فهرست مطالب

Modeling and Simulation - Volume