This paper deals with the Cross-Entropy method application in the control theory. The method is a the combinatorial optimization technique that is mostly used in the networks theory and could be used in deterministic optimization problems as well. The paper shows the possibiliy of the Cross-Entropy usage in the control parameter tuning. Similar to genetics algorithms, this method minimizes a gi...

The research on two-wheels balancing robot has gained momentum due to their functionality and reliability when completing certain tasks. This paper presents investigations into the performance comparison of Linear Quadratic Regulator (LQR) and PID-PID controllers for a highly nonlinear 2–wheels balancing robot. The mathematical model of 2-wheels balancing robot that is highly nonlinear is deriv...

The problem of state feedback control design is conventionally handled by pole assignment or Linear Quadratic Regulator (LQR) method via Algebraic Riccati Equation (ARE). However, these methods still suffer from the disadvantage of trial and error approach for parameter tuning. To be specific, selecting the weighting matrices Q and R of LQR has to be done by trial and error approach. Hence to a...

A current source converter (CSC) based static synchronous compensator (STATCOM) is a shunt flexible AC transmission system (FACTS) device, which has a vital role as a stability support for small and large transient instability in an interconnected power network. A robust linear quadratic regulator (LQR) based controller for CSCSTATCOM is proposed. In this paper, LQR based CSC-STATCOM is designe...

 The ADRC tuning is essentially a pole-placement technique and the desired performance is indirectly achieved through the location of the closed-loop poles. However, the final choice of these poles becomes a trial-and-error strategy. In contrast with pole-placement, in the LQR method, the desired performance objectives are directly and globally addressed by minimizing a quadratic function of ...

In this paper an infinite-dimensional LQR control-based design for a system containing linear hyperbolic partial differential equations coupled with linear ordinary differential equations is presented. The design is based on an infinite-dimensional Hilbert state-space representation of the coupled system. The feedback control gain is obtained by solving algebraic and differential matrix Riccati...

We present a new walking controller based on 3LP, a 3D model of bipedal walking that is composed of three pendulums to simulate falling, swing and torso dynamics. Taking advantage of linear equations and closed-form solutions of 3LP, the proposed controller projects intermediate states of the biped back to the beginning of the phase for which a discrete LQR controller is designed. After the pro...

This paper describes the LMI synthesis of feedback controllers which minimise closed loop transient perturbation growth with limited control effort. Controllers are synthesized for the linearised Lorenz equations, and their performance is compared to that of LQR controllers. At low control effort the controllers behave similarly, but the LMI based controllers are able to produce an almost monot...

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...

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...