Original scientific paper
https://doi.org/10.1080/00051144.2023.2295204
Robust synchronization of four-dimensional chaotic finance systems with unknown parametric uncertainties
Muhammad Shafiq
; Department of Electrical and Computer Engineering, Sultan Qaboos University Muscat, Oman
Israr Ahmad
; Department of Information Technology, University of Technology and Applied Sciences Nizwa, Nizwa, Oman
*
* Corresponding author.
Abstract
The inherent randomness in economic factors causes complex and irregular behaviour that
affects financial system stability and economic growth. Such chaotic behaviour can make it
difficult to synchronize financial systems. The chaotic finance system synchronization precision maintains financial stability and economic growth. In this paper, the controller design
procedure assumes that the financial system is exposed to unknown bounded exogenous disturbances and model uncertainties. This research proposes a novel direct adaptive control strategy
that achieves robust synchronization of two identical four-dimensional finance chaotic (FDFC)
systems. The proposed controller establishes a faster, smoother synchronization error vector
convergence to zero. The controller design procedure does not eliminate the closed-loop’s nonlinear terms and is independent of the financial system parameters. These controller’s attributes
accomplish the closed-loop robust performance. Further, this controller uses real-time estimates
of unknown model uncertainties and bounds to compensate for unknown exogenous disturbances. Computer simulation results and proofs of theoretical analysis based on the Lyapunov
stability theory confirm that the proposed control technique compels the error vector trajectories to the origin in a short transient time with less active oscillations for all signals. The paper
includes comparative computer simulations for verifying the theoretical findings.
Keywords
Hyperchaotic finance system; Lyapunov stability theory; adaptive controller; chaos synchronization
Hrčak ID:
322967
URI
Publication date:
27.12.2023.
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