Novel GPID: Grünwald–Letnikov Fractional PID for Enhanced Adaptive Cruise Control DOI Creative Commons

Diaa Eldin Elgezouli,

Hassan Eltayeb, Mohamed A. Abdoon

et al.

Fractal and Fractional, Journal Year: 2024, Volume and Issue: 8(12), P. 751 - 751

Published: Dec. 20, 2024

This study demonstrates that the Grünwald–Letnikov fractional proportional–integral–derivative (GPID) controller outperforms traditional PID controllers in adaptive cruise control systems, while conventional struggle with nonlinearities, dynamic uncertainties, and stability, GPID enhances robustness provides more precise across various driving conditions. Simulation results show improves accuracy, reducing errors better than controller. Additionally, maintains a consistent speed reaches target faster, demonstrating superior control. The GPID’s performance different orders highlights its adaptability to changing road conditions, which is crucial for ensuring safety comfort. By leveraging calculus, also acceleration deceleration profiles. These findings emphasize potential revolutionize control, significantly enhancing Numerical obtained α=0.99 from have shown accuracy consistency, adapting conditions improved demonstrated faster stabilization of at 60 km/h smaller reduced error 0.59 50 s compared 0.78 PID.

Language: Английский

A novel fractional-order 3-D chaotic system and its application to secure communication based on chaos synchronization DOI
Sajad Iqbal, Jun Wang

Physica Scripta, Journal Year: 2025, Volume and Issue: 100(2), P. 025243 - 025243

Published: Jan. 27, 2025

Abstract In this study, we introduce a new fractional-order chaotic system (FO-CS) that comprises six terms, setting it apart from classical models such as the Lorenz, Chen, and Lü systems. The proposed system, while having different number of terms compared to Lorenz Chen systems, generates attractors closely resemble those found in these conventional algebraic structure is relatively simple, consisting four linear two quadratic terms. We conduct comprehensive theoretical analysis dynamic simulations both fractional integer-order perspectives, exploring numerous dynamical characteristics, including Lyapunov exponent spectra, fractal dimensions, Poincaré maps, bifurcation phenomena. Furthermore, derive Hamiltonian energy function for through application Helmholtz’s theorem. To delve into synchronization within carry out numerical alongside an active control method. effective implementation strategy deepens our understanding dynamics highlights its potential applications, particularly secure communication. One significant use techniques transmission real audio signals, showcasing relevance technique enhancing communication security.

Language: Английский

Citations

2
Dynamic Analysis and FPGA Implementation of Fractional-Order Hopfield Networks with Memristive Synapse DOI Creative Commons
A. Anzo-Hernández, Ernesto Zambrano-Serrano, Miguel Ángel Platas-Garza

et al.

Fractal and Fractional, Journal Year: 2024, Volume and Issue: 8(11), P. 628 - 628

Published: Oct. 24, 2024

Memristors have become important components in artificial synapses due to their ability emulate the information transmission and memory functions of biological synapses. Unlike counterparts, which adjust synaptic weights, memristor-based operate by altering conductance or resistance, making them useful for enhancing processing capacity storage capabilities neural networks. When integrated into systems like Hopfield networks, memristors enable study complex dynamic behaviors, such as chaos multistability. Moreover, fractional calculus is significant model effects, enabling more accurate simulations systems. Fractional-order particular, exhibit chaotic multistable behaviors not found integer-order models. By combining with fractional-order these offer possibility investigating different phenomena This investigates dynamical behavior a network (HNN) incorporating memristor piecewise segment function one its synapses, highlighting impact derivatives memristive on stability, robustness, complexity system. Using four neurons case study, it demonstrated that HNN exhibits multistability, coexisting attractors, limit cycles. Through spectral entropy analysis, regions initial condition space display varying degrees are mapped, those areas where series approach pseudo-random sequence numbers. Finally, proposed implemented Field-Programmable Gate Array (FPGA), demonstrating feasibility real-time hardware realization.

Language: Английский

Citations

4
Harnessing machine learning for identifying parameters in fractional chaotic systems DOI

Ce Liang,

Weiyuan Ma, Chenjun Ma

et al.

