Modeling and Stability Enhancement of Wind Turbine using Linear Quadratic Regulator

2020 ◽  
Author(s):  
Shaharyar Yousaf ◽  
Neelam Mughees ◽  
Abdullah Mughees ◽  
Ali Abbas ◽  
Syed Zulqadar Hassan ◽  
...  
Keyword(s):  
Wind Turbine ◽  
Linear Quadratic Regulator ◽  
Linear Quadratic ◽  
Stability Enhancement

Variable Speed Wind Turbine with External Stiffness and Rotor Deviation Observer

2014 ◽  
Vol 661 ◽  
pp. 154-159
Author(s):  
Muhammad Nizam Kamarudin ◽  
Abdul Rashid Husain ◽  
Mohamad Noh Ahmad
Keyword(s):  
Wind Turbine ◽  
Estimation Error ◽  
Linear Quadratic Regulator ◽  
Speed Control ◽  
Observer Design ◽  
System Structure ◽  
Angular Deviation ◽  
Variable Speed ◽  
Linear Quadratic ◽  
Variable Speed Control

Often in prominent literature, the appearance of external stiffness in wind turbine dynamical model has been neglected. The ignorance of external stiffness eliminates the presence of rotor-side angular deviation in the system dynamic. In order to give more practical look of the variable speed control system structure, we develop a linear observer to estimate the rotor angular deviation. We use Linear Quadratic Regulator (LQR) to design the observer gain, as well as the estimation error gain. To facilitate observer design, the system is linearized around its origin by using Jacobian matrix. By using the estimated rotor angular deviation, we design a variable speed control via Lyapunov and Arstein to enhance power output from the turbine.

A novel adaptive-rear axles steering controller for an 8 × 8 combat vehicle

2021 ◽  
pp. 095440622110099
Author(s):  
Moataz Ahmed ◽  
Moustafa El-Gindy ◽  
Haoxiang Lang
Keyword(s):  
Sliding Mode ◽  
Linear Quadratic Regulator ◽  
Rough Terrain ◽  
Lateral Stability ◽  
Linear Quadratic ◽  
Simulation Based ◽  
Combat Vehicle ◽  
Lqr Controller ◽  
Stability Enhancement ◽  
Gain Scheduled

Multi-axle vehicles are widely used in several applications such as transportation, industrial, and military field, because of its higher reliability in comparison with conventional two axles vehicles. Despite that, there is a paucity of research studies that consider lateral stability enhancement of these vehicles, especially on rough terrain. This simulation-based research study fills this gap and introduces a new adaptive Active Rear Steering (ARS) controller that improves the lateral stability of an 8x8 combat vehicle for rough-terrain operation. The developed controller is designed utilizing the Integral Sliding Mode Control theory (ISMC) based on Gain-Scheduled Linear Quadratic Regulator (GSLQR). Besides, the GSLQR control gains are optimized by a Genetic Algorithm (GA) toolbox using a new synthesized cost function to ensure asymptotic stability. Furthermore, a new Adaptive-ISMC (AISMC) is introduced by using genetic programming to generate control equations that can replace the developed high-dimension GSLQR gains and facilitate future hardware implementation. The developed controller is evaluated by performing a series of simulation-based Double Lane Change (DLC) maneuvers on several rough terrains. The evaluation is conducted for both high friction and slippery surfaces at high and moderate speed, consequently. The results show high fidelity and robustness of the developed controller in comparison with a previously designed optimal LQR controller.

scholarly journals Design and Simulation of an LQR-PI Control Algorithm for Medium Wind Turbine

Energies ◽  
2019 ◽  
Vol 12 (12) ◽  
pp. 2248 ◽  
Author(s):  
Kwansu Kim ◽  
Hyun-Gyu Kim ◽  
Yuan Song ◽  
Insu Paek
Keyword(s):  
Numerical Model ◽  
Wind Turbine ◽  
Control Algorithm ◽  
Hybrid Control ◽  
Linear Quadratic Regulator ◽  
Synchronous Generator ◽  
Control Technique ◽  
Pi Control ◽  
Linear Quadratic ◽  
Horizontal Axis Wind Turbine

In this paper, a new linear quadratic regulator (LQR) and proportional integral (PI) hybrid control algorithm for a permanent-magnet synchronous-generator (PMSG) horizontal-axis wind turbine was developed and simulated. The new algorithm incorporates LQR control into existing PI control structures as a feed-forward term to improve the performance of a conventional PI control. A numerical model based on MATLAB/Simulink and a commercial aero-elastic code were constructed for the target wind turbine, and the new control technique was applied to the numerical model to verify the effect through simulation. For the simulation, the performance data were compared after applying the PI, LQR, and LQR-PI control algorithms to the same wind speed conditions with and without noise in the generator speed. Also, the simulations were performed in both the transition region and the rated power region. The LQR-PI algorithm was found to reduce the standard deviation of the generator speed by more than 20% in all cases regardless of the noise compared with the PI algorithm. As a result, the proposed LQR-PI control increased the stability of the wind turbine in comparison with the conventional PI control.

scholarly journals Design and Verification of the LQR Controller Based on Fuzzy Logic for Large Wind Turbine

Energies ◽  
2021 ◽  
Vol 14 (1) ◽  
pp. 230
Author(s):  
Taesu Jeon ◽  
Insu Paek
Keyword(s):  
Fuzzy Logic ◽  
Wind Tunnel ◽  
Wind Turbine ◽  
Wind Tunnel Test ◽  
Linear Quadratic Regulator ◽  
Power Performance ◽  
Linear Quadratic ◽  
Lqr Controller ◽  
Power Region ◽  
Tower Vibration

In this study, a linear quadratic regulator based on the fuzzy logic (LQRF) control algorithm for a variable-speed variable-pitch wind turbine was designed. In addition, to verify the optimum performance of the controller, simulations and wind tunnel tests were conducted. In the simulation, the performances of the proportional-integral (PI) and LQRF algorithms were compared in the transition region and the rated power region. In the wind tunnel test, the applicability of the LQRF algorithm was verified by comparing it with the conventional PI algorithms. The results showed that when compared with the PI control, the proposed LQRF control reduced the tower vibration by up to 12.50% depending on the operating region. Furthermore, the power deviation was reduced by 38.93%. These tests confirmed that the proposed LQRF control increases the power performance and structural stability of wind turbines compared with conventional PI controls.

Analysis of Synchronous Moment for Active Front Steering and a Two Actuated Wheels of Electric Vehicle Based on Dynamic Stability Enhancement

2019 ◽  
Vol 11 (1) ◽  
Author(s):  
Eid. S. Mohamed ◽  
Mh.I. Khalil ◽  
Ahmed A.A. Saad
Keyword(s):  
Linear Quadratic Regulator ◽  
Vehicle Stability ◽  
Linear Quadratic ◽  
Smart Systems ◽  
Active Front Steering ◽  
Lqr Controller ◽  
Optimal Linear ◽  
Vehicle Trajectory ◽  
Stability Enhancement ◽  
Yaw Moment

Active Front Steering (AFS) and Direct Yaw moment Controller (DYC) are the vehicle smart systems to improve the vehicle stability and safety. The AFS uses front wheels Steer-By-Wire (SBW) system. DYC uses Rear Independent in Wheel Actuated Electric Vehicles (RIWA-EVs). It generates yaw moment to correct the vehicle state deviations. The proposed controller algorithm consists of two levels. First level feedback controller evaluate the optimal yaw moment generated to achieve the desired vehicle trajectory motion with minimize the yaw rate and side-slip errors. The second level controller is utilized to allocate the required front steer angle and traction/ regeneration to the RIWA embedded in rear wheels by taking into account the tire slip. An optimal Linear Quadratic Regulator (LQR) controller is designed, and its controller effectiveness is evaluated under various input driving manoeuvres. The results indicate that the integrated AFS/DYC can significantly stabilize the vehicle motion and highly reduce the driver’s workload. The laboratory experiment of AFS subsystem, for adequate actual front steering angle is measured, in order to apply in vehicle model to predict the responses. The results disclose that the RMS can be an effective route to monitor the vehicle stability.

scholarly journals LQR-Based Adaptive Virtual Inertia for Grid Integration of Wind Energy Conversion System Based on Synchronverter Model

Electronics ◽  
2021 ◽  
Vol 10 (9) ◽  
pp. 1022
Author(s):  
Walter Gil-González ◽  
Oscar Danilo Montoya ◽  
Andrés Escobar-Mejía ◽  
Jesús C. Hernández
Keyword(s):  
Wind Turbine ◽  
Linear Quadratic Regulator ◽  
State Variables ◽  
Linear Quadratic ◽  
Turbine Generator ◽  
Generator System ◽  
Worst Case ◽  
Wind Turbine Generator ◽  
Virtual Inertia ◽  
Wind Turbine Generator System

This paper proposes adaptive virtual inertia for the synchronverter model implemented in a wind turbine generator system integrated into the grid through a back-to-back converter. A linear dynamic system is developed for the proposed adaptive virtual inertia, which employs the frequency deviation and the rotor angle deviation of the synchronverter model as the state variables and the virtual inertia and frequency droop gain as the control variables. In addition, the proposed adaptive virtual inertia uses a linear quadratic regulator to ensure the optimal balance between fast frequency response and wind turbine generator system stress during disturbances. Hence, it minimizes frequency deviations with minimum effort. Several case simulations are proposed and carried out in MATLAB/Simulink software, and the results demonstrate the effectiveness and feasibility of the proposed adaptive virtual inertia synchronverter based on a linear quadratic regulator. The maximum and minimum frequency, the rate change of the frequency, and the integral of time-weighted absolute error are computed to quantify the performance of the proposed adaptive virtual inertia. These indexes are reduced by 46.61%, 52.67%, 79.41%, and 34.66%, in the worst case, when the proposed adaptive model is compared to the conventional synchronverter model.

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