Improved Renyi Entropy Benchmark for Performance Assessment of Common Cascade Control System
Year: 2019
Type: article
Abstract: To deal with the inconsistency of the minimum variance (MV) benchmark in evaluating non-Gaussian disturbance systems, this paper proposed a new benchmark, which combined entropy with output mean value. For a cascade control system, the new benchmark was constructed by analyzing the weakness of the MV benchmark and the pure Renyi entropy benchmark. In order to estimate the more accurate performance of the unknown system, an improved estimation of distribution algorithm based on entropy criterion is given. It can identify the disturbance distribution and calculate the new index evaluation value. Finally, different disturbance distributions were used to verify the consistency of the new index. The experimental results show that the proposed index and algorithms are consistent and effective in evaluating the performance of the unknown systems with non-Gaussian disturbance.
Source: IEEE Access
Authors: Qian Zhang, Ya-Gang Wang, Feifei Lee, Qiu Chen, Zhen Sun
Institution: University of Shanghai for Science and Technology
Language: English
Subfield: Control and Systems Engineering
Field: Engineering
Domain: Physical Sciences
Open Access status: gold
Estimated APC paid: $1,750
Awards: G3340971499, G424266510, G8030318055
OpenAlex ID: W2910690466
