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40 results on '"Najariyan, Marzieh"'

7. Constrained model predictive control for networked jump systems under denial‐of‐service attacks and time delays.

Author

Qiu, Li, Chen, Runjie, Lin, Shaolie, Liu, Xueliang, and Najariyan, Marzieh

Subjects
PREDICTIVE control systems, GLOBAL asymptotic stability, DENIAL of service attacks, TIME delay systems, MARKOVIAN jump linear systems
Abstract

This article addresses the problem of model predictive control of networked jump systems in the presence of DoS attacks and time delays. In the structural framework of the network predictive control system, we mathematically model the networked jump system by using Markov chains to describe the time delays and a polytope model to describe the jump system phenomenon, considering the properties of DoS attacks and time delays. Based on this, we propose a strategy to lessen the effect of network constraints on the control performance of the system. This strategy involves the corresponding control inputs from the control sequence for real‐time active compensation. It includes adjusting the control sequence application length variation based on the duration of the DoS attacks and time delays at each moment. In addition, we demonstrate the recursive feasibility of the control strategy and the global asymptotic stability of the control system from a theoretical perspective through the Lyapunov stability theory. Finally, the effectiveness of the proposed strategy is verified by simulation arithmetic. [ABSTRACT FROM AUTHOR]

Published
2024
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10. Networked H∞ Control and its Applications for a Multi-Station Cooperative Motion System

Author

Qiu, Li, Wen, Yidan, Monirul, Islam Md., Najariyan, Marzieh, Pan, Jianfei, and Wu, Zongze

Abstract

This paper analyzes each station node’s electromagnetic and electronic characteristics for the multi-station cooperative motion system (MSCMS). The closed-loop MSCMS model is built based on a networked control scheme by considering the communication constraints and external disturbance. Considering the station nodes position compensation and topological structure among multi-station nodes, stability and stabilization conditions for the networked MSCMS with random time delays are proposed by combing the Markov modeling method and the networked $H_{\infty} $ control theory based on constructing a Lyapunov functional. In order to improve the cooperative motion precision, a networked $H_{\infty} $ controller is designed for the MSCMS by combining a cooperative motion error compensation scheme and inequality techniques. To verify the effectiveness of the proposed method, several groups of experimental results are presented in this paper. Note to Practitioners—With the industry’s extensive application of multi-station motor system collaborative control technology, building an NMSCMS model with suitable motors and network structure is vital. The main problem this paper researched is how to guarantee the performance of the system under uncertain disturbance and random delays. Due to the issues mentioned above, a corresponding $H_{\infty} $ controller is designed, and the controller is verified by experimental in which motor position errors under different situations are compared. Future research focuses on the same problem with a more complicated network structure and more factors, making the system description more complex.

Published
2024
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13. Solving First Order Linear Fuzzy Differential Equations System

Author

Najariyan, Marzieh, Mazandarani, Mehran, Balas, Valentina Emilia, Kacprzyk, Janusz, Series editor, Pal, Nikhil R., Advisory editor, Bello Perez, Rafael, Advisory editor, Corchado, Emilio S., Advisory editor, Hagras, Hani, Advisory editor, Kóczy, László T., Advisory editor, Kreinovich, Vladik, Advisory editor, Lin, Chin-Teng, Advisory editor, Lu, Jie, Advisory editor, Melin, Patricia, Advisory editor, Nedjah, Nadia, Advisory editor, Nguyen, Ngoc Thanh, Advisory editor, Wang, Jun, Advisory editor, Balas, Valentina Emilia, editor, Jain, Lakhmi C., editor, and Balas, Marius Mircea, editor

Published
2018
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14. Fuzzy Fractional Derivative: A New Definition

Author

Najariyan, Marzieh, Mazandarani, Mehran, Balas, Valentina Emilia, Kacprzyk, Janusz, Series editor, Pal, Nikhil R., Advisory editor, Bello Perez, Rafael, Advisory editor, Corchado, Emilio S., Advisory editor, Hagras, Hani, Advisory editor, Kóczy, László T., Advisory editor, Kreinovich, Vladik, Advisory editor, Lin, Chin-Teng, Advisory editor, Lu, Jie, Advisory editor, Melin, Patricia, Advisory editor, Nedjah, Nadia, Advisory editor, Nguyen, Ngoc Thanh, Advisory editor, Wang, Jun, Advisory editor, Balas, Valentina Emilia, editor, Jain, Lakhmi C., editor, and Balas, Marius Mircea, editor

