Robust Multivariable controller Design with the simultaneous H2 /H∞/µ for Single Person Aircraft

In a physical system several targets are normally being considered in which each of nominal and robust performance has their own strengths and weaknesses. In nominal performance case, system operation without uncertainty has decisive effect on the operation of system, whereas in robust performance one, operation with uncertainty will be considered. The target of present paper is a balance between nominal and robust performance of state feedback A new approach of present paper is the combination of two controllers of μ and H2/H∞.  The controller for robust stability status, nominal performance, robust performance and noise rejection are designed simultaneous. Controller will be achieved from solving constraint optimization problem. Where a simultaneous H2 /H∞/µ robust multivariable controller has been designed over an X-29 Single Person.  This model has three inputs and three outputs, where the state space equations of the system response to an unstable one. Simulation results show the effectiveness and benefits of the method.DOI:http://dx.doi.org/10.11591/ijece.v3i2.235

Path Planning for Two-Link Navigation in an Unknown Environment using webcam

In this article, we used image processing by a webcam connected on top of the arm robot. The robot navigation is in an unknown environment. Then start point and target point were determined for the robot, so the robot needs to have a program for path planning using Voronoi diagrams to find the path. After the possible path for moving the robot was found, the route information obtained was sent to the arm robot. The arm robot moves in the workspace and any time new information was processed via the webcam. The program was written using MATLAB software which at controls the robot’s movement the unknown environment

An LMI Approach to Automatic Loop-Shaping of QFT Controllers

Quantitative Feedback Theory (QFT) is one of the most effective methods of robust controller design. In QFT design, we can consider the phase information of the perturbed plant so it is less conservative than H$\infty$ and µ-synthesis methods. In this paper, we want to overcome the major drawback of QFT method, i.e., lack of an automated technique for loop-shaping. Clearly such an automatic process must involve some sort of optimization, and while recent results on convex optimization have found fruitful applications in other areas of control theory we have tried to use LMI theory for automating the loop-shaping step of QFT design