https://doi.org/10.1140/epjs/s11734-021-00332-5
Regular Article
Nonlinear model predictive control of the chaotic Hindmarsh–Rose biological neuron model with unknown disturbance
Electrical Electronics Engineering, Sakarya University, Sakarya, Turkey
a
selcukemiroglu@sakarya.edu.tr
Received:
18
January
2021
Accepted:
30
October
2021
Published online:
24
November
2021
In this paper, the control of chaos in Hindmarsh–Rose biological neuron model is investigated using model predictive control (MPC). The chaotic behaviors of the corresponding system are diminished, and the system is stabilized at the equilibrium point. The system is provided to converge the equilibrium or desired point and desired trajectory. MPC-based control design is also addressed against the disturbances such as sensor noise. The system is not only converged to equilibrium point but also converge the desired point and tracks the desired trajectory including disturbances by applying MPC. In addition, the effect of prediction and control horizons on effectiveness of the controller is discussed. The effectiveness of the proposed method is illustrated by intensive simulations.
© The Author(s), under exclusive licence to EDP Sciences, Springer-Verlag GmbH Germany, part of Springer Nature 2021
