Trajectory Tracking between Josephson Junction and Classical Chaotic System via Iterative Learning Control

Cheng, Chao-Ching; Chao, Paul C.-P.

doi:10.3390/app8081285

Cited by 6 publications

(3 citation statements)

References 31 publications

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“…Cheng et al reported on "Trajectory Tracking between Josephson Junction and Classical Chaotic System via Iterative Learning Control" [4]. This article addressed trajectory tracking between two nonidentical systems with chaotic properties.…”

Section: The Topics Of Applied System Innovationmentioning

confidence: 99%

Selected Papers from IEEE ICASI 2018

2020

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This Special Issue on “Selected Papers from IEEE ICASI 2018” includes excellent papers presented at the IEEE ICASI 2018 regarding the “applied system innovation” topic. Mechanical engineering and design innovations are both academic and practical engineering fields, which involve systematic technological materialization through scientific principles and engineering designs. Technological innovations in mechanical engineering include IT-based intelligent mechanical systems, mechanics and design innovations, and applied materials in nanosciences and nanotechnology. The aim is to encourage the attendees at the IEEE ICASI 2018 to publish their experimental and theoretical research relating to applied system innovation.

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Section: The Topics Of Applied System Innovationmentioning

confidence: 99%

Selected Papers from IEEE ICASI 2018

2020

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“…For model predictive control (MPC) of a quad-rotor platform, control took the form of linear matrix inequalities [26]. LMI control was used for trajectory tracking instead of iterative learning control (ILC) [27].…”

Section: Literature Surveymentioning

confidence: 99%

Stability Driven Optimal Controller Design for High Quality Images

Suh¹

2018

Electronics

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This note presents an optimal design method to enhance image quality in optical image stabilization (OIS) systems. First of all, performance limitations of conventional methods are shown and secondly, a new design framework based on convex optimization is proposed. The resulting controller essentially stabilizes the closed loop systems because the proposed method is derived from Lyapunov stability. From the test results, it is confirmed that this method reduces the effect of hand vibrations and makes images sharp. Additionally, it is shown that the proposed method is also effective in robot vision and recognition rate of deep neural network (DNN) based traffic signs and pedestrians detection in automotive applications. This note has three main contributions. First, performance limitations of the conventional method are shown. Second, from the relation between sensitivity and complementary sensitivity functions, an indirect design method for performance improvement is proposed, and finally, stability guaranteed optimal design is proposed. Unlike conventional methods, the proposed method does not require addition filters to suppress resonances of the plant and this note highlights phases of the closed loop systems on removing external vibrations.

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“…backstepping control [7][8][9][10][11][12][13][14], sliding mode control [15][16][17][18][19][20][21][22], iterative learning control [23], and intelligent control [24][25][26][27][28][29][30][31][32][33][34][35].…”

Section: Introductionmentioning

confidence: 99%

Fixed-Time Adaptive Chaotic Control for Permanent Magnet Synchronous Motor Subject to Unknown Parameters and Perturbations

et al. 2023

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It is well known that the permanent magnet synchronous motor (PMSM) exhibits chaotic characteristics when its parameters fall within a certain range, which can lead to system instability. This article proposes an adaptive control strategy for achieving the fixed-time chaotic stabilization of PMSM, even in the presence of unknown parameters and perturbations. The developed controller is synthesized by combining a parametric adaptive mechanism with a fixed-time control technique. The stability analysis demonstrates that the system states under the developed controller can converge to small neighborhoods around the equilibrium point within a fixed time. Thanks to the adoption of the parametric adaptive mechanism, the developed controller is not only insensitive to unknown parameters but also robust against perturbations. Finally, simulated studies are conducted to verify and emphasize the effectiveness of the developed control strategy.

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Trajectory Tracking between Josephson Junction and Classical Chaotic System via Iterative Learning Control

Cited by 6 publications

References 31 publications

Selected Papers from IEEE ICASI 2018

Selected Papers from IEEE ICASI 2018

Stability Driven Optimal Controller Design for High Quality Images

Fixed-Time Adaptive Chaotic Control for Permanent Magnet Synchronous Motor Subject to Unknown Parameters and Perturbations

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