Design of predictive control systems with a disturbance estimation mechanism for motion control

2020 Fiscal Year Final Research Report

• Project/Area Number: 17K06233
• Research Category: Grant-in-Aid for Scientific Research (C)
• Allocation Type: Multi-year Fund
• Section: 一般
• Research Field: Dynamics/Control
• Research Institution: Akita Prefectural University
• Principal Investigator: Satoh Toshiyuki 秋田県立大学, システム科学技術学部, 准教授 (40315635)
• Co-Investigator(Kenkyū-buntansha): 齋藤 直樹 秋田県立大学, システム科学技術学部, 教授 (60315645)
• Project Period (FY): 2017-04-01 – 2021-03-31
• Keywords: 機械力学・制御 / モデル予測制御 / 状態推定器

Outline of Final Research Achievements

For the aim of motion control, we have studied on model precitive control strategies that have an ability to estimate and cancel disturbance without additive mechcanisms such as disturbance observer. Predictive Functional Control (PFC), which is a model predictive control (MPC), is mainly addressed in this research. Generally speaking, PFC does not require the state-estimator. However, to estimate disturbancce and cancel it indirectly, we intendedly introduced the prediction-type estimator as an internal model in PFC, constructed an augmented system, and derived the optimal control law. The PFC with such structure is abbreviated as PFC_EBIM. We applied PFC_EBIM to a position control problem of a mechatronics servo system. We experimentally confirmed that the designed PFC_EBIM efficiently estimated and canceled disturbance such as friction and improved the tracking performance.

Free Research Field

制御工学

Academic Significance and Societal Importance of the Research Achievements

ロボットやメカトロニクス機器のモーション・コントロールにおいて，位置や速度，力などの物理量を精度良く，かつ高速に制御する必要がある，このような制御を行おうとする場合には一般に，制御対象の精密な動力学モデルが必要となる．しかし，精密なモデルの構築には多大なコストが掛かる．本研究成果の意義は，こうしたコストを低減化し，産業的に主流となっているPID制御よりも高度なmモデルベースト制御手法を提供する点にある．また，制御工学的にも，主となるフィードバック補償器と外乱推定・除去メカニズムとを統合した設計法を開発することは意義がある．