This paper deals with modelling, identification and simulation of the inverted pendulum PS600. This system is unstable and nonlinear with one input – voltage of a DC motor which can change position of the cart and two outputs – cart position and angle of the pendulum rod. First, a mathematical model of the inverted pendulum is derived, followed by identification of its unknown parameters. Then,...

A cart-pole inverted pendulum system is one of the underactuated systems that has been used in many applications. This research aims to study design and effectiveness Adaptive Super-Twisting controller stabilize by comparing it with other previous control methods. stabilization upright using algorithm (ASTA), was investigated. The proposed designed based on decoupling method solve coupled input...

In control applications, to apply the results obtained by evolutions and simulations to real systems, it is indispensable for them to have high robustness in computer simulations. The goal of this study is to generate robust control equations for controlling the real system of a rolling inverted pendulum with Genetic Programming. The control equations for this system must swing a pole up from a...

friction is a nonlinear phenomenon which has destructive effects on performance of control systems. to obviate these effects, friction compensation is an effectual solution. in this paper, an adaptive technique is proposed in order to eliminate limit cycles as one of the undesired behaviors due to presence of friction in control systems which happen frequently. the proposed approach works for n...

In this paper we present a novel decoupled fuzzy sliding mode (DFSM) strategy for swinging-up an inverted pendulum. In the proposed technique the control objective is decomposed into two sub-tasks, i.e., swing-up and stabilization. Accordingly, first a DFSM controller stabilizing the pole is synthesized and optimised via genetic algorithms. Next, a DFSM controller with a piecewise linear slidin...

This paper introduces an evolutionary algorithm that is tailored to generate recurrent neural networks functioning as nonlinear controllers. Network size and architecture, as well as network parameters like weights and bias terms, are developed simultaneously. There is no quantization of inputs, outputs or internal parameters. Different kinds of evolved networks are presented that solve the pol...

Presents a recurrent neural network for solving the Sylvester equation with time-varying coefficient matrices. The recurrent neural network with implicit dynamics is deliberately developed in the way that its trajectory is guaranteed to converge exponentially to the time-varying solution of a given Sylvester equation. Theoretical results of convergence and sensitivity analysis are presented to ...

This paper presents stability analysis of fuzzy model-based nonlinear control systems, and the design of nonlinear gains and feedback gains of the nonlinear controller using a genetic algorithm (GA) with arithmetic crossover and nonuniform mutation. A stability condition is derived based on Lyapunov's stability theory with a smaller number of Lyapunov conditions. A solution of the stability con...

The stabilization of an inverted pendulum on a manually controlled cart (cart-inverted-pendulum; CIP) in an upright position, which is analogous to balancing a stick on a fingertip, is considered in order to investigate how the human central nervous system (CNS) stabilizes unstable dynamics due to mechanical instability and time delays in neural feedback control. We explore the possibility that...

This paper investigates the design and analysis of three controllers used to stabilize an inverted pendulum on a cart. This is accomplished by decomposing each control algorithm into two separate phases: swing-up control and stabilization control. A classical, H2, and H∞ design are each considered to stabilize a nominal linearized model of the inverted pendulum on a cart in the upward vertical ...