Reduced order linear quadratic regulator controller for voltage multiplier cells integrated boost converter

2016 ◽  
Vol 10 (6) ◽  
pp. 536-548 ◽  
Author(s):  
Mangaiyarkarasi Palaveashem ◽  
Kavitha Anbukumar
Keyword(s):  
Linear Quadratic Regulator ◽  
Boost Converter ◽  
Linear Quadratic ◽  
Reduced Order ◽  
Order Linear ◽  
Voltage Multiplier ◽  
Integrated Boost

COMPARISON OF HYSTERESIS CONTROL AND REDUCED ORDER LINEAR QUADRATIC REGULATOR CONTROL FOR POWER FACTOR CORRECTION USING DC–DC CUK CONVERTERS

2012 ◽  
Vol 21 (01) ◽  
pp. 1250002 ◽  
Author(s):  
M. G. UMAMAHESWARI ◽  
G. UMA ◽  
S. REDLINE VIJITHA
Keyword(s):  
Power Factor ◽  
Power Factor Correction ◽  
Linear Quadratic Regulator ◽  
Voltage Regulation ◽  
Experimental Results ◽  
Linear Quadratic ◽  
Reduced Order ◽  
Order Linear ◽  
Hysteresis Controller ◽  
Set Up

This paper focuses on a comparative study of a reduced order linear quadratic regulator control (ROLQR) and conventional variable frequency hysteresis controller (HC) for power factor correction, and their performances are compared. A prototype of front-end AC–DC converter followed by DC–DC Cuk converter controlled by a dSPACE signal processor was set up for 60 watts. Experimental results are presented to validate the simulation results. Simulation and experimental results reveal that ROLQR control can achieve good output voltage regulation and also provide improved robustness in shaping the input current in the presence of load variations when compared to conventional HC.

scholarly journals DYNAMICS BASED CONTROL OF A SKID STEERING MOBILE ROBOT

2016 ◽  
Vol 9 (2) ◽  
pp. 70 ◽  
Author(s):  
Osama Elshazly ◽  
Hossam Abbas ◽  
Zakarya Zyada
Keyword(s):  
Mobile Robot ◽  
Inverse Dynamics ◽  
Linear Quadratic Regulator ◽  
Nonlinear Controller ◽  
Linear Quadratic ◽  
Reduced Order ◽  
Lqr Control ◽  
Control Schemes ◽  
Skid Steering ◽  
Drive Model

In this paper, development of a reduced order, augmented dynamics-drive model that combines both the dynamics and drive subsystems of the skid steering mobile robot (SSMR) is presented. A Linear Quadratic Regulator (LQR) control algorithm with feed-forward compensation of the disturbances part included in the reduced order augmented dynamics-drive model is designed. The proposed controller has many advantages such as its simplicity in terms of design and implementation in comparison with complex nonlinear control schemes that are usually designed for this system. Moreover, the good performance is also provided by the controller for the SSMR comparable with a nonlinear controller based on the inverse dynamics which depends on the availability of an accurate model describing the system. Simulation results illustrate the effectiveness and enhancement provided by the proposed controller.

FULL-AND REDUCED- ORDER COMPENSATOR FOR INNOSAT ATTITUDE CONTROL

2015 ◽  
Vol 76 (12) ◽  
Author(s):  
Fadzilah Hashim ◽  
Mohd Yusoff Mashor ◽  
Siti Maryam Sharun
Keyword(s):  
State Space ◽  
Attitude Control ◽  
Space Form ◽  
Transfer Functions ◽  
Linear Quadratic Regulator ◽  
Linear Quadratic ◽  
Reduced Order ◽  
Lqr Control ◽  
Best Value ◽  
Control Scheme

