The best example of a closed-loop control system is a traffic light control system including a sensor at the input. Therefore, these systems are also named as automatic control systems. In this arrangement, the control system output can be corrected automatically to get the preferred output. As an alternative of the input, this error signal can be given as an input of a controller.Ĭonsequently, the controller generates an actuating signal to control the plant. This feedback signal can be obtained from the elements of feedback in the control system by considering the system output as an input. In the above diagram, the error detector generates an error signal, so this is the variation of the input as well as the feedback signal. This type of control system can include more than one feedback. So the output can be controlled accurately by providing feedback to the input. Mina Kamel, Kostas Alexis, Markus Wilhelm Achtelik, Roland Siegwart, " Fast Nonlinear Model Predictive Control for Multicopter Attitude Tracking on SO(3)", Multiconference on Systems and Control (MSC), 2015, Novotel Sydney Manly Pacific, Sydney Australia.When the control system includes a feedback loop, then the systems are known as feedback control systems.Siegwart, " Hybrid Predictive Control for Aerial Robotic Physical Interaction towards Inspection Operations", IEEE International Conference on Robotics and Automation, ICRA 2014, Hong Kong, China, May 31-June 7, 2014, p.
Tzes, " Robust Model Predictive Flight Control of Unmanned Rotorcrafts", Journal of Intelligent and Robotic Systems, Springer (DOI: 10.1007/s1084-7) Siegwart, " Explicit Model Predictive Control and L1-Navigation Strategies for Fixed–Wing UAV Path Tracking", Mediterranean Control Conference, 2014, Palermo, Italy, June 16-June 19, 2014, p. 1159-1165
Can we decouple the system? What assumptions are required? Are they reasonable?.What is the required -for control purposes- order of the system?.Should -for control purposes- the system be captured with Nonlinear, Linear or Hybrid dynamics?.Therefore, the following questions should be answered before deriving a model to be used with Model Predictive Control methods:
A good model is simple as possible, but not simpler. Finding a good balance between these two requirements is a balance. At the same time, the selected objective and imposed constraints also influence and define these properties.Ī good model for MPC is a model that is descriptive enough, captures the dominant and important dynamics of the system but also remains simple enough such that it allows the optimization problem to be tractable and solvable in real-time. In fact, the model selection has a major role regarding the computational complexity of the algorithm, its theoretical properties (e.g. MPC relies on the provided model for its computations.
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