Nonlinear neuro-predictive control of a miniature coaxial helicopter
| Autor: | Bogdan Muresan, Cristina Bianca Pop, Ioan Nascu, Ruben Crisan |
|---|---|
| Rok vydání: | 2011 |
| Předmět: |
Engineering
Artificial neural network business.industry ComputerApplications_COMPUTERSINOTHERSYSTEMS Control engineering Recurrent neural nets Optimal control law.invention Computer Science::Robotics Nonlinear system Model predictive control Coaxial rotors Control theory law Quadratic programming Coaxial business |
| Zdroj: | 2011 19th Mediterranean Conference on Control & Automation (MED). |
| DOI: | 10.1109/med.2011.5982978 |
| Popis: | In this paper the design of a nonlinear predictive controler based on a neural network model for a coaxial miniature helicopter is presented. The first step is the development of neural network models for all four movements of the helicopter. Recurrent dynamic networks are trained to predict accurately the behaviour of the helicopter. Further, this neural models are used for prediction in order to design nonlinear predictive controllers for yaw, altitude, pitch and roll control. When computing the optimal control signals, contraints are considered using a quadratic programming optimization technique. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
|