An adaptive version of growing and pruning RBF neural network has been used to predict the system output and implement Linear Model-Based Predictive Controller (LMPC) and Non-linear Model-based Predictive Controller (NMPC) strategies. A radial-basis neural network with growing and pruning capabilities is introduced to carry out on-line model identification.An Unscented Kal...

Abstract This paper addresses the development of an attitude determination and control system (ADCS) for a sounding rocket using thrust vector (TVC). To design ADCS, non-linear 6 degrees-of-freedom (DoF) model dynamics kinematics is deduced implemented in simulation environment. An optimal controller designed linear quadratic regulator (LQR) with additional integral action (LQI), relying on der...

One of the challenging tasks concerning two wheeled inverted pendulum (TWIP) mobile robot is balancing its tilt to upright position, this is due to its inherently open loop instability. This paper presents an experimental comparison between model based controller and non-model based controllers in balancing the TWIP mobile robot. A Fuzzy Logic Controller (FLC) which is a non-model based control...

The purpose of this paper is to provide a unified presentation of the formulas arising in the discrete-time finite-horizon linear Linear Quadratic Regulator problem, the Linear Quadratic Gaussian problem, the Linear Exponential of Quadratic Gaussian problem, and the minimax Linear Quadratic Gaussian problem. For these classes of optimal control problems, the paper presents formulas for optimal ...

The paper provides a survey of some recent quadratic stability methods for static output feedback robust controller design for linear continuous-time invariant systems with convex polytopic uncertainty and their mutual comparison. Robust controller design is based on linear matrix inequalities (LMIs) conditions and single Lyapunov functions. The presented quadratic stability methods are compare...

This chapter deals with the design of a Fuzzy Logic Controller based Optimal Linear Quadratic Regulator (FC-LQR) for the control of a robotic system. The main idea is to design a supervisory fuzzy controller capable to adjust the controller parameters in order to obtain the desired axes positions under variations of the robot parameters and payload variations. In the advanced control of robotic...

This paper proposes a polynomial chaos based numerical method providing an optimal controller for the linearquadratic regulator (LQR) problem when the parameters in the formulation are uncertain, i.e., a controller minimizing the mean value of the LQR cost function obtained for a certain distribution of the uncertainties which is assumed to be known. The LQR problem is written as an optimality ...

What led to the novel ideas, some of them theoretical, presented in this paper is our highly experimental approach to nonlinear control. We actually designed and fabricated a two-link inverted pendulum, and learned about the relationships and the tradeoffs that exist in such a device. In the context of controlling an inverted pendulum, the novel ideas presented in this paper relate to i) the de...

Abstract: Both the linear moving horizon estimator and controller may be solved by solving a linear quadratic optimal control problem. A primal active set, a dual active set, and an interior point algorithm for solution of the linear quadratic optimal control problem are presented. The major computational effort in all these algorithms reduces to solution of certain unconstrained linear quadrat...