Observer-structured controller: Model-based visual feedback control and model-data-concurrent-based flight control

This paper addresses the design problem of observer-structured controller , which has been recently proposed as an extension of Luenberger observer-based controllers to the case of controlling Linear Parameter-Varying (LPV) systems, and demonstrates its effectiveness in three practical design examples. The first one is model-based visual feedback controller design for a cart-driven inverted pendulum, the second one is data-based flight controller design, and the last one is model-data-concurrent-based flight controller design. Observer-structured controller has been proposed to embed plant state estimation ability to a priori designed Linear-Time-Invariant (LTI) or LPV controllers, similarly to existing methods in literature to embed plant state estimation ability to a priori designed LTI controllers which are designed for controlling LTI plant systems. However, the demonstrations of its applicability and usefulness have not been sufficiently illustrated. This paper therefore shows them directly by designing observer-structured controllers for model-based design problem, in which only mathematical plant models and a priori designed controller state-space matrices are available, for data-based design problem, in which only operational data and a priori designed controller state space matrices are available, and for model-data-concurrent-based design problem, in which operational data as well as mathematical plant models and a priori designed controller state-space matrices are available. In particular, the controller designed in the first formulation demonstrates the practical state estimation performance by lab-level experiments, and the controller in the second formulation demonstrates the usefulness of operational data to improve plant state estimation ability but simultaneously illustrates the lack of theoretical performance guarantee, and the controller in the last formulation well demonstrates the effectiveness of operational data to improve plant state estimation performance while rigorous estimation performance is guaranteed by using models.