Dealing with a LQR controller surface subject to power and torque constraints, is an issue of nonlinear problem that is difficult to implement. This paper employs a fuzzy controller surface to replace the LQR surface subject to power and torque constraints by using class stacking, least square and Sugenotype fuzzy inference mode. Through this type of transformation, called “Optimal fuzzy contro...

We review the example of linear quadratic regulator (LQR) problem given in paper[2] by A. Chapelon and C.-Z. Xu. We discuss three different algebraic Riccati equations that are associated to such LQR problems.

In this paper we present a set of projection-based designs for constructing simplified linear quadratic regulator (LQR) controllers for large-scale network systems. When such systems have tens of thousands of states, the design of conventional LQR controllers becomes numerically challenging, and their implementation requires a large number of communication links. Our proposed algorithms bypass ...

In this paper, a mathematical model of flexible single link robotic manipulator that has a rotational base and translational motion has been developed using lagrangian method. The control strategies like PID, LQR and State feedback controller have been implemented for controlling the tip position of flexible single link robotic manipulators through MATLAB. State feedback controller uses pole pl...

This paper presents a method to solve the constrained infinite-time linear quadratic regulator (LQR) problem. We use an operator splitting technique, namely the alternating minimization algorithm (AMA), to split the problem into an unconstrained LQR problem and a projection step, which are solved repeatedly, with the solution of one influencing the other. The first step amounts to the solution ...

This paper addresses linear quadratic regulation (LQR) for variable speed variable pitch wind turbines. Because of the inherent nonlinearity of wind turbine, a set of operating conditions is identified and then a LQR controller is designed for each operating point. The feedback controller gains are then interpolated linearly to get control law for the entire operating region. Besides, the aerod...

A quadcopter control system is a fundamentally difficult and challenging problem because its dynamics modelling highly nonlinear, especially after accounting for the complicated aerodynamic effects. Plus, variables are interdependent coupled in nature. There six controllers studied analysed this work which (1) Proportional–Integral–Derivative (PID), (2) Proportional-Derivative (PD), (3) Linear ...

In this article, we discuss the design and implementation of a receding horizon control (RHC) which will be used to represent the control for the baroreceptor loop in the human cardiovascular system (CVS). This control will be applied to a model of the CVS developed in a previous work by Kappel and Peer. In that earlier work, a linear quadratic control strategy (LQR) was implemented to represen...

Design of power system stabilizer using Linear Quadratic Regulator (LQR) technique. Designs that ignore noise in a plant are likely to fail when implemented in actual conditions. Presence of the noise, which results in LQR output oscillating with very small magnitude. This type of unwanted noisy output is eliminated using Linear Quadratic Gaussian (LQG) Regulator. This paper presents techniques...

This study presents a Linear Quadratic Optimal (LQR) controller design for an inverted pendulum on a cart using the Artificial Bee Colony (ABC) algorithm. Main design parameters of the linear quadratic regulator are the weighting matrices. Generally, selecting weighting matrices is managed by trial and error since there exists no apparent connection between these weights and time domain require...