Tese: Switching receding-horizon approximate estimation and control of a flexible joint robotic manipulator
Aluno(a) : Lara Candido AlvimOrientador(a): Helon Ayala e Elias Rossi
Área de Concentração: Mecânica Aplicada
Data: 10/05/2023
Link para tese/dissertação: https://doi.org/10.17771/PUCRio.acad.64518
Resumo: The advances in Robotics in recent decades allow a growing range of applications of robotic manipulators in various sectors of industry. This directly impacts the Human-Robot Interaction (HRI), resulting in an increase in tasks that require a shared work environment, safety performance, and the contact detection ability of the robotic manipulator. Consequently, control methods capable of predicting contact, and controlling force or trajectory to avoid damage during collisions become increasingly necessary either for safety or performance reasons. Separating the dynamics of a single-link manipulator into two modes, namely position control mode (free mode) and torque control mode (contact mode), the first part of this dissertation deals with the estimation problem of states for active mode detection through the implementation of the Moving Horizon State Estimation with Neural Networks (NNMHSE) method. The effectiveness of the proposed estimation method is evaluated by comparing the states and modes generated by the MHSE and those estimated by the Neural Network. This method presented a high coefficient of determination factor (R²), and a significant reduction in the processing time of the estimation algorithm. The second part of this dissertation deals with the position and torque switching problem for a non-linear robotic manipulator, applying Model-Based Predictive Control (MPC). The implemented switched MPC algorithm was able to effectively control both modes of the system, presenting low prediction error, even considering cyclical changes in the modes. Both methods prove to be suitable for controlling co-located robotic manipulators with humans or in unstructured environments through operation mode detection and position-torque switching control. Link da defesa: https://puc-rio.zoom.us/j/97518786462?pwd=aStmdWljOXZURldsMnRFbCs0dmxHdz09