Generalized nonlinear optimal predictive control using iterative state-space trajectories: Applications to autonomous flight of UAVs

Model Predictive Control (MPC) is a modern technique that, nowadays, encapsulates different optimal control techniques. For the case of non-linear dynamics, many possible variants can be developed which can lead to new control algorithms. In this manuscript a novel generic control system method is p...

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Bibliographic Details
Published in:International journal of control, automation, and systems 2015, Automation, and Systems, 13(2), , pp.361-370
Main Authors: Murillo, Marina H., Limache, Alejandro C., Rojas Fredini, Pablo S., Giovanini, Leonardo L.
Format: Article
Language:English
Subjects:
Aircraft
Altitude
Autonomous
Control
Control algorithms
Control systems
Dynamical systems
Engineering
Flight simulation
Mathematical models
Mechatronics
Nonlinear dynamics
Optimization
Predictive control
Regular Papers
Research centers
Robotics
Studies
Trajectories
Unmanned aerial vehicles
Variables
제어계측공학
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Summary:Model Predictive Control (MPC) is a modern technique that, nowadays, encapsulates different optimal control techniques. For the case of non-linear dynamics, many possible variants can be developed which can lead to new control algorithms. In this manuscript a novel generic control system method is presented. This method can be applied to control, in an optimal way, different systems having non-linear dynamics. Particularly, in this paper, the proposed technique is presented in the context of developing a control system for autonomous flight of UAVs. This technique can be used for different types of aerial vehicles having any type of generic non-linear dynamics. The presented method is based on the use of iteratively defined optimal candidate state-space trajectories in global state-space. The method uses a generalized linearization process which, opposite to standard methods, does not need to be predefined in a certain equilibrium state but instead it is performed along any arbitrary state. The technique allows the inclusion of constraints with ease. The presented technique is used as a centralized control system unit that is able to control the full aircraft dynamics without the need of decoupling the system in different reduced modes. The technique is tested by making a Cessna 172 airplane model to perform the following autonomous unmanned maneuvers: climbing at constant speed to a desired altitude, heading change to a desired flight direction, and, coordinate turn.
ISSN:1598-6446
2005-4092
DOI:10.1007/s12555-013-0416-y