针对具有非概率不确定性的结构的可靠模型预测振动控制

IF 4.6 2区 工程技术 Q1 CONSTRUCTION & BUILDING TECHNOLOGY
Jinglei Gong, Xiaojun Wang
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引用次数: 0

摘要

本文提出了一种新的可靠模型预测控制(MPC)方法,用于具有非概率不确定性的结构主动振动控制。首先,通过将非概率可靠性约束纳入名义 MPC,建立了可靠 MPC 框架。基于一阶泰勒展开和第一通道理论,提出了适合在线计算的高效非概率可靠性分析方法。还进一步提出了一种非概率卡尔曼滤波器,用于确定系统状态及其不确定区域。与大多数稳健型 MPC 方法不同,所提出的可靠型 MPC 侧重于满足结构可靠性方面的状态约束,更适用于具有严格安全要求的结构。与现有的基于可靠性的振动控制方法相比,可靠 MPC 无需了解扰动情况,对载荷环境的适应性更强。通过数值示例和工程案例研究,验证了所提出的可靠 MPC 的有效性和优越性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Reliable Model Predictive Vibration Control for Structures with Nonprobabilistic Uncertainties

Reliable Model Predictive Vibration Control for Structures with Nonprobabilistic Uncertainties

This paper proposes a novel reliable model predictive control (MPC) method for active vibration control of structure with nonprobabilistic uncertainties. First, the framework of reliable MPC is established by integrating nonprobabilistic reliability constraints into nominal MPC. Based on the first-order Taylor expansion and first-passage theory, an efficient nonprobabilistic reliability analysis method that is suitable for online computation is proposed. A nonprobabilistic Kalman filter is further proposed for determine system states and their uncertain region. Unlike most robust MPC approaches, the proposed reliable MPC focuses on the satisfaction of state constraints in terms of structural reliability and is more suitable for structures with stringent safety requirements. Compared to existing reliability-based vibration control methods, reliable MPC requires no knowledge of disturbance and exhibits greater adaptability to load environments. The effectiveness and superiority of the proposed reliable MPC are validated through a numerical example and an engineering case study.

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来源期刊
Structural Control & Health Monitoring
Structural Control & Health Monitoring 工程技术-工程:土木
CiteScore
9.50
自引率
13.00%
发文量
234
审稿时长
8 months
期刊介绍: The Journal Structural Control and Health Monitoring encompasses all theoretical and technological aspects of structural control, structural health monitoring theory and smart materials and structures. The journal focuses on aerospace, civil, infrastructure and mechanical engineering applications. Original contributions based on analytical, computational and experimental methods are solicited in three main areas: monitoring, control, and smart materials and structures, covering subjects such as system identification, health monitoring, health diagnostics, multi-functional materials, signal processing, sensor technology, passive, active and semi active control schemes and implementations, shape memory alloys, piezoelectrics and mechatronics. Also of interest are actuator design, dynamic systems, dynamic stability, artificial intelligence tools, data acquisition, wireless communications, measurements, MEMS/NEMS sensors for local damage detection, optical fibre sensors for health monitoring, remote control of monitoring systems, sensor-logger combinations for mobile applications, corrosion sensors, scour indicators and experimental techniques.
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