The linear positioning of hydraulic cylinders is used in industrial applications, such as the positioning of flight fins on airplanes, injection molding processes, rock drilling, etc. One of the most used control techniques is the PID (Proportional Integral Derivative) control, the problem with this technique is the tuning of its three parameters. In this work, the experimental identification of the transfer function of the system to be controlled was first done, using the MATLAB toolbox ident. Then the PSO (Particle Swarm Optimization) algorithm was implemented in MATLAB codes. Like any optimization algorithm it requires a performance index or cost function, in this research ITAE (Integral Time Absolute Error) was used. The codes were tested with research papers found in the literature, polished until they were ready for any transfer function. These algorithms were then tested in the transfer function previously identified, achieving satisfactory results in the simulations. Finally, those values of the PID parameters found were tested in the linear positioning module of the Oleohydraulics and Pneumatics Laboratory at the Universidad Católica de Santa María. Also achieving satisfactory results in the performance of the controlled system: minimum establishment time, minimum rise time and minimum overshoot, which matched with the values obtained by data acquisition. Finally, the Ant Colony algorithm (ACO) was tested, looking for better results. The best results were obtained with the ant colony algorithm, for 20 ants, with 1000 nodes, and 100 tours. For the system with load the best solution was Kp = 11.01, Ki = 5.51 and Kd = 3.71. The results were improved by making a better experimental identification of the system. The solution was also improved by increasing the number of tours and the number of nodes, increasing the computational cost. With the controller implemented, the setup time was reduced from 2.5 to 0.6 seconds without overshoot and with an error of less than 2 mm.
Object recognition is essential in any surveillance system. Being important to identify the entry of intruders to a home or parking in restricted places, are some actions that are performed during a routine. However, the performance of these systems turns out to be inefficient because they remain static and in many cases their viewing angle turns out to be very limited. Therefore, we believe that a mobile surveillance system would be more efficient in reducing citizen insecurity in some closed housing estates, shopping centers or condominiums. Since being a mobile monitoring system would not have the disadvantages that present security systems have. Reason why, in this project is proposed the design and application of a patrol robot with autonomous navigatio n, which is able to monitor and travel a specified route. This path can be defined by the user, who when recording a waypoint the rob o t will move to that location in a relatively straight line, allowing the robot to navigate from one point to another preprogrammed. The navigation of robot will be done by GPS, but not only using this signal. Since, although it is true that this gives us information about the position or speed of a topological form, it does not show us if there are any obstacles in the way.For this we seek to merge GPS navigation with a sensor-based one, which collects information and with the help of a microprocessor this information serves for the robot to make decisions, since it is sought to be completely autonomous. Finally, the robot will be able to capture images with the help of a camera, storing them in its internal memory. These im a ges are then sent to the user in real time so that the user can analyze them and detect any anomaly act in the shortest possible time.
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