A unified framework for detection, isolation and compensation of actuator faults in uncertain particulate processes

Giridhar, Arthi; El‐Farra, Nael H.

doi:10.1109/acc.2008.4587003

Cited by 7 publications

(7 citation statements)

References 27 publications

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“…I I (10) For the above-described augmented system eq 9, the corresponding FTC can be designed to yield tracking performance under both normal and admissible faults.…”

Section: Traditional Fault-tolerant Controlmentioning

confidence: 99%

Predictive Functional Control for Linear Systems under Partial Actuator Faults and Application on an Injection Molding Batch Process

Zhang

Xue

et al. 2014

Ind. Eng. Chem. Res.

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Actuator faults commonly exist in process control systems. Due to these faults, the controller may not achieve the required target, so the control performance may degrade. In this paper, the fault-tolerant control is designed through a predictive functional control framework to deal with partial actuator faults and unknown disturbances, which exist widely in process control systems. Based on a new state space formulation of the process models, an improved predictive functional control scheme is proposed, where satisfactory closed-loop control performance is achieved even with unknown disturbances and actuator faults. With the actuator faults, the system becomes a process with parameter uncertainties. Hence, a sufficient condition that guarantees closed-loop robust stability is presented. Simulations are given to illustrate the feasibility and effectiveness of the proposed scheme.

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“…I I (10) For the above-described augmented system eq 9, the corresponding FTC can be designed to yield tracking performance under both normal and admissible faults.…”

Section: Traditional Fault-tolerant Controlmentioning

confidence: 99%

Predictive Functional Control for Linear Systems under Partial Actuator Faults and Application on an Injection Molding Batch Process

Zhang

Xue

et al. 2014

Ind. Eng. Chem. Res.

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“…For example, Wang et al [4] put forward an iterative learning control (ILC) scheme for batch processes under partial actuator faults according to a particular 2D Fornasini-Marchsini model. Giridhar and El-Farra [5] proposed a robust detection, isolation, and compensation of control actuator faults based on the framework of feedback robust control. Jin et al [6] proposed an improved ILC scheme to control the nonlinear constrained system with actuator failures.…”

Section: Introductionmentioning

confidence: 99%

Fractional-Order Predictive Functional Control of Industrial Processes with Partial Actuator Failures

Dai

et al. 2020

Complexity

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As the actuator faults in an industrial process cause damage or performance deterioration, the design issue of an optimal controller against these failures is of great importance. In this paper, a fractional-order predictive functional control method based on population extremal optimization is proposed to maintain the control performance against partial actuator failures. The proposed control strategy consists of two key ideas. The first one is the application of fractional-order calculus into the cost function of predictive functional control. Since the knowledge of analytical parameters including the prediction horizon, fractional-order parameter, and smoothing factor in fractional-order predictive functional control is not known, population extremal optimization is employed as the second key technique to search for these parameters. The effectiveness of the proposed controller is examined on two industrial processes, e.g., injection modeling batch process and process flow of coke furnace under constant faults, time-varying faults, and nonrepetitive unknown disturbance. The comprehensive simulation results demonstrate the performance of the proposed control method by comparing with a recently developed predictive functional control, genetic algorithm, and particle swarm optimization-based versions in terms of four performance indices.

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“…The use of model‐predictive control (MPC) has been proposed to improve process safety . Other methods used for safety analysis or improved safety include: (a) sneak analysis to identify hazards by detecting paths through which unwanted material or energy is transferred between the process components, (b) hierarchical task analysis, which is a systematic qualitative technique of analyzing hazards associated with human errors, (c) hazardous human‐error analysis to identify hazards arising from human‐machinery interactions, (d) failure mode and effects analysis to identify hazards and predict their consequences, (e) alarm standards design, (f) Bayesian networks, (g) detection, isolation, and compensation of actuator faults, (h) shortcut risk assessment, and (i) human reliability analysis . Also, several analytical tools have been developed and used for operability analysis .…”

Section: Introductionmentioning

confidence: 99%

Model‐predictive safety system for proactive detection of operation hazards

Ahooyi¹,

Soroush²,

Arbogast

et al. 2016

AIChE Journal

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A method of designing model-predictive safety systems that can detect operation hazards proactively is presented. Such a proactive safety system has two major components: a set of operability constraints and a robust state estimator. The safety system triggers alarm(s) in real time when the process is unable to satisfy an operability constraint over a receding time-horizon into the future. In other words, the system uses a process model to project the process operability status and to generate alarm signals indicating the presence of a present or future operation hazard. Unlike typical existing safety systems, it systematically accounts for nonlinearities and interactions among process variables to generate alarm signals; it provides alarm signals tied to unmeasurable, but detectable, state variables; and it generates alarm signals before an actual operation hazard occurs. The application and performance of the method are shown using a polymerization reactor example.

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A unified framework for detection, isolation and compensation of actuator faults in uncertain particulate processes

Cited by 7 publications

References 27 publications

Predictive Functional Control for Linear Systems under Partial Actuator Faults and Application on an Injection Molding Batch Process

Predictive Functional Control for Linear Systems under Partial Actuator Faults and Application on an Injection Molding Batch Process

Fractional-Order Predictive Functional Control of Industrial Processes with Partial Actuator Failures

Model‐predictive safety system for proactive detection of operation hazards

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