This article presents a neural algorithm based on Reinforcement Learning for optimising Linear Quadratic Regulator (LQR) creation. The proposed method allows designing such target function that automatically leads to changes in the quality and resource matrix so LQR regulator achieves desired performance. solution’s stability optimality are controller’s responsibility. However, mechanism obtain...

In this report a number of algorithms for optimal control of a double inverted pendulum on a cart (DIPC) are investigated and compared. Modeling is based on Euler-Lagrange equations derived by specifying a Lagrangian, difference between kinetic and potential energy of the DIPC system. This results in a system of nonlinear differential equations consisting of three 2-nd order equations. This sys...

This paper presents an LQR-Based 6DOF control of an unmanned aerial vehicles (UAV), namely a small-scale quadrocopter. Due to its high nonlinearity and a high degree of coupling system, the control of an UAV is very challenging. quadrocopter trajectory tracking in a 3D space is greatly affected by the quadrocopter balancing around its roll-pitch-yaw frame. Lack of precise tracking control about...

State-of-the-art approaches in quadrotor control split the problem into multiple cascaded subproblems, exploiting the different time scales of the rotational and translational dynamics. They calculate a desired acceleration as input for a cascaded attitude controller but omit the attitude dynamics. These approaches use limits on the desired acceleration to maintain feasibility and robustness th...

1 John Watkins, Systems Engineering Department, U.S. Naval Academy, 105 Maryland Ave, Annapolis, MD 21402 [email protected] 2 Eugene Mitchell, Systems Engineering Department, U.S. Naval Academy, 105 Maryland Ave, Annapolis, MD 21402 [email protected] Abstract  The optimal Linear Quadratic Regulator (LQR) method is a powerful technique for designing controllers for comple...

A framework for the design and simulation of a building envelope and an HVAC system is used to compare advanced control algorithms in terms of energy efficiency, thermal comfort, and computational complexity. Building models are first captured in Modelica [1] to leverage Modelica’s rich building component library and then imported into Simulink [15] to exploit Simulink’s strong control design e...

The rotary inverted pendulum system was a highly nonlinear model, multivariable and absolutely unstable dynamic system. This paper presents hybrid control method for swing up and LQR control method for the stabilization. The flexibility of the hybrid control method based on the selection of heuristic swing up controller and energy swing up controller at the different positions of pendulum. The ...

This paper presents the design of optimal controller for nonlinear Rotary Inverted Pendulum (RIP) dynamic system using Linear Quadratic Regulator (LQR). LQR, an optimal control technique is generally used for control of the linear dynamical systems, have been used in this paper to control the non linear dynamical system. The non linear system states are fed to LQR which is designed using linear...