Application of sampled data LQR control scheme for grid tie inverter

Abstract This paper is concerned with sampled-data leader following consensus of multiple unmanned surface vehicle (MUSV) systems with random switching network topologies and wave-induced disturbance. By modelling the switching of network topologies with the use of a Markov process and considering the effect of wave-induced disturbance, a new sampled-data consensus control protocol is proposed. By employing an appropriate Lyapunov-Krosovskii function method and the weak infinitesimal operation, a novel stability criterion is derived, which ensures that the MUSV system can reach robustly leader-following consensus with H∞ performance satisfied. Based on this criterion, the Markov dependent switching consensus controller gains are obtained by solving a set of linear matrix inequalities. Finally, an illustrative example is given to verify the effectiveness of the proposed control scheme for MUSV systems.

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A Hybrid Adaptive Control Scheme Using Sampled Data and Intersampling Compensation

IFAC Proceedings Volumes ◽

10.1016/s1474-6670(17)48247-4 ◽

1993 ◽

Vol 26 (2) ◽

pp. 169-172

Author(s):

Jing Sun

Keyword(s):

Adaptive Control ◽

Sampled Data ◽

Control Scheme ◽

Hybrid Adaptive Control ◽

Adaptive Control Scheme

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FULL-AND REDUCED- ORDER COMPENSATOR FOR INNOSAT ATTITUDE CONTROL

Jurnal Teknologi ◽

10.11113/jt.v76.5883 ◽

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.

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An Adaptively Controlled Electrohydraulic Servo-Mechanism: Part 1: Adaptive Controller Design

Proceedings of the Institution of Mechanical Engineers Part B Management and engineering manufacture ◽

10.1243/pime_proc_1987_201_064_02 ◽

1987 ◽

Vol 201 (3) ◽

pp. 175-180 ◽

Cited By ~ 16

Author(s):

K A Edge ◽

K R A Figueredo

Keyword(s):

Adaptive Control ◽

Controller Design ◽

Control Design ◽

Adaptive Controller ◽

Adaptive Control System ◽

Sampled Data ◽

Robust Controller ◽

Servo Mechanism ◽

Control Scheme ◽

Model Reference Adaptive

A systematic model reference adaptive control design scheme is presented. The control scheme is developed and analysed within the framework of a sampled data system with a parameter adaptive algorithm designed on the basis of hyper stability theory. A number of supervisory functions are used to supplement the basic adaptive control system in order to enhance robust controller action.

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