This paper presents the mathematical modeling of a quadcopter. A modified PID control algorithm in Simulink is developed, observing the system's behavior in a virtual environment. PID controller is implemented in an embedded system. The quadcopter is attached to a test bench for submission to external forces. Finally, real test on outdoor scenarios have been made to validate the proposed PID controller.

This paper presents the mathematical model of a quadricopter under the Newton-Euler formulation. A Transfer function has been chosen, which represents a brushless motor and its driver as one system. PID cascade control had been designed to solve the path tracking problem for a quadcopter. The controller is evaluated in a 3D environment in Simulink.

To achieve optimal performance in the regulation of nonlinear systems, more advanced control techniques are needed. In this paper, three of these techniques are applied and compared in a system composed of three tanks in cascade. The first one is the Nonlinear Extended Prediction Self-Adaptive Control (NEPSAC). NEPSAC is a nonlinear predictive controller and therefore, is based on solving an optimization problem using the nonlinear model of the process to find a feedback control law. The second one is a gain scheduling controller using an array of autotuned PID controllers. This will be the non-model-based strategy. Finally, the gain scheduling approach is used again but with an array of linear model predictive controllers. In this case the predictive controller is EPSAC, the linear version of NEPSAC controller. Comparing all these control strategies, this work deepens in the characteristics, performance, advantages and disadvantages of these techniques to deal with nonlinear processes. It is intended to be a reference guide to choose — from a practical point of view — the most appropriate controller when dealing with a soft nonlinear system.

This paper presents the use of a new concept: Internet of Things (IoT), applied to the fermentation process of Cocoa at the Piura's mountain range. A prototype was designed and built with sensors that record the variables of temperature, oxygen and carbon dioxide during the process and send this information to the Internet. Finally a system has been developed that receives this information, visualizes it, and through graphs it allows monitoring and analyze the process in real time. The work has been done in the community of Buenos Aires, Piura, Peru.