According to the existed structure and algorithm of extension controller, proposed an improved extension control algorithm based on the Optimal Control, which was named LQR-EC, and applied to a SIMO system—Crane-Double Pendulum System. And, using MATLAB simulation platform to study the effect of the LQR—EC Algorithm. The result shows that, the LQR-EC Algorithm not only has a simple theory, but ...

Abstract – The modeling and control of 3 Degrees-of-Freedom (DOF) four-rotor rotorcraft is presented in this paper. Optimal control (LQR), LQR with gain scheduling, feedback linearization and sliding-mode control are simulated and tested on an experimental rig. The performance of the individual controllers are compared and discussed. Our simulation showed Sliding Mode Control (SMC) returned the...

An autonomous distributed LQR/APF control algorithm for multiple small spacecraft during simultaneous close proximity operations has been developed. This research contributes to the control of multiple small spacecraft for emerging operation, which may include inspection, assembly, or servicing. A control algorithm is proposed which combines the control effort efficiency of the Linear Quadratic...

This paper proposes novel approaches to design hierarchical decentralized robust controllers for homogeneous linear multi-agent systems (MASs) perturbed by disturbances/noise. Firstly, based on LQR method, we present a systematic procedure to design hierarchical decentralized optimal stabilizing controllers for MASs without disturbances/noise. Next, a method for deriving reduced-order hierarchi...

We present Extended LQR, a novel approach for locally-optimal control for robots with non-linear dynamics and non-quadratic cost functions. Our formulation is conceptually different from existing approaches, and is based on the novel concept of LQR-smoothing, which is an LQR-analogue of Kalman smoothing. Our approach iteratively performs both a backward Extended LQR pass, which computes approxi...

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 ...