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Self-Tuning Proportional-Type Performance Recovery Property Output Voltage-Tracking Algorithm for DC–DC Boost Converter
- Source :
- IEEE Transactions on Industrial Electronics. 66:3167-3175
- Publication Year :
- 2019
- Publisher :
- Institute of Electrical and Electronics Engineers (IEEE), 2019.
-
Abstract
- This article exhibits an output voltage-tracking control algorithm incorporating a self-tuning algorithm and disturbance observers (DOBs) for dc–dc boost converters without tracking error integrators, considering model nonlinearities, parameter variations, and load uncertainties. The proposed algorithm is designed such that it forces the output voltage to track its target trajectory driven by a time-varying low-pass filter (LPF), despite model-plant mismatches. This paper makes two main contributions. First, it constructs the self-tuning algorithm by updating the closed-loop cut-off frequency in the time-varying LPF to improve the transient tracking performance. Second, it embeds first-order DOBs in the proportional-type nonlinear controller to achieve both performance recovery and the offset-free properties. The experimental verifications are carried out to illustrate the effectiveness of the closed-loop system driven by the proposed technique with a 3-kW prototype dc–dc boost converter; the 46% improvement of the tracking performance is observed, compared with the conventional feedback-linearization controller.
- Subjects :
- Computer science
020208 electrical & electronic engineering
Automatic frequency control
Self-tuning
02 engineering and technology
Filter (signal processing)
Nonlinear system
Control and Systems Engineering
Control theory
Integrator
Boost converter
0202 electrical engineering, electronic engineering, information engineering
Electrical and Electronic Engineering
Algorithm
Voltage
Subjects
Details
- ISSN :
- 15579948 and 02780046
- Volume :
- 66
- Database :
- OpenAIRE
- Journal :
- IEEE Transactions on Industrial Electronics
- Accession number :
- edsair.doi...........e2ff8c20861433f002eb7f90c09f07b9
- Full Text :
- https://doi.org/10.1109/tie.2018.2849982