含有自校正模型的加權多模型自適應控制

張玉振; 李擎; 張維存

doi:10.13374/j.issn2095-9389.2018.11.013

含有自校正模型的加權多模型自適應控制

doi: 10.13374/j.issn2095-9389.2018.11.013

北京科技大學自動化學院, 北京 100083

基金項目:

國家自然科學基金資助項目(61520106010,61741302)

詳細信息

中圖分類號: TP301.6
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- 文章訪問數: 790
- HTML全文瀏覽量: 252
- PDF下載量: 14
- 被引次數: 0
出版歷程
- 收稿日期: 2017-11-07

Weighted multiple model adaptive control with self-tuning model

School of Automation and Electrical Engineering, University of Science and Technology Beijing, Beijing 100083, China

摘要

摘要: 研究了含有大范圍參數不確定性離散時間被控對象的加權多模型自適應控制問題(包括模型集構建和加權算法分析).通過構建含有自校正模型和多個固定模型的模型集覆蓋并逼近被控對象,在模型輸出誤差可分的前提下,采用基于模型輸出誤差性能指標的加權算法,并依據固定模型中是否包含真實被控對象模型的不同情形分析加權算法的收斂性.在權值收斂的前提下,利用虛擬等價系統理論,分析了參數未知線性時不變和參數跳變的情形,在不依賴于特定局部控制算法的基礎上,證明了此種模型集構建下的加權多模型自適應控制系統的穩定性和收斂性,放寬了先期加權多模型自適應控制系統穩定性分析中關于模型集構建的約束條件.最終,通過計算機MATLAB仿真,驗證了此類加權多模型自適應控制系統的收斂性和閉環穩定性.
- 離散系統 /
- 多模型自適應控制 /
- 加權算法 /
- 穩定性 /
- 收斂性
Abstract: The issues of model set construction and weighting algorithm analysis in multiple model adaptive control of discrete-time systems with large parameter uncertainty are considered in this paper. First, to improve system performance by reducing the calculation burden and relaxing the convergence conditions for the classical weighting algorithm, a new weighting algorithm is adopted, which is based on the model output errors of the multi-model adaptive control system with a self-tuning model. Second, the weighting algorithm convergence is analyzed in two cases:when the model set contains the true model of plant and it tends to the fixed model, and when the model set does not contain the true model of plant and it tends to the self-tuning model. Third, according to the virtual equivalent system (VES) concept and methodology, the stability of weighted multiple model adaptive control (WMMAC) with a self-tuning model is presented under a unified framework. The analysis procedures for linear time-invariant (LTI) and parameter jump plants are independent of specific local control methods and weighting algorithm, which only require that each local controller stabilizes the corresponding local model, the output of the formed closed-loop system tracks the reference signal, and the weighting algorithm is convergent. The principal contributions of the paper are the analysis of global stability and the convergence of the overall system with a self-tuning model. Compared with the stability results of WMMAC in the early stage, the constraint condition that the model set only has fixed models is relaxed, which can enlarge the application range of the stability results in theory. In addition, because of the introduction of a self-tuning controller, the control performance of the system is significantly improved when the real model of the plant is not included in the model set. Finally, computer simulation results verify the feasibility and effectiveness of the proposed method.
- discrete-time system /
- multiple model adaptive control /
- weighting algorithm /
- stability /
- convergence

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