Fractional order chaotic cryptography in colored noise environment by using fractional order interpolatory cubature Kalman filter

Ramezani, Amin; Safarinejadian, Behrouz; Zarei, Jafar

doi:10.1177/0142331218822721

Cited by 12 publications

(7 citation statements)

References 27 publications

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“…The results show that the FICKFs with suitable free parameters lead to better accuracy compared with the existing filters with the same degree [ 91 ]. For nonlinear discrete-time fractional-order systems affected by colored noise, a similar FICKF is proposed in [ 92 ]. The authors propose a transformation of the system with colored noise into one with correlated process and measurement noises.…”

Section: Fractional-order Filtersmentioning

confidence: 99%

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A Review of Recent Advances in Fractional-Order Sensing and Filtering Techniques

Muresan

Birs

Dulf

et al. 2021

Sensors

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The present manuscript aims at raising awareness of the endless possibilities of fractional calculus applied not only to system identification and control engineering, but also into sensing and filtering domains. The creation of the fractance device has enabled the physical realization of a new array of sensors capable of gathering more information. The same fractional-order electronic component has led to the possibility of exploring analog filtering techniques from a practical perspective, enlarging the horizon to a wider frequency range, with increased robustness to component variation, stability and noise reduction. Furthermore, fractional-order digital filters have developed to provide an alternative solution to higher-order integer-order filters, with increased design flexibility and better performance. The present study is a comprehensive review of the latest advances in fractional-order sensors and filters, with a focus on design methodologies and their real-life applicability reported in the last decade. The potential enhancements brought by the use of fractional calculus have been exploited as well in sensing and filtering techniques. Several extensions of the classical sensing and filtering methods have been proposed to date. The basics of fractional-order filters are reviewed, with a focus on the popular fractional-order Kalman filter, as well as those related to sensing. A detailed presentation of fractional-order filters is included in applications such as data transmission and networking, electrical and chemical engineering, biomedicine and various industrial fields.

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Section: Fractional-order Filtersmentioning

confidence: 99%

“…The novel filtering algorithm is then applied to these new outputs. Simulation results on a fractional-order hyperchaotic Lorenz system targeting the cryptography in a communication system demonstrate the effectiveness of the proposed scheme [ 92 ].…”

Section: Fractional-order Filtersmentioning

confidence: 99%

A Review of Recent Advances in Fractional-Order Sensing and Filtering Techniques

Muresan

Birs

Dulf

et al. 2021

Sensors

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“…For the nonlinear time-varying discrete stochastic system constructed above, a cubature Kalman filter (CKF) [37][38][39] algorithm is used to estimate the state of the system. Firstly, the cubature points of the system are calculated, as shown in…”

Section: Control Model Of Stochastic Systems Based On Ckfmentioning

confidence: 99%

Control Optimization of Stochastic Systems Based on Adaptive Correction CKF Algorithm

Zhang

2020

International Journal of Aerospace Engineering

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Standard cubature Kalman filter (CKF) algorithm has some disadvantages in stochastic system control, such as low control accuracy and poor robustness. This paper proposes a stochastic system control method based on adaptive correction CKF algorithm. Firstly, a nonlinear time-varying discrete stochastic system model with stochastic disturbances is constructed. The control model is established by using the CKF algorithm, the covariance matrix of standard CKF is optimized by square root filter, the adaptive correction of error covariance matrix is realized by adding memory factor to the filter, and the disturbance factors in nonlinear time-varying discrete stochastic systems are eliminated by multistep feedback predictive control strategy, so as to improve the robustness of the algorithm. Simulation results show that the state estimation accuracy of the proposed adaptive cubature Kalman filter algorithm is better than that of the standard cubature Kalman filter algorithm, and the proposed adaptive correction CKF algorithm has good control accuracy and robustness in the UAV control test.

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“…It is acknowledged that the conventional integer-order differential equations and calculus theory are still the most-widely used mathematical tools for formulating novel controllers. However, as for the characterization of the transient response of electronic circuits or the transitional states of chaos systems, the fractional calculus theory proved to be more useful (Alsaedi et al, 2015; Ramezani et al, 2019). These engineering observations motivate us to develop novel fractional-order controllers for rendering higher tracking and stabilizing accuracy than conventional ones.…”

Section: Introductionmentioning

confidence: 99%

Optimal fractional-order proportional–integral–derivative control enabling full actuation of decomposed rotary inverted pendulum system

Yang

Zhang

Voyles

2023

Transactions of the Institute of Measurement and Control

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Allowing for a “virtual” full actuation of a rotary inverted pendulum (RIP) system with only a single physical actuator has been a challenging problem. In this paper, a hybrid control scheme that involves a pole-placement feedback controller and an optimal proportional–integral–derivative (PID) or fractional-order PID (FOPID) controller is proposed to simultaneously enable the tracking control of the rotary arm and the stabilization of the pendulum arm in an input–output feedback linearized RIP system. The PID controller is optimized first with the particle swarm optimization (PSO) to obtain three optimal gains, and then the other two parameters of the FOPID controller are optimized with the PSO. Compared to the optimized PID controller, the optimized FOPID controller improves the tracking and stabilizing accuracy by 53% and 29%, respectively, and demonstrates better adaptability for tracking different reference signals. Moreover, the hybrid FOPID controller exhibits 74.8% and 53% higher tracking accuracy than previous optimized model reference adaptive control PID (MRAC-PID) and linear–quadratic regulator (LQR) controllers, respectively. The proposed hybrid controllers are also digitized with different rules and sampling times, showing a closer performance between the discrete-time and continuous-time hybrid controllers under smaller sampling times.

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Fractional order chaotic cryptography in colored noise environment by using fractional order interpolatory cubature Kalman filter

Cited by 12 publications

References 27 publications

A Review of Recent Advances in Fractional-Order Sensing and Filtering Techniques

A Review of Recent Advances in Fractional-Order Sensing and Filtering Techniques

Control Optimization of Stochastic Systems Based on Adaptive Correction CKF Algorithm

Optimal fractional-order proportional–integral–derivative control enabling full actuation of decomposed rotary inverted pendulum system

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