Javad Poshtan

Iran University of Science and Technology

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Allahyar Montazeri

Lancaster University

Majid Poshtan

California Polytechnic State University

Yousef Alipouri

University of Alberta

Mohammad Hossein Kahaei

Iran University of Science and Technology

Majid Ghaniee Zarch

Bu-Ali Sina University

Jafar Zarei

Shiraz University of Technology

Vicenç Puig

Universitat Politècnica de Catalunya

Mohammad-Reza Jahed-Motlagh

Iran University of Science and Technology

Nargess Sadeghzadeh-Nokhodberiz

Qom University of Technology

Omid Zandi

Iran University of Science and Technology

Cooperative Institutions

Iran University of Science and Technology

Amirkabir University of Technology

University of Tehran

Islamic Azad University, Tehran

K.N.Toosi University of Technology

Islamic Azad University, Science and Research Branch

Sharif University of Technology

Aalborg University

University of Toronto

Shahid Beheshti University

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Fast-array implementation of adaptive IIR filter in feed-forward active noise and vibration control

World Congress (2008)

Allahyar Montazeri Keivan Zavari Javad Poshtan Alireza Roosta

In this paper an RLS-based adaptive controller for active noise and vibration control systems is presented. This adaptive controller is designed based on feed-forward architecture and uses IIR filter as the control filter. Because the derived algorithm for ANVC systems is based on RLS recursion, its computational complexity is of order O(n^2) which is too high for real-time implementations. Besides, it is also vulnerable to round-off and finite precision errors that may occur in real-time implementation of the algorithm. Since the aim is to test the algorithm in an experimental duct a fast array implementation of the algorithm is proposed. This fast array form is used the extended the fast array algorithms for FIR filter which is studied in literature before. The proposed fast array solution of the algorithm not only reduces the computational complexity to the order of O(n) with the same performance, but also because of its matrix nature it has good numerical stability in real-time applications which is a necessity in active noise and vibration control applications.

Active Noise Control

Feed forward

Active Vibration Control

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A modification to classical evolutionary programming by shifting strategy parameters

Applied Intelligence (2012)

Yousef Alipouri Javad Poshtan Yagub Alipouri

Operator (biology)

Sequence (biology)

10.1007/s10489-012-0364-x

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Citations (10)

Verification of the control system performance using viability theory

2022 8th International Conference on Control, Decision and Information Technologies (CoDIT) (2017)

Majid Ghaniee Zarch Vicenç Puig Javad Poshtan

The 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.

Benchmark (surveying)

Representation

Simplicity

10.1109/codit.2017.8102689

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Citations (2)

Fault detection and isolation using viability theory and interval observers

Majid Ghaniee Zarch Vicenç Puig Javad Poshtan

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.

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Online Optimal Controller Design using Evolutionary Algorithm with Convergence Properties

Majlesi Journal of Electrical Engineering (2014)

Yousef Alipouri Javad Poshtan

Many real-world applications require minimization of a cost function. This function is the criterion that figures out optimally. In the control engineering, this criterion is used in the design of optimal controllers. Cost function optimization has difficulties including calculating gradient function and lack of information about the system and the control loop. In this article, for the first time, gradient memetic evolutionary programming is proposed for minimization of non-convex cost functions that have been defined in control engineering. Moreover, stability and convergence of the proposed algorithm are proved. Besides, it is modified to be used in online optimization. To achieve this, the sign of the gradient function is utilized. For calculating the sign of the gradient, there is no need to know the cost-function’s shape. The gradient functions are estimated by the algorithm. The proposed algorithm is used to design a PI controller for nonlinear benchmark system CSTR (Continuous Stirred Tank Reactor) by online and offline approaches.

Benchmark (surveying)

Minification

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Induction motors fault diagnosis using a stacked sparse auto-encoder deep neural network

Proceedings of the Institution of Mechanical Engineers Part I Journal of Systems and Control Engineering (2022)

Saeid Jorkesh Azadeh Gholaminejad Javad Poshtan

In this article, deep neural network and stacked sparse auto-encoder deep neural network performances in fault diagnosis are compared. Methods are employed experimentally for the detection and isolation of an induction motor’s condition (healthy, bearing outer race fault, stator winding short circuit, and rotor broken bar) in the presence of unbalanced power supply and pump dry running disturbances. Pre-processing and de-noising is performed on three-phase electrical current signals using fast Fourier transform and independence component analysis algorithm, respectively. Experimental results show that sparse auto-encoder deep neural network method has outperformed and diagnosed the aforementioned faults in the presence of disturbances with a highly reliable accuracy rate of 90.65%.

10.1177/09596518221125960

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Citations (2)

Event-Triggered Robust Fault Diagnosis Kalman Filter for Stochastic Systems

IEEE Sensors Journal (2021)

Hamideh Jafari Javad Poshtan

This paper proposes a new method for robust fault diagnosis based on data-sending management in discrete-time linear stochastic systems. First, a methodology for identifying a subspace independent of disturbances is presented, which significantly attenuates the effects of disturbances. The sufficient conditions are proposed as linear matrix inequalities (LMIs) to guarantee the observability and stability of a new subspace. After that, the recursive robust Kalman filter is extended based on data-sending management. Finally, this Kalman filter is used to design residual signals. Event-triggered and self-triggered hybrid methods are used to decrease the transfer amount of measured data, and at the same time to preserve the fault diagnosis method performance. Simulation results illustrate the capabilities and effectiveness of the proposed design methodology for fault diagnosis in linear stochastic systems with unknown inputs while the data-sending rate decreases significantly.

Observability

10.1109/jsen.2021.3056480

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Citations (12)

Optimizing a Multi-Channel ANC System for Broadband Noise Cancellation in a Telephone Kiosk Using Genetic Algorithms

Shock and Vibration (2009)

Allahyar Montazeri Javad Poshtan

The problem of optimizing an active noise control system for the implementation of a multi-channel ANC system with the aim of global reduction of broadband noise in a telephone kiosk is addressed in this paper. This optimization involves finding best locations for loudspeakers and microphones, and optimizing control signals. The problem of finding a proper size for control system, i.e. the number of loudspeakers and microphones involved in the control system is also investigated. The mean of acoustic potential energy in the enclosure in a frequency range of 50 Hz to 300 Hz is selected as a measure for optimization. Several genetic algorithms are proposed and compared to find the global minimum of this performance index. In order to have a better performance in reaching the global minimum, the parameters of these genetic algorithms are tuned, and the best genetic algorithm is selected among them. Numerical simulations of the acoustical potential energy and also sound pressure at the height where the head of a person may be located, confirms the optimality of the locations proposed by the genetic algorithm. Besides, the robustness of the optimized control system with respect to eventual changes in the location of primary and secondary loudspeakers and also microphones is shown with several simulations.

Active Noise Control

Robustness

10.1155/2009/943240

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Citations (14)

Fault tolerance evaluation of nonlinear systems using viability theory

Majid Ghaniee Zarch Javad Poshtan Vicenç Puig

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.

Benchmark (surveying)

Kernel (algebra)

10.1109/systol.2016.7739833

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An Overview of Modeling, Stability, and Control of Flapping Robots

Sorayya Leyci Javad Poshtan

Flapping drones have been the focus of attention for various reasons, such as the ability to fly scilently at low speeds and also high maneuverability. This article describes the history of flapping robots and their importance in engineering and how to obtain the forces required to fly. Then, by examining different aspects and presenting the equations, a suitable model is proposed to achieve the control objectives. Due to the kinematic and dynamic complexity, the obtained model is non-linear and periodic. The stability of the robot, which has been often investigated through the averaging and Floquet theory, is also described. In order to stabilize the robot, useful methods presented taking into account the possible challenges in controlling the altitude and attitude. Considering the weight limitations of the robot, selection of electronic components was also considered as a challenge. ‌‌

Flapping

Floquet theory

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