Active fault tolerant active vibration dual-mode Model Predictive Control for a smart flexible beam

IF 4.6 2区 计算机科学 Q1 AUTOMATION & CONTROL SYSTEMS
A.R. Prashant , Arun K. Tangirala , C. Lakshmana Rao , M.V.V.S. Murthy
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Abstract

To address the challenges of vibration control in flexible systems, an active fault-tolerant control framework utilizing dual-mode Model Predictive Control (MPC) is introduced. This advanced approach integrates fault detection, isolation, and accommodation mechanisms directly into the control system to ensure continuous and reliable operation in the presence of soft sensor faults, minimizing performance degradation and safeguarding system integrity. The framework leverages the predictive capabilities of MPC and the dual-mode stability concept to achieve an optimal balance between active vibration suppression and fault accommodation. In this framework, dual-mode MPC is particularly advantageous for managing system constraints, offering better adaptability to uncertainties and unexpected disturbances compared to traditional controllers. A detailed evaluation using a Smart Flexible Beam (SFB), employed as an active vibration isolation system, highlights the superior performance of dual-mode MPC. It outperforms standard MPC by providing enhanced fault tolerance in scenarios involving soft sensor failures and offers better constraint-handling capabilities than Linear Quadratic (LQ) controllers. Furthermore, dual-mode MPC demonstrates robustness to parametric variations and ease of tuning, making it a versatile and effective solution. Through comprehensive simulation studies, the proposed framework showcases its efficacy in achieving significant vibration attenuation, maintaining system stability, and ensuring operational reliability, particularly for critical applications such as aerospace. This makes it a promising approach for enhancing the resilience and robustness of smart flexible systems in high-performance environments.
智能柔性梁的主动容错主动振动双模模型预测控制
为了解决柔性系统振动控制的难题,提出了一种基于双模模型预测控制(MPC)的主动容错控制框架。这种先进的方法将故障检测,隔离和调节机制直接集成到控制系统中,以确保在存在软传感器故障的情况下持续可靠地运行,最大限度地减少性能下降并保护系统完整性。该框架利用MPC的预测能力和双模稳定性概念来实现主动振动抑制和故障调节之间的最佳平衡。在这个框架中,双模MPC在管理系统约束方面特别有利,与传统控制器相比,它对不确定性和意外干扰具有更好的适应性。采用智能柔性梁(SFB)作为主动隔振系统进行详细评估,突出了双模MPC的优越性能。它通过在涉及软传感器故障的场景中提供增强的容错性来优于标准MPC,并提供比线性二次(LQ)控制器更好的约束处理能力。此外,双模MPC显示了对参数变化的鲁棒性和易于调谐,使其成为一种通用而有效的解决方案。通过全面的仿真研究,所提出的框架展示了其在实现显着的振动衰减,保持系统稳定性和确保运行可靠性方面的有效性,特别是在航空航天等关键应用中。这使得它成为一种在高性能环境中增强智能灵活系统的弹性和鲁棒性的有前途的方法。
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来源期刊
Control Engineering Practice
Control Engineering Practice 工程技术-工程:电子与电气
CiteScore
9.20
自引率
12.20%
发文量
183
审稿时长
44 days
期刊介绍: Control Engineering Practice strives to meet the needs of industrial practitioners and industrially related academics and researchers. It publishes papers which illustrate the direct application of control theory and its supporting tools in all possible areas of automation. As a result, the journal only contains papers which can be considered to have made significant contributions to the application of advanced control techniques. It is normally expected that practical results should be included, but where simulation only studies are available, it is necessary to demonstrate that the simulation model is representative of a genuine application. Strictly theoretical papers will find a more appropriate home in Control Engineering Practice''s sister publication, Automatica. It is also expected that papers are innovative with respect to the state of the art and are sufficiently detailed for a reader to be able to duplicate the main results of the paper (supplementary material, including datasets, tables, code and any relevant interactive material can be made available and downloaded from the website). The benefits of the presented methods must be made very clear and the new techniques must be compared and contrasted with results obtained using existing methods. Moreover, a thorough analysis of failures that may happen in the design process and implementation can also be part of the paper. The scope of Control Engineering Practice matches the activities of IFAC. Papers demonstrating the contribution of automation and control in improving the performance, quality, productivity, sustainability, resource and energy efficiency, and the manageability of systems and processes for the benefit of mankind and are relevant to industrial practitioners are most welcome.
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