Adaptive RBF neural network-based control of an underactuated control moment gyroscope

• Published in: Neural computing & applications 2021-06, Vol.33 (12), p.6805-6818
• Main Authors: Montoya-Cháirez, Jorge, Rossomando, Fracisco G., Carelli, Ricardo, Santibáñez, Víctor, Moreno-Valenzuela, Javier
• Format: Article
• Language: English
• Subjects: Adaptive control; Artificial Intelligence; Computational Biology/Bioinformatics; Computational Science and Engineering; Computer Science; Controllers; Data Mining and Knowledge Discovery; Disturbances; Gyroscopes; Image Processing and Computer Vision; Mechanical systems; Neural networks; Original Article; Probability and Statistics in Computer Science; Proportional integral derivative; Radial basis function; Robust control; System effectiveness; Tracking control; Tracking errors; Trajectory control
• ISSN: 0941-0643; 1433-3058
• DOI: 10.1007/s00521-020-05456-8

Radial basis function (RBF) neural networks have the advantages of excellent ability for the learning of the processes and certain immunity to disturbances when using in control systems. The robust trajectory tracking control of complex underactuated mechanical systems is a difficult problem that requires effective approaches. In particular, adaptive RBF neural networks are a good candidate to deal with that type of problems. In this document, a new method to solve the problem of trajectory tracking of an underactuated control moment gyroscope is addressed. This work is focused on the approximation of the unknown function by using an adaptive neural network with RBF fully tuned. The stability of the proposed method is studied by showing that the trajectory tracking error converges to zero while the solutions of the internal dynamics are bounded for all time. Comparisons between the model-based controller, a cascade PID scheme, the adaptive regressor-based controller, and an adaptive neural network-based controller previously studied are performed by experiments with and without two kinds of disturbances in order to validate the proposed method.