This paper addresses the three-axis stabilization of a satellite system in the presence of the gravity gradient and orbital eccentricity. Multivariable non-linear dynamics of the satellite system are converted into three well-known non-linear canonical independent models with unknown parameters. The new model is efficient and practical for designers to implement and analyze different control me...

A novel intelligent multiple-controller framework incorporating a fuzzy-logic based switching supervisor is presented for adaptive control of non-linear systems . The proposed methodology provides the designer with an automated choice of using either: a conventional Proportional-Integral-Derivative (PID) controller, a PID structure based pole (only) placement controller, or a PID structure base...

Abstract: In this paper, a novel combination of unfalsified control and intelligent control is proposed to improve the dynamic performance of an uncertain system. A PID controller, whose parameters are adaptively tuned by switching among members of a given candidate set using observed plant data, is presented and compared with multi-model adaptive control. Two different cost functions are compa...

Abstract. A Fuzzy-PID controller is designed for tracing reference cutting forces in grinding by integrating a high performance fuzzy controller and an easy to use PID controller. When the error of the grinding force is large, in order to respond quickly, the fuzzy controller with a self-tuning factor is adopted and the Max-Proc strategy is also used. This will be good for fuzzy reasoning. If t...

In this study, a black box modeling of the coupledtank system is obtained by using fuzzy sets. The derived model is tested via adaptive neuro fuzzy inference system (ANFIS). In order to achieve a better control performance, the parameters of three different controller types, classical proportional integral controller (PID), fuzzy PID and function tuner method, are tuned by one of the evolutiona...

In this paper the importance of self tuning adaptive PID control scheme for automotive suspension system is explained. The objective of this study is to obtain a mathematical model for the passive and semi-active suspension system for quarter car model. Current automobile suspension system employs springs and damper with fixed coefficient. Vehicle suspension systems are typically rated by their...

The PID trajectory tracking controller for Lagrangian systems shows performance limitation imposed by inverse dynamics according to desired trajectory. Since the equilibrium point cannot be defined for the control system involving performance limitation, we define newly the quasiequilibrium region as an alternative for equilibrium point. This analysis result of performance limitation can guide ...

The objective of this study is to present an offline control of highly non-linear inverted pendulum system moving on a plane inclined at an angle of 10° from horizontal. The stabilisation was achieved using three different soft-computing control techniques i.e. Proportional-integral-derivative (PID), Fuzzy logic and Adaptive neuro fuzzy inference system (ANFIS). A Matlab-Simulink model of the p...

An adaptive radial basis function (RBF) neural network model is developed in this paper for nonlinear systems using the recursive orthogonal least squares (ROLS) algorithm. The model is used in a nonlinear model predictive control (NMPC). The developed adaptive NMPC is applied to a chemical reactor rig. On-line control performance is presented and it demonstrates superiority over the fixed para...

This paper develops an adaptive control method for controlling frequency and voltage of an islanded mini/micro grid (M/µG) using reinforcement learning method. Reinforcement learning (RL) is one of the branches of the machine learning, which is the main solution method of Markov decision process (MDPs). Among the several solution methods of RL, the Q-learning method is used for solving RL in th...