Fault detection model-based controller for process systems

Minh, Vu Trieu; Afzulpurkar, Nitin; Muhamad, Wan Mansor Wan

doi:10.1002/asjc.346

Cited by 13 publications

(10 citation statements)

References 36 publications

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“…Exact model predictive law and observer formulation is important in some cases like fault diagnostics and fast implementation of a given predictive controller . Reference approximated the optimal control law with a piecewise constant function defined over a hyper‐cube partition of the system state space by solving a set of nonconvex polynomial optimization problems, whose approximate solutions are computed by means of semidefinite relaxation techniques for semialgebraic problems.…”

Section: Introductionmentioning

confidence: 99%

Robust Output Feedback Model Predictive Control: A Stochastic Approach

Mohammadkhani

Bayat

Jalali

2017

Asian Journal of Control

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This paper addresses the robust explicit model predictive control scheme for linear systems with input and output constraint in the presence of disturbances and noise. Conditions for disturbance rejection are established by incorporating a full state/disturbance observer. The separation principle is applied to design an optimal observer in the unconstrained problem. Then, an efficient algorithm is developed to explicitly design observer gains by minimizing a quadratic performance criterion. It is shown that the solution includes a set of regions with piecewise affine functions of the state and reference vectors and a set of regions with optimal observers. In the proposed method, two sets of partitions associated with the control law and the observer gains are obtained. Therefore, the online computation includes finding the active regions of both observer and control law partitions in which the current state is located. The proposed technique is particularly attractive for a wide range of practical problems where the exact model of the actual system is not available.

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Section: Introductionmentioning

confidence: 99%

Robust Output Feedback Model Predictive Control: A Stochastic Approach

Mohammadkhani

Bayat

Jalali

2017

Asian Journal of Control

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“…This common Lyapunov will guarantee the stability for all switching sequences among those controllers. The system modelling is referred in [9] and [10].…”

Section: Introductionmentioning

confidence: 99%

Performances of PID and Different Fuzzy Methods for Controlling a Ball on Beam

et al. 2016

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This paper develops and analyses the performances evaluation of different control strategies applied for a nonlinear motion of a ball on a beam system. Comparison results provide in-depth comprehension on the stable ability of different controllers for this real mechanical application. The three different controllers are a conventional PID method, a Mamdani-type fuzzy rule method and a Sugeno-type fuzzy rule method. In this study, the PID shows the fastest sinuous reference tracking while the Mamdani-type fuzzy method proves the highest stability performance for tracking square wave motions.

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“…Fault diagnoses and control are an important problem in discrete event systems [6,19,20,23,31]. However, a separate fault diagnosis is insufficient as it enables us simply to detect and recover errors without recovering important lost information.…”

Section: Introductionmentioning

confidence: 99%

Confusion Diagnosis and Control of Discrete Event Systems Using Synchronized Petri Nets

Chen¹,

Li²,

Al-Ahmari³

et al. 2013

Asian Journal of Control

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The mixture of conflicting transitions and concurrent transitions in Petri nets can lead to the loss of conflict information, which is an unfortunate phenomenon in discrete event systems, usually called confusions. They appear in the processes of resource allocation and may cause incomplete decision‐making on conflicts. Hence, a confusion detection method and a control strategy are required. This paper proposes a class of confusion control event reconfigurable (CCR) nets to control confusions with the evolution of markings. Their properties such as safety and liveness with the mapping from original Petri nets to CCR nets are investigated. Two confusion control algorithms are proposed to generate a set of control code sequences, which can completely control the occurrences of confusions. Then, a confusion detection algorithm with polynomial time complexity is developed. Finally, an example of confusion analysis in automated manufacturing systems is presented.

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Fault detection model-based controller for process systems

Cited by 13 publications

References 36 publications

Robust Output Feedback Model Predictive Control: A Stochastic Approach

Robust Output Feedback Model Predictive Control: A Stochastic Approach

Performances of PID and Different Fuzzy Methods for Controlling a Ball on Beam

Confusion Diagnosis and Control of Discrete Event Systems Using Synchronized Petri Nets

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