This research is focused on the development of a nonlinear cascade-based control algorithm for a laboratory helicopter-denominated Twin Rotor MIMO System (TRMS). The TRMS is an underactuated nonlinear multivariable system, characterised by a coupling effect between the dynamics of the propellers and the body structure, which is caused by the action-reaction principle originated in the acceleration and deceleration of the propeller groups. Firstly, this work introduces an extensive description of the platform’s dynamics, which was carried out by splitting the system into its electrical and mechanical parts. Secondly, we present a design of a nonlinear cascade-based control algorithm that locally guarantees an asymptotically and exponentially stable behaviour of the controlled generalised coordinates of the TRMS. Lastly, a demonstration of the effectiveness of the proposed approach is provided by means of numerical simulations performed under the MATLAB®/Simulink® environment.
Part of the book: Nonlinear Systems
During the last years, there has been a notable increase in the number of studies focused on the assessment of brain dynamics for the recognition of emotional states by means of nonlinear methodologies. More precisely, different entropy metrics have been applied for the analysis of electroencephalographic recordings for the detection of emotions. In this sense, regularity-based entropy metrics, symbolic predictability-based entropy indices, and different multiscale and multilag variants of the aforementioned methods have been successfully tested in a series of studies for emotion recognition from the EEG recording. This chapter aims to unify all those contributions to this scientific area, summarizing the main discoverings recently achieved in this research field.
Part of the book: Brain-Computer Interface