This paper presents a study on the estimator based on Linear Quadratic Regulator (LQR) control scheme for Innovative Satellite (InnoSAT). By using LQR control scheme, the controller and the estimator has been derived for state space form in all three axes to stabilize the system’s performance. This study starts by converting the transfer functions of attitude control into state space form.  Then, the step continues by finding the best value of weighting matrices of LQR in order to obtain the best value of controller gain, K. After that, the best value of L is obtained for the estimator gain. The value of K and L is combined in forming full order compensator and in the same time the reduced order compensator is also formed. Lastly, the performance of full order compensator is compared to reduced order compensator. From the simulation, results indicate that both types of estimators have presented good stability and tracking performance. However, reduced order estimator has simpler equation and faster convergence to zero than the full order estimator. This property is very important in developing a satellite attitude control for real-time implementation.

scholarly journals Hybrid Controller Based on LQR Applied to Interleaved Boost Converter and Microgrids under Power Quality Events

Energies ◽  
2021 ◽  
Vol 14 (21) ◽  
pp. 6909
Author(s):  
Gerardo Humberto Valencia-Rivera ◽  
Ivan Amaya ◽  
Jorge M. Cruz-Duarte ◽  
José Carlos Ortíz-Bayliss ◽  
Juan Gabriel Avina-Cervantes
Keyword(s):  
Renewable Energy Sources ◽  
Real Life ◽  
Linear Quadratic Regulator ◽  
Boost Converter ◽  
Optimal Operation ◽  
Gray Wolf ◽  
Linear Quadratic ◽  
Photovoltaic Array ◽  
Hybrid Controller ◽  
Interleaved Boost Converter

Renewable energy sources are an environmentally attractive idea, but they require a proper control scheme to guarantee optimal operation. In this work, we tune different controllers for an Interleaved Boost Converter (IBC) powered by a photovoltaic array using three metaheuristics: Genetic Algorithm, Particle Swarm Optimization, and Gray Wolf Optimization. We also develop several controllers for a second simulated scenario where the IBC is plugged into an existing microgrid (MG) as this can provide relevant data for real-life applications. In both cases, we consider hybrid controllers based on a Linear Quadratic Regulator (LQR). However, we hybridize it with an Integral action (I-LQR) in the first scenario to compare our data against previously published controllers. In the second one, we add a Proportional-Integral technique (PI-LQR) as we do not have previous data to compare against to provide a more robust controller than I-LQR. To validate our approach, we run extensive simulations with each metaheuristic and compare the resulting data. We focus on two fronts: the performance of the controllers and the computing cost of the solvers when facing practical issues. Our results demonstrate that the approach proposed for tuning controllers is a feasible strategy. The controllers tuned with the metaheuristics outperformed previously proposed strategies, yielding solutions thrice faster with virtually no overshoot and a voltage ripple seven times smaller. Not only this, but our controllers could correct some issues liaised to the IBC when it is plugged into an MG. We are confident that these insights can help migrate this approach to a more diverse set of MGs with different renewable sources and escalate it to real-life experiments.

scholarly journals Feedback Control Methods for a Single Machine Infinite Bus System

2020 ◽  
Author(s):  
Pratik Vernekar ◽  
Zhongkui Wang ◽  
Andrea Serrani ◽  
Kevin Passino
Keyword(s):  
Single Machine ◽  
Linear Models ◽  
Linear Quadratic Regulator ◽  
Pole Placement ◽  
High Fidelity ◽  
Nonlinear Feedback ◽  
Linear Quadratic ◽  
Reduced Order ◽  
System P ◽  
Single Machine Infinite Bus

In this manuscript, we present a high-fidelity physics-based truth model of a Single Machine Infinite Bus (SMIB) system. We also present reduced-order control-oriented nonlinear and linear models of a synchronous generator-turbine system connected to a power grid. The reduced-order control-oriented models are next used to design various control strategies such as: proportional-integral-derivative (PID), linear-quadratic regulator (LQR), pole placement-based state feedback, observer-based output feedback, loop transfer recovery (LTR)-based linear-quadratic-Gaussian (LQG), and nonlinear feedback-linearizing control for the SMIB system. The controllers developed are then validated on the high-fidelity physics-based truth model of the SMIB system. Finally, a comparison is made of the performance of the controllers at different operating points of the SMIB system.

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