller. This approach utilizes the simplicity of a PID controller and the power of a soft computing technique like neuro-fuzzy to handle non-linearity. The model in this study is developed on the MATLAB Simulink platform and the obtained simulation results satisfy the requirements of constant output power even if the wind speed input changes abruptly.

Modelling and Analysis Of flexible manipulator: Soft robotics

Abstract: In contrast to conventional rigid-linked robots, soft robotic manipulators can assume a variety of complex morphologies in response to control inputs and gravitational loads. This paper presents a novel technique for modelling flexible robotic manipulators using inverse dynamics. This study provides mathematical modelling of a manipulator robot’s kinematic and dynamic behavior under the influence of nonlinear material properties and a distributed mass payload. The kinematic model is used to develop a control strategy that optimizes the robot’s kinematic performance. The dynamic model takes into account the robot’s pace. The static model, on the other hand, allows for autonomous trajectory tracking in specific situations. In addition, the Simulation of the proposed treatment parallels the evolution of control systems. In this paper, a concise analysis of soft robotics and research in the direction of modelling a flexible manipulator are presented, along with a performance comparison between link 1 and link 2 under varying parameter conditions. Experiments are performed to test the validity of hypotheses

Fuzzy Approximation-Based Adaptive Backstepping Optimal Control for a Class of Nonlinear Discrete-Time Systems With Dead-Zone

Abstract: In this paper, an adaptive fuzzy optimal control design is addressed for a class of unknown nonlinear discrete-time systems. The controlled systems are in a strict-feedback frame and contain unknown functions and nonsymmetric dead-zone. For this class of systems, the control objective is to design a controller, which not only guarantees the stability of the systems, but achieves the optimal control performance as well. This immediately brings about the difficulties in the controller design. To this end, the fuzzy logic systems are employed to approximate the unknown functions in the systems. Based on the utility functions and the critic designs, and by applying the backsteppping design technique, a reinforcement learning algorithm is used to develop an optimal control signal. The adaptation auxiliary signal for unknown dead-zone parameters is established to compensate for the effect of nonsymmetric dead-zone on the control performance, and the updating laws are obtained based on the gradient descent rule. The stability of the control systems can be proved based on the difference Lyapunov function method. The feasibility of the proposed control approach is further demonstrated via two simulation examples.

A 3-10-Ghz low-noise amplifier with wideband LC-ladder matching network

Abstract: Reactive matching is extended to wide bandwidths using the impedance property of LC-ladder filters. In this paper, we present a systematic method to design wideband low-noise amplifiers. An SiGe amplifier with on-chip matching network spanning 3-10 GHz delivers 21-dB peak gain, 2.5-dB noise figure, and -1-dBm input IP3 at 5 GHz, with a 10-mA bias current.

Adaptive NN Tracking Control of Uncertain Nonlinear Discrete-Time Systems With Nonaffine Dead-Zone Input

Abstract: In the paper, an adaptive tracking control design is studied for a class of nonlinear discrete-time systems with dead-zone input. The considered systems are of the nonaffine pure-feedback form and the dead-zone input appears nonlinearly in the systems. The contributions of the paper are that: 1) it is for the first time to investigate the control problem for this class of discrete-time systems with dead-zone; 2) there are major difficulties for stabilizing such systems and in order to overcome the difficulties, the systems are transformed into an n -step-ahead predictor but nonaffine function is still existent; and 3) an adaptive compensative term is constructed to compensate for the parameters of the dead-zone. The neural networks are used to approximate the unknown functions in the transformed systems. Based on the Lyapunov theory, it is proven that all the signals in the closed-loop system are semi-globally uniformly ultimately bounded and the tracking error converges to a small neighborhood of zero. Two simulation examples are provided to verify the effectiveness of the control approach in the paper.

A survey on sliding mode control for networked control systems

Abstract: In the framework of the networked control systems (NCSs), the components are connected with each other over a shared band-limited network. The merits of NCSs include easy extensibility, resource sh...