Fault detection and isolation using viability theory and interval observers

This paper proposes the use of interval observers and viability theory in fault detection and isolation (FDI). Viability theory develops mathematical and algorithmic methods for investigating the viability constraints characterisation of dynamic evolutions of complex systems under uncertainty. These methods can be used for checking the consistency between observed and predicted behaviour by using simple sets that approximate the exact set of possible behaviour (in the parameter or state space). In this paper, FDI is based on checking for an inconsistency between the measured and predicted behaviours using viability theory concepts and sets. Finally, an example is provided in order to show the usefulness of the proposed approachPeer ReviewedPostprint (author's final draft

A dual source fed eleven level switched capacitor multilevel inverter with voltage boosting capability

This work introduces an 11-level switched-capacitor multilevel inverter (SCMLI) designed for solar photo-voltaic (PV) applications, capitalizing on the growing popularity of multilevel inverters due to their superior power quality. With a 1.67-times boosting capability, the proposed SCMLI employs 10 switches, 2 DC supplies, and 2 capacitors to achieve an 11-level output voltage waveform. The topology requires only seven driver circuits, incorporating 2 bidirectional switches and 3 complementary pairs of switches. The proposed inverter has intrinsic capacitor self-balancing features since the capacitors are connected across the DC voltage source at different times throughout a basic cycle to charge the capacitors at a level of input voltage. A thorough comparison between the topology and recently developed SCMLI’s has been presented. The comparison demonstrates the effectiveness in terms of switches, capacitors, sources, efficiency, total standing voltage (TSV), and boosting capacity. To experimentally validate its performance, the suggested SCMLI undergoes testing using a frequency-based switching method. The topology exhibits low total harmonic distortion (THD) of 7.65% in its output voltage waveform and 0.89% in the output current waveform

Analysis of the behavior of coupled loudspeakers in a MIMO ANC system in an enclosure

In this paper the problem of coupling of acoustic sources in a confined space is treated. By considering the coupling of sources in a rectangular enclosure the set of coupled equations governing the acoustical behavior of enclosure are solved. The resulted model can be used to analyze the behavior of a multi-input multi-output (MIMO) active noise control (ANC) system in real application where coupling of sources can not be neglected. Comparison of results to the case that coupling will be ignored among loudspeakers shows that coupling will effectively change the strength of sources and hence the required voltage signals to drive the loudspeakers. The developed model gives an improved description of the acoustic environment inside the rectangular enclosure, especially in an ANC system when sources are placed in a fraction of wavelength and the interaction among sources will change the radiation impedance of other sources

Volterra-Laguerre modeling for NMPC

Volterra series are perhaps the best understood nonlinear system representations in signal processing. They can be used to model a wide class of nonlinear systems. However, since these models are non-parsimonious in parameters, the symmetric kernel parameters are used This model is used to evaluate identification of a pH-neutralization process. The aim is to use this model in nonlinear model predictive control framework. For this purpose various orders of the Laguerre filters and also Volterra kernels are tested and the results are compared in terms of the validation of these models. The results show that to have a good trade off between simplicity of the model and its corresponding fitness, the selected nonlinear Volterra model has the memory of 3 while the number of its kennel is 4. The VAF of this model is 99.63% which is completely acceptable for nonlinear model predictive control applications

Adaptive Volterra-Laguerre modeling for NMPC

Model Predictive Control (MPC) is one of the most successful controllers in process industries. Process industries need a predictive controller that is low cost, easy to setup and maintains an adaptive behavior which accounts for plant changes, nonlinearities and under-modeling. To this aim, it is necessary to obtain a suitable adaptive modeling that can be easily used in nonlinear MPC framework. Experiments show performance advantages of Volterra series in terms of convergence, interpretability, and system sizes that can be handled They can be used to model a wide class of nonlinear systems. However, since these models are in general non-parsimonious in parameters, in this paper the symmetric kernel parameters and Laguerre filtering are used to generate regression vector. The performance of the proposed method is evaluated by simulation results obtained for identification experiments of a pH-neutralization process

Fault tolerance evaluation of nonlinear systems using viability theory

Trabajo presentado a la 3rd Conference on Control and Fault Tolerant Systems, celebrada en Barcelona (España) del 7 al 9 de septiembre de 2016.This paper presents a computational procedure based on viability theory to evaluate the fault tolerance admissibility of a given fault configuration of a nonlinear system controlled by means of a predictive control law. The admissible solution set for the control problem, including the effect of faults, is determined using viability kernel and capture basin. Finally, water heater part of pasteurization process is provided as benchmark in order to show the usefulness of viability theory for fault tolerance evaluation.This work has been partially funded by the Spanish Government (MINECO) through the project CICYT ECOCIS (ref. DPI2013-48243-C2-1-R), by MINECO and FEDER through the project CICYT HARCRICS (ref. DPI2014-58104-R).Peer Reviewe

Verification of the control system performance using viability theory

© 2017 IEEE. Personal use of this ma terial is permitted. Permission from IEEE must be obtained for al l other uses, in any current or future media, including reprinting /republishing this material for advertising or promotional purposes, creating new collective works, f or resale or redistribution to se rvers or lists, or reuse of any copyrighted compone nt of this work in other worksThe development of efficient methods for the control system performance verification has drawn a lot of attention recently. In this paper, the use of viability theory for this purpose is investigated in case of non-linear systems. In particular, verification algorithms based on the use of the computation of invariance and viability kernels and capture basin are proposed. A Lagrangian method has been used in order to approximate these sets for nonlinear systems. Because of simplicity and efficient computations, zonotopes are adopted for set representation. An application example based on a well known control benchmark is provided in order to show the effectiveness of the proposed method.Peer Reviewe

Verification of the control system performance using viability theory

© 2017 IEEE. Personal use of this ma terial is permitted. Permission from IEEE must be obtained for al l other uses, in any current or future media, including reprinting /republishing this material for advertising or promotional purposes, creating new collective works, f or resale or redistribution to se rvers or lists, or reuse of any copyrighted compone nt of this work in other worksThe development of efficient methods for the control system performance verification has drawn a lot of attention recently. In this paper, the use of viability theory for this purpose is investigated in case of non-linear systems. In particular, verification algorithms based on the use of the computation of invariance and viability kernels and capture basin are proposed. A Lagrangian method has been used in order to approximate these sets for nonlinear systems. Because of simplicity and efficient computations, zonotopes are adopted for set representation. An application example based on a well known control benchmark is provided in order to show the effectiveness of the proposed method.Peer ReviewedPostprint (author's final draft

Fault detection and isolation using viability theory and interval observers

This paper proposes the use of interval observers and viability theory in fault detection and isolation (FDI). Viability theory develops mathematical and algorithmic methods for investigating the adaptation to viability constraints of evolutions governed by complex systems under uncertainty. These methods can be used for checking the consistency between observed and predicted behavior by using simple sets that approximate the exact set of possible behavior (in the parameter or state space). In this paper, fault detection is based on checking for an inconsistency between the measured and predicted behaviors using viability theory concepts and sets. Finally, an example is provided in order to show the usefulness of the proposed approach.Postprint (author's final draft