The purpose of this work is to design a neurofuzzy controller, which can be used in a microcomputer to control the position of an electrohydraulic servo actuating primary flight controls. More specifically, an artificial intelligence based neuro-fuzzy controller is synthesized to solve a robust servomechanism problem. Indeed, the artificial intelligence based synthesis of control law provides a...

One of the main challenges in automatic controller synthesis is to develop methods that can successfully be applied for complex tasks. The difficulty is increased even more in the case of settings with multiple interacting agents. We apply the artificial homeostatic hormone system (AHHS) approach, which is inspired by the signaling network of unicellular organisms, to control a system of severa...

H ∞ control problem using a stable nonlinear output feedback controller is presented in this paper. The particular class of nonlinear uncertain systems being considered is characterized in terms of Integral Quadratic Constraints and Global Lipschitz Conditions describing the admissible uncertainty and nonlinearity, respectively. The nonlinear controller is then constructed by including a copy o...

Trajectory tracking is an essential capability of robotics operation in industrial automation. In this article, an artificial neural controller is proposed to tackle trajectory-tracking problem of an autonomous ground vehicle (AGV). The controller is implemented based on fractional order proportional integral derivative (FOPID) control that was already designed in an earlier work. A non-holonom...

Abstract: This paper studies on the design of a nonlinear controller for the looper-tension system in hot strip finishing mills using a static state feedback linearization and an ILQ(Inverse Linear Quadratic) Optimal Control. Nonlinear dynamic equations of the looper-tension system are analytically linearized by a static feedback linearization algorithm with a compensator. A nonlinear controlle...

This paper proposes the application of Neuro-Fuzzy (NF) hybrid system for Sumo Robot (SR) control. This robot is frequently designed by engineering students for robotic competition. As the relation between sensors output signals and motors control pulses is highly nonlinear in SR, soft computing techniques can be used to define this nonlinear relation and control of the robot in a competition r...

This paper introduces a new class of simple nonlinear PID controllers and provides a formal treatment of their stability analysis. These controllers are comprised of a sector-bounded nonlinear gain in cascade with a linear fixed-gain P, PD, PI, or PID controller. Three simple nonlinear gains are proposed: the sigmoidal function, the hyperbolic function, and the piecewise]linear function. The sy...

An artificial neural network can be used as an intelligent controller to control non-linear, dynamic system through learning. It can easily accommodate non-linearities and time dependencies. Most common multi-layer feed-forward neural networks have the drawbacks of large number of neurons and hidden layers required to deal with complex problems and require large training time. To overcome these...