Augmentação estocástica com horizonte de predição estendido baseada no PID para um sistema multivariável

Abstract

The objective of this research was to investigate and design a control system based on the Stochastic Augmentation with Extended Prediction Horizon using 10-steps ahead, consisting of the union of characteristics of a linear deterministic controller with a stochastic predictive controller, resulting in a control system with guaranteed robustness and with predictive, linear, and stochastic characteristics. For the application of the Stochastic Augmentation, the chosen controllers were the classic PID and the GMV in its incremental form, where the former was augmented resulting in a controller with extended prediction horizon, the AEHP. The classic PID controller in the discrete time domain is compared to AEHP. Both controllers were tested in simulations with a process model that represents the dynamics of a helicopter, denominated 2DOF Helicopter (H2DOF), produced by the Quanser company. The H2DOF is a multivariable system, whose model in the state space is transformed to the transfer function form, generating two coupled subsystems, one for the pitch angle and other to the yaw angle, in which the couplings influence were considered as disturbances in the controllers design stage. The transformation of the system model to the transfer function form reduced the complexity of multivariable system in the state space, allowing the use of a more simple control law. Furthermore, it was performed the pairing of input and output, to verify what output was more sensible the one specific input, by means of Relative Gain Array. And to prove the control system efficiency based in the Stochastic Augmentation with extended prediction horizon, simulations were realized using the software Matlab®, assessing the performance of extended prediction horizon, enduring the coupled dynamics, facing load disturbances and Gaussian disturbances. The essays were evaluated by robustness and performance indices. The predictive AEHP controller obtained better results for most indices with guaranteed robustness, compared to the discrete-time PID controller.