Model prediction-based approach to fault-tolerant control with applications

Abstract

Abstract-Fault-tolerant control (FTC) is an integral component in industrial processes as it enables the system to continue robust operation under some conditions. In this paper, an FTC scheme is proposed for interconnected systems within an integrated design framework to yield a timely monitoring and detection of fault and reconfiguring the controller according to those faults. The unscented Kalman filter (UKF)-based fault detection and diagnosis system is initially run on the main plant and parameter estimation is being done for the local faults. This critical information is shared through information fusion to the main system where the whole system is being decentralized using the overlapping decomposition technique. Using this parameter estimates of decentralized subsystems, a model predictive control (MPC) adjusts its parameters according to the fault scenarios thereby striving to maintain the stability of the system. Experimental results on interconnected continuous time stirred tank reactors (CSTR) with recycle and quadruple tank system indicate that the proposed method is capable to correctly identify various faults, and then controlling the system under some conditions.

Enhancing Resilience: Smart Grid Cybersecurity and Fault Diagnosis Strategies

“…Fault diagnosis plays a critical role in grid resilience by enabling utilities to swiftly detect, isolate, and address faults or abnormalities in the grid infrastructure [87]. Grid resilience refers to the ability of the power grid to withstand and recover from disruptions, such as equipment failures, natural disasters, cyber-attacks, or human errors, while maintaining the reliable delivery of electricity to consumers [88].…”

Safeguarding Stability: Strategies for Addressing Dynamic System Variations in Power Grid Cybersecurity

“…Natural Language Processing (NLP): NLP-driven AI systems can sift through vast amounts of textual data from social media, news outlets, or other sources to gather insights, assess public sentiment, and provide early indicators of potential issues or crises [93]. Adaptive Systems for Decision-Making: AI-powered decision support systems can assist decision-makers by processing and analyzing information rapidly, providing recommendations, and even learning from past decisions and outcomes to refine future suggestions [94]. Climate Change and Environmental Monitoring: AI and ML models can analyze environmental data to track changes, predict trends, and propose mitigation strategies for climate-related issues like deforestation, pollution, or biodiversity loss.…”

Robust H∞ fault-tolerant control for stochastic Markov jump time-delay systems with actuator faults and application

“…In recent years, many scholars have had some achievements in the research of robust faulttolerant control [19][20][21][22]. Ma et al [19] have investigated the networked nonfragile H ∞ control problem for Lipschitz nonlinear system with quantization and packet dropout in both feedback and forward channels.…”

“…By means of fuzzy logic systems, approximating unknown nonlinear functions, a fuzzy adaptive observer is designed to es timate the unmeasured state. Mahmoud and Khalid [22] have proposed for interconnected systems within the framework of integrated design a faulttolerant control scheme to monitor and detect the faults in time, and to reconfigure the controller according to these faults.…”