In this paper, robust stabilization of an experimental system is considered. This system consists of a pendulum free to rotate 360 degrees that is attached to a cart. The cart can move in one dimension. The linearized model of the system is used and transformed to a linear diagonal form. The system is separated into slow and fast subsystems. The fast dynamics are treated as a disturbance and th...

This paper presents a neural network approach to controlling nonlinear system. Trial-and-error correlation learning, which is a generally useful method for optimizing parameters, is applied to training a neural controller to balance an inverted pendulum. The controller is simplified by automatically pruning the hidden neurons to only two. Computer simulation shows that the trained neural contro...

In this paper, three controllers, including OFCHA (optimal fuzzy control using hedge algebras – HAs), FCHA (fuzzy control using HAs) and CFC (conventional fuzzy control) are designed. Attention is paid to the stability in the vertical position of a damped-elastic-jointed inverted pendulum subjected to a time-periodic follower force. The different values of the angular coefficient of the followe...

In this paper, the performance of two adaptive observers applied to interconnected systems is studied. The nonlinearity of systems can be written in a fractional form. The first adaptive observer is an adaptive sliding mode observer for a Lipchitz nonlinear system and the second one is an adaptive sliding mode observer having a filtered error as a sliding surface. After comparing their performa...

This paper presents controlling of a class of nonlinear systems with structured and unstructured uncertainties using fuzzy sliding mode control. First known dynamics of the system are eliminated through feedback linearization and then fuzzy sliding mode controller is designed using TS method, based on the Lyapunov method, which is capable of handling uncertainties. There are no signs of the und...

This paper will present a novel method based on harmonic mean, geometric mean, arithmetic mean and root mean square to help reduce fuzzy rules. The objective of the new method proposed is to produce fuzzy models with both a small number of interpretable rules and sufficiently high precision. Comparisons will be made between systems utilizing reduced rules and original rules to verify efficacy o...

In this paper, we present a walking approach for the Nao robot that improves the agility and stability of the robot when walking on a flat surface such as the soccer field used in the Standard Platform League. The gait uses the computationally inexpensive model of an inverted pendulum to generate a target trajectory for the center of mass of the robot. This trajectory is adapted using the obser...

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...

Abstract We consider an experimental system consisting of a pendulum, which is free to rotate 360 degrees, attached to a cart. The cart can move in one dimension. We study the effect of friction on the design and performance of a feedback controller, a linear quadratic regulator, that aim to stabilize the pendulum in the upright position. We show that a controller designed using a simple viscou...

This paper presents the experimental implementation of a gradient-based nonlinear model predictive control (NMPC) algorithm to the swing-up control of a rotary inverted pendulum. The key attribute of the NMPC algorithm used here is that it only seeks to reduce the error at the end of the prediction horizon rather than finding the optimal solution. This reduces the computation load and allows re...