Applied Mathematics and Computation, Journal Year: 2025, Volume and Issue: 500, P. 129454 - 129454

Published: April 6, 2025

Language: Английский

Citations

0
Modeling Thermal Impedance of IGBT Devices Based on Fractional Calculus Techniques DOI Open Access

Nan Yang,

Zhengjian Yang,

Yaoling Huang

et al.

Electronics, Journal Year: 2024, Volume and Issue: 13(22), P. 4423 - 4423

Published: Nov. 12, 2024

The thermal impedance characteristics of insulated gate bipolar transistor (IGBT) modules are critical for the management and design electronic devices. This paper proposes a fractional-order equivalent model, which is inspired by correlation between multi-time-scale dissipation heat conduction processes fractional calculus. model derived based on connection calculus Foster network in mathematical operations, with only two parameters to be identified: capacity C order α. Moreover, this provides parameter identification method proposed multi-objective particle swarm optimization (MOPSO) algorithm. In validate effectiveness superiority work, experiments comparative works provided paper. results indicate that can accurately describe frequency domain characteristic curves IGBT modules, difference amplitude not exceeding 1 dB phase 1° within operating range (1 kHz, MHz).

Language: Английский

Citations

1
Joint Battery State of Charge Estimation Method Based on a Fractional-Order Model with an Improved Unscented Kalman Filter and Extended Kalman Filter for Full Parameter Updating DOI Creative Commons
Jingjin Wu, Yuhao Li, Qian Sun

et al.

Fractal and Fractional, Journal Year: 2024, Volume and Issue: 8(12), P. 695 - 695

Published: Nov. 26, 2024

State estimation of batteries is crucial in battery management systems (BMSs), particularly for accurately predicting the state charge (SOC), which ensures safe and efficient operation. This paper proposes a joint SOC method based on fractional-order model, utilizing multi-innovation full-tracking adaptive unscented Kalman filter (FOMIST-AUKF-EKF) combined with an extended (EKF) online parameter updates. The model more effectively represents battery’s dynamic characteristics compared to traditional integer-order models, providing precise depiction electrochemical processes nonlinear behaviors. It offers superior modeling long-memory effects, complex dynamics, aging processes, enhancing adaptability characteristics. Comparative results indicate maximum end-voltage error reduction 0.002 V model. technology increases robustness against noise by incorporating multiple historical observations, while strategy dynamically adjusts covariance matrix real-time data, thus accuracy. Furthermore, EKF updates parameters (e.g., resistance capacitance) real time, correcting errors improving prediction Simulation experimental validation show that proposed significantly outperforms UKF-based techniques accuracy, stability, adaptability. Specifically, under varying conditions such as NEDC DST, demonstrates excellent practicality, 0.27% 0.67%, respectively.

Language: Английский

Citations

0
Novel GPID: Grünwald–Letnikov Fractional PID for Enhanced Adaptive Cruise Control DOI Creative Commons

Diaa Eldin Elgezouli,

Hassan Eltayeb, Mohamed A. Abdoon

et al.

Fractal and Fractional, Journal Year: 2024, Volume and Issue: 8(12), P. 751 - 751

Published: Dec. 20, 2024

This study demonstrates that the Grünwald–Letnikov fractional proportional–integral–derivative (GPID) controller outperforms traditional PID controllers in adaptive cruise control systems, while conventional struggle with nonlinearities, dynamic uncertainties, and stability, GPID enhances robustness provides more precise across various driving conditions. Simulation results show improves accuracy, reducing errors better than controller. Additionally, maintains a consistent speed reaches target faster, demonstrating superior control. The GPID’s performance different orders highlights its adaptability to changing road conditions, which is crucial for ensuring safety comfort. By leveraging calculus, also acceleration deceleration profiles. These findings emphasize potential revolutionize control, significantly enhancing Numerical obtained α=0.99 from have shown accuracy consistency, adapting conditions improved demonstrated faster stabilization of at 60 km/h smaller reduced error 0.59 50 s compared 0.78 PID.

Language: Английский

Citations

0