AbstractWe consider an LQR optimal control problem with partially unknown dynamics. We propose a new model-based online algorithm to obtain approximation of the dynamics and at same time during single simulation. The iterative is based on mixture Reinforcement Learning techniques. In particular, we use Gaussian distributions represent model uncertainty probabilistic updated each iteration using...

This paper studies the exponential stabilization problem for discrete-time switched linear systems based on a control-Lyapunov function approach. It is proved that a switched linear system is exponentially stabilizable if and only if there exists a piecewise quadratic control-Lyapunov function. Such a converse control-Lyapunov function theorem justifies many of the earlier synthesis methods tha...

The paper presents a fuzzy control based on parallel distributed fuzzy controllers for a heat exchanger. Each subcontroller is LQR designed and provides local optimal solutions. First, a Takagi-Sugeno fuzzy model is employed to represent a system. The stability of the system with the proposed fuzzy controllers is discussed. The simulation results are compared with classical PID control and illu...

We revisit in this paper the discrete-time linear quadratic regulator (LQR) problem from perspective of receding-horizon policy gradient (RHPG), a newly developed model-free learning framework for control applications. provide fine-grained sample complexity analysis RHPG to learn that is both stabilizing and -close optimal LQR solution, our algorithm does not require knowing initialization. Com...

In this paper the mathematical model representing the dynamic of a Unmanned Aerial Vehicle (UAV) is studied in order to analyse its behaviour. In order to stabilize the entire system, linear Quadratic Regulator (LQR) control is used in such a way to set both PD and PID controls in position variables. A set simulation is performed to carry out the results for linear and non linear models. The LQ...

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...

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...

In this paper, a new analytical method to find a near-optimal high gain controller for the non-minimum phase affine nonlinear systems is introduced. This controller is derived based on the closed form solution of the Hamilton-Jacobi-Bellman (HJB) equation associated with the cheap control problem. This methodology employs an algebraic equation with parametric coefficients for the systems with s...