Published
2018
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15. Stability and Stabilization of Semi-Markov Jump Linear System With DoS Attacks

Author

Qiu, Li, Zhou, Shuyou, Wen, Yidan, Najariyan, Marzieh, and Liu, Chengxiang

Abstract

In this brief, the denial of service (DoS) attacks on the communication channel of the semi-Markov jump system are studied. Firstly, the DoS attacks are modeled as a Markov chain, and then a networked semi-Markov jump system model with DoS attacks is proposed. Based on this model, the network semi-Markov jump system stability under the DoS attacks is analyzed, and the mean square stability lemma is derived. According to the mean square stability condition of the system, the sufficient condition of the mean square stability of the system is put forward, and the mean square stability controller is designed according to the sufficient condition. Due to the introduction of the DoS attacks, a new Lyapunov function is constructed, and linear matrix inequality(LMI) is derived. Finally, several groups of comparative simulation are constructed to verify the compensation effect of control strategy on DoS attacks and frequent system switching.

Published
2024
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29. Proportional Predictive Control of Networked Linear Switched Reluctance Machine System With Time-Varying Delay

Author

Qiu, Li, Deng, Tao, Yang, Xiaomei, Najariyan, Marzieh, Pan, Jianfei, and Liu, Chengxiang

Subjects
General Materials Science
Abstract

In this article, a proportional predictive (PP) control strategy is proposed and a high-precision position tracking controller is designed for the networked linear switched reluctance machine system (NLSRMS) with time-varying delay. The closed-loop system model of the NLSRMS is constructed based on the PP control strategy. The stability conditions of the system are proposed by combining the optimal control value calculated by the cost function. The controller of the closed-loop NLSRMS is designed by using continuously updated predictive output equation information based on calculation. The comparative study of the proposed PP and PID control methods is presented by tracking several types of signals. The maximum steady errors of PP and PID control strategies are 0.2 mm and 2 mm under the sinusoidal signal, respectively. The maximum steady errors of PP and PID control strategies are 0.07 mm and 0.7 mm under the square signal, respectively. The simulation results show the effectiveness of the proposed PP control strategy.

Published
2022

36. Fuzzy optimal control of a poisoning-pest model by using α-cuts.

Author

Farahi, Mohamad Hadi, Keshtegar, Mansooreh, and Najariyan, Marzieh

Subjects
PEST control, DYNAMICAL systems, FUZZY sets, OPTIMAL control theory, CALCULUS of variations, SAFETY
Abstract

In this article, a dynamical system represents the poisoning-pest model is considered. At First a mathematical model for the poisoning-pest model is simulated. Since there is no exact number of pests it is natural to consider the variables as fuzzy variables. Thus we need to consider a fuzzy dynamical system to the poisoning-pest model. To solve such a fuzzy optimal control system, using α-cut, and Zadeh's extension principle, one can convert this system to a non-fuzzy optimal control system. The final optimal control problem is solved by discrelization method. [ABSTRACT FROM AUTHOR]

Published
2014

37. Type-2 fuzzy linear systems

Author

Najariyan, Marzieh, Mazandarani, Mehran, John, Robert, Najariyan, Marzieh, Mazandarani, Mehran, and John, Robert

Abstract

Fuzzy Linear Systems (FLSs) are used in practical situations where some of the systems parameters or variables are uncertain. To date, investigations conducted on FLSs are restricted to those in which the uncertainty is assumed to be modeled by Type-1 Fuzzy Sets (T1FSs). However, there are many situations where considering the uncertainty as T1FSs may not be possible due to different interpretations of experts about the uncertainty. Moreover, solutions of FLSs are T1FSs which do not provide any information about a measure of the dispersion of uncertainty around the T1FSs. Therefore, in this research a model of uncertain linear equations system called a type-2 fuzzy linear system is presented to overcome the shortcomings. The uncertainty is represented by a special class of type-2 fuzzy sets – triangular perfect quasi type-2 fuzzy numbers. Additionally, conditions for the existence of a unique type–2 fuzzy solution to the linear system are derived. A definition of a type-2 fuzzy solution is also given. The applicability of the proposed model is illustrated using examples in the pulp and paper industry, and electrical engineering.

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38. Type-2 fuzzy linear systems

Author

Najariyan, Marzieh, Mazandarani, Mehran, John, Robert, Najariyan, Marzieh, Mazandarani, Mehran, and John, Robert

Abstract

Fuzzy Linear Systems (FLSs) are used in practical situations where some of the systems parameters or variables are uncertain. To date, investigations conducted on FLSs are restricted to those in which the uncertainty is assumed to be modeled by Type-1 Fuzzy Sets (T1FSs). However, there are many situations where considering the uncertainty as T1FSs may not be possible due to different interpretations of experts about the uncertainty. Moreover, solutions of FLSs are T1FSs which do not provide any information about a measure of the dispersion of uncertainty around the T1FSs. Therefore, in this research a model of uncertain linear equations system called a type-2 fuzzy linear system is presented to overcome the shortcomings. The uncertainty is represented by a special class of type-2 fuzzy sets – triangular perfect quasi type-2 fuzzy numbers. Additionally, conditions for the existence of a unique type–2 fuzzy solution to the linear system are derived. A definition of a type-2 fuzzy solution is also given. The applicability of the proposed model is illustrated using examples in the pulp and paper industry, and electrical engineering.

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39. Type-2 fuzzy linear systems

Author

Najariyan, Marzieh, Mazandarani, Mehran, John, Robert, Najariyan, Marzieh, Mazandarani, Mehran, and John, Robert

Abstract

Fuzzy Linear Systems (FLSs) are used in practical situations where some of the systems parameters or variables are uncertain. To date, investigations conducted on FLSs are restricted to those in which the uncertainty is assumed to be modeled by Type-1 Fuzzy Sets (T1FSs). However, there are many situations where considering the uncertainty as T1FSs may not be possible due to different interpretations of experts about the uncertainty. Moreover, solutions of FLSs are T1FSs which do not provide any information about a measure of the dispersion of uncertainty around the T1FSs. Therefore, in this research a model of uncertain linear equations system called a type-2 fuzzy linear system is presented to overcome the shortcomings. The uncertainty is represented by a special class of type-2 fuzzy sets – triangular perfect quasi type-2 fuzzy numbers. Additionally, conditions for the existence of a unique type–2 fuzzy solution to the linear system are derived. A definition of a type-2 fuzzy solution is also given. The applicability of the proposed model is illustrated using examples in the pulp and paper industry, and electrical engineering.

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40. Type-2 fuzzy linear systems

Author

Najariyan, Marzieh, Mazandarani, Mehran, John, Robert, Najariyan, Marzieh, Mazandarani, Mehran, and John, Robert

Abstract

Fuzzy Linear Systems (FLSs) are used in practical situations where some of the systems parameters or variables are uncertain. To date, investigations conducted on FLSs are restricted to those in which the uncertainty is assumed to be modeled by Type-1 Fuzzy Sets (T1FSs). However, there are many situations where considering the uncertainty as T1FSs may not be possible due to different interpretations of experts about the uncertainty. Moreover, solutions of FLSs are T1FSs which do not provide any information about a measure of the dispersion of uncertainty around the T1FSs. Therefore, in this research a model of uncertain linear equations system called a type-2 fuzzy linear system is presented to overcome the shortcomings. The uncertainty is represented by a special class of type-2 fuzzy sets – triangular perfect quasi type-2 fuzzy numbers. Additionally, conditions for the existence of a unique type–2 fuzzy solution to the linear system are derived. A definition of a type-2 fuzzy solution is also given. The applicability of the proposed model is illustrated using examples in the pulp and paper industry, and electrical engineering.

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