دانشگاه صنعتی امیرکبیر AUT Journal of Modeling and Simulation 2588-2953 دانشگاه صنعتی امیرکبیر 828 10.22060/miscj.2016.828 Research Article Partial Eigenvalue Assignment in Discrete-time Descriptor Systems via Derivative State Feedback Partial Eigenvalue Assignment in Discrete-time Descriptor Systems via Derivative State Feedback Mirassadi Sakineh Ph.D. Student, Department of Mathematics, Shahrood University of Technology Ahsani Tehrani Hojat Associate Professor, Department of Mathematics, Shahrood University of Technology 21 11 2016 48 2 65 74 16 05 2016 12 11 2016 Copyright © 2016, دانشگاه صنعتی امیرکبیر. 2016 https://miscj.aut.ac.ir/article_828.html

A method for solving the descriptor discrete-time linear system is focused. For easily, it is converted to a standard discrete-time linear system by the definition of a derivative state feedback. Then partial eigenvalue assignment is used for obtaining state feedback and solving the standard system. In partial eigenvalue assignment, just a part of the open loop spectrum of the standard linear systems are reassigned, while leaving the rest of the spectrum invariant and for reassigning, similarity transformation is used. Using partial eigenvalue assignment is easier than using eigenvalue assignment. Because by partial eigenvalue assignment, size of matrices and state and input vectors are decreased and stability is kept, too. Also concluding remarks and an algorithm are proposed to the descriptions will be obvious. At the end, convergence of state and input vectors in the descriptor system to balance point (zero) are showed by figures in a numerical example.

Descriptor Discrete-Time System Derivative State Feedback Partial Eigenvalue Assignment Converge to Balance Point
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دانشگاه صنعتی امیرکبیر AUT Journal of Modeling and Simulation 2588-2953 دانشگاه صنعتی امیرکبیر 829 10.22060/miscj.2016.829 Research Article Potentials of Evolving Linear Models in Tracking Control Design for Nonlinear Variable Structure Systems Potentials of Evolving Linear Models in Tracking Control Design for Nonlinear Variable Structure Systems Kalhor Ahmad Assistant Professor, School of Electrical and Computer Engineering, University of Tehran Hojjatzadeh Nima M.Sc. Student, Faculty of New Sciences and Technologies, University of Tehran Golgouneh Alireza M.Sc. Student, Faculty of New Sciences and Technologies, University of Tehran 21 11 2016 48 2 75 92 15 05 2016 12 11 2016 Copyright © 2016, دانشگاه صنعتی امیرکبیر. 2016 https://miscj.aut.ac.ir/article_829.html

Evolving models have found applications in many real world systems. In this paper, potentials of the Evolving Linear Models (ELMs) in tracking control design for nonlinear variable structure systems are introduced. At first, an ELM is introduced as a dynamic single input, single output (SISO) linear model whose parameters as well as dynamic orders of input and output signals can change through the time. Then, the potential of ELMs in modeling nonlinear time-varying SISO systems is explained. Next, the potential of the ELMs in tracking control of a minimum phase nonlinear time-varying SISO system is introduced. For this mean, two tracking control strategies are proposed respectively for (a) when the ELM is known perfectly and (b) when the ELM model has uncertainties but dynamic orders of the input and output signals are fixed. The methodology and superiority of the proposed tracking control systems are shown via some illustrative examples: speed control in a DC motor and link position control in a flexible joint robot.

Evolving linear model nonlinear time-varying systems tracking control system
دانشگاه صنعتی امیرکبیر AUT Journal of Modeling and Simulation 2588-2953 دانشگاه صنعتی امیرکبیر 831 10.22060/miscj.2016.831 Research Article Analysis of critical paths in a project network with random fuzzy activity times Analysis of critical paths in a project network with random fuzzy activity times Kazemi Abolfazl Assistant Professor, Faculty of Industrial and Mechanical Engineering, Islamic Azad University (Qazvin Branch) Talebi Ahmad M.Sc., Faculty of Industrial and Mechanical Engineering, Islamic Azad University (Qazvin Branch) Oroojeni Mohammad Javad Mahsa Ph.D., Department of Mechanical and Industrial Engineering, Northeastern University, Boston, USA 21 11 2016 48 2 93 102 19 03 2016 12 11 2016 Copyright © 2016, دانشگاه صنعتی امیرکبیر. 2016 https://miscj.aut.ac.ir/article_831.html

Project planning is part of project management, which is relates to the use of schedules such as Gantt charts to plan and subsequently report progress within the project environment. Initially, the project scope is defined and the appropriate methods for completing the project are determined. In this paper a new approach for the critical path analyzing a project network with random fuzzy activity times has been proposed. The activity times of a project are assumed to be random fuzzy. Linear programming formulation has been applied to determine the critical path. The critical path method (CPM) problem has been solved using the expected duration optimization model and the mean-variance model, along with Liu’s definition for random fuzzy variables. Furthermore, a numerical example problem is solved for illustrating the proposed method.

Critical Path Method (CPM) Activity Times Random Fuzzy Time Triangular Fuzzy Numbers Normal Distribution
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دانشگاه صنعتی امیرکبیر AUT Journal of Modeling and Simulation 2588-2953 دانشگاه صنعتی امیرکبیر 833 10.22060/miscj.2016.833 Research Article A risk adjusted self-starting Bernoulli CUSUM control chart with dynamic probability control limits A risk adjusted self-starting Bernoulli CUSUM control chart with dynamic probability control limits Aminnayeri Majid Associate Professor, Department of Industrial Engineering, Amirkabir University of Technology Sogandi Fatemeh Ph.D. Student, Department of Industrial Engineering, Amirkabir University of Technology 21 11 2016 48 2 103 110 07 03 2016 12 11 2016 Copyright © 2016, دانشگاه صنعتی امیرکبیر. 2016 https://miscj.aut.ac.ir/article_833.html

Usually, in monitoring schemes the nominal value of the process parameter is assumed known. However, this assumption is violated owing to costly sampling and lack of data particularly in healthcare systems. On the other hand, applying a fixed control limit for the risk-adjusted Bernoulli chart causes to a variable in-control average run length performance for patient populations with dissimilar risk score distributions in monitoring clinical and surgical performance. To solve these problems, a self-starting scheme is proposed based on a parametric bootstrap method and dynamic probability control limits for the risk-adjusted Bernoulli cumulative sum control charts. The advantage of the proposed control charts lies in the use of probability control limits when any assumptions about the patients’ risk distributions and process parameter. Simulation studies show that both proposed schemes have good performance under various shifts.

Average Run Length Self-Starting Monitoring Bernoulli Process Probability Control Limits Surgical Performance