High-performance fractional order terminal sliding mode control strategy for DC-DC Buck converter

Wang, Jianlin; Xu, Dianguo; Zhou, Huan; Bai, Anning; Lu, Wei

doi:10.1371/journal.pone.0187152

Cited by 9 publications

(9 citation statements)

References 21 publications

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“…In Ref. [ 22 ], a γ adaptive algorithm was presented, i.e., ; however, the proposed algorithm, could not guarantee that |x 1 | would yield the fastest approaching speed at x∈[0,1]. Therefore, an improvement to the γ adaptive algorithm using parameter λ is proposed herein.…”

Section: Adaptive Strategy Of γ and Simulation Resultsmentioning

confidence: 99%

Parameter adaptive terminal sliding mode control for Full-Bridge DC-DC converter

et al. 2021

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The poor dynamic performance problem of a Full-Bridge converter under a traditional control strategy is investigated in this study. A new parameter adaptive terminal sliding mode control policy is developed for a Full-Bridge DC-DC converter, by combining the integral part with the power function and differential function in the design of the sliding surface. In theory, the steady-state error of the system can approach zero within a short time. To manage the un-ideal situation after using a fixed value of power γ, an improved γ adaptive algorithm is proposed. The system output is tracked and γ is adjusted in real time. The effect of the system can be guaranteed always in an optimal state. Finally, simulation results are provided to verify the performance of the proposed design method under different conditions.

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Section: Adaptive Strategy Of γ and Simulation Resultsmentioning

confidence: 99%

Parameter adaptive terminal sliding mode control for Full-Bridge DC-DC converter

et al. 2021

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“…In order to achieve efficient sliding-mode control, these parameters should be adjusted adaptively according to the time of reaching the sliding surface. Therefore, considering the strong nonlinear mapping ability of neural network [42], a sliding-mode controller of PID approach law parameters online adjustment based on neural network is proposed.…”

Section: Plos Onementioning

confidence: 99%

Multi-packet transmission aero-engine DCS neural network sliding mode control based on multi-kernel LS-SVM packet dropout online compensation

Wang

Ren

2020

PLoS ONE

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In view of the strong nonlinear characteristics of the multi-packet transmission Aero-engine DCS with induced delay and random packet dropout, a neural network PID approach law sliding-mode controller using sliding window strategy and multi-kernel LS-SVM packet dropout online compensation is proposed. Firstly, the time-delay term in the system model is transformed equivalently, to establish the discrete system model of multi-packet transmission without time-delay; furthermore, the construction of multi-kernel function is transformed into kernel function coefficient optimization, and the optimization problem can be solved by the chaos adaptive artificial fish swarm algorithm, then the online predictive compensation will be made for data packet dropout of multi-packet transmission through the sliding window multi-kernel LS-SVM. After that, a sliding-mode controller design method of proportional integral differential approach law based on neural network is proposed. And online adjustment of PID approach law parameters can be achieved by nonlinear mapping of neural network. Finally, Truetime is used to simulate the method. The results shows that when the packet dropout rate is 30% and 60%, the average error of packet dropout prediction of multikernel LS-SVM reduces 29.21% and 44.66% compared with that of combined kernel LS-SVM, and the chattering amplitude of the proposed neural network PID approach law sliding-mode controller is decreased compared with other five approach law methods respectively. This controller can ensure a fast response speed, which shows that this method can achieve a better tracking control of the aeroengine network control system.

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“…With the basic application of FOSMC presented here, it can be extended to a FTSMC for a VSI circuit for grid as well as standalone operation as a future scope. Similarly, Adaptive FTSMC proposed in [18] for a DC-DC buck converter can very well be extended for DC-AC inverter for smaller steady state error and finite convergence. In Ref.…”

Section: Introductionmentioning

confidence: 99%

Robust fractional order sliding mode control for solar based DC-AC inverter

Saheb¹,

Gudey²

2020

Journal of Energy Systems

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Fractional order sliding mode control (FOSMC) strategy for a solar based DC-AC inverter is presented in this work. First FOSMC is implemented to voltage source inverter with a fixed DC input voltage of 400V to drive a load of 2.3 kW at a power factor of 0.8 lag. Here load voltage and current through capacitor as state variables and a linear sliding surface is considered. FOSMC using Gao’s reaching law is derived for inverter circuit. FOSMC is implemented at load bus to control output voltage of inverter with linear and nonlinear loads to desired values. FOSMC controls the output voltage with good voltage regulation, less steady state error of 1.32 %, settling time of 0.15 ms, good dynamic response, and convergence to origin with less chattering compared to classical SMC. FOSMC based solar based VSI is presented. The maximum power from PV array is extracted using P&O MPPT algorithm. A boost converter is used to step up input voltage of 200 V to 400 V. P-V and I-V characteristics are obtained for a typical solar cell of 2.5 kW FOSMC requires less control efforts to obtain a pure sinusoidal output voltage waveform of 230 V (rms) with output voltage THD of 0.135% well within IEEE standards. PSCAD/EMTDC v4.6 is used for simulation work.

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High-performance fractional order terminal sliding mode control strategy for DC-DC Buck converter

Cited by 9 publications

References 21 publications

Parameter adaptive terminal sliding mode control for Full-Bridge DC-DC converter

Parameter adaptive terminal sliding mode control for Full-Bridge DC-DC converter

Multi-packet transmission aero-engine DCS neural network sliding mode control based on multi-kernel LS-SVM packet dropout online compensation

Robust fractional order sliding mode control for solar based DC-AC inverter

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