Marco Herrera

Lanes Detection Based on Unsupervised and Adaptive Classifier

This paper describes an algorithm to detect the road lanes based on an unsupervised and adaptive classifier. We have selected this classifier because in the road we do not know the parameters of lanes, although we know that lanes are there, only they need to be classified. First of all, we tested and measured the brightness of the lanes of the road in many videos. Generally, the lines on the road are white. We used the HSV image and we improved the region of study. Then, we used a Hough transform which yields a set of possible lines. These lines have to be classified. The classifier starts with initial parameters because we suppose that the vehicle is on road and in the center of the lane. There are two classes, the first one is the left road line and the second one is the right road line. Each line has two parameters that are: middle point of line and the line slope. These parameters will be changing in order to adjust to the real lanes. A tensor holds the two lines, so these lines will not separate more than the tensor allows. A Kalman filter estimates the new classs parameters and improves the tracking of the lanes. Finally, we use a mask in order to highlight the lane and show to the user a better image.

Sliding Mode Control: An Approach to Control a Quadrotor

This paper describes the synthesis and application of controller based on sliding mode theory to a quad rotor. A PD sliding surface is considered for vertical take-off and landing aircraft, also changes in angles are done, and some disturbances are included. Therefore, the controller can be implemented using a PD controller as the sliding surface, and adding some algebra the complete controller algorithm is presented. The controller is tested by simulations.

A Blended Sliding Mode Control with Linear Quadratic Integral Control based on Reduced Order Model for a VTOL System.

In this paper, a Sliding Mode Control with chattering reduction based on reduced order model using Linear Quadratic Integral Control as sliding surface, is implemented to One Degree of Freedom Vertical Take-Off Landing System (VTOL). The controller performance is measured using Integral of the Square Error index by simulation and real tests. Finally, the Sliding Mode Control with a Linear Quadratic Integral Control as sliding surface performance for reference tracking and, robustness against VTOL system physical parameter uncertainties and external disturbances are verified by experimental results.

A fuzzy sliding mode controller from a reduced order model: A mobile robot experimental application

This paper presents a Sliding Mode Control with a Fuzzy PD+I surface for mobile robots that can be approximated by first-order-plus deadtime (FOPDT) models. The performance of this controller is compared with a Sliding Mode Control with a PID surface. An approximated model of a wheeled mobile robot is used in order to design the two controllers. The wheeled mobile robot is considered as two FOPDT processes. Simulation and experimental results are presented. The performance of the controllers is compared in terms of integral absolute error (IAE).

Optimal location of sliding mode control and power system stabilizers in order to damp electromechanical oscillations using the residue

The purpose of this work is to find the optimal location of sliding mode control and power system stabilizer in order to damp electromechanical oscillations in the power system using the residue method. The proposed control is evaluated performing several simulations on a modified version of the 39-bus New England power grid. A modal analysis is performed at the test system in order to evaluate numerically the effect of the proposed control. The matrices A, B, C and D are exported from the software DigSILENT to the MATLAB simulation software with the purpose to determine the Residue and find the optimal location of a Sliding Mode Control and PSS. The controller is added to the automatic voltage regulator of the select generator.

Two-wheeled inverted pendulum path planning: An experimental validation

This paper presents experimental results of a two-wheeled inverted pendulum path planning. The model of the robot, which has six identified variables, is linearized by least squares estimation. A Linear-quadratic Regulator is designed to maintain the robot stabilized, while it moves over a path. Furthermore, an integral part is added to the controller in order to achieve steady state equal to zero. Thus the result is an optimal PI controller. The path planning is designed using a Rapidly Exploring Random Tree Connect method. In addition, two algorithms are presented to improve the quality of the path, the first algorithm reduces the redundant paths and the second algorithm uses the Bezier curves to smooth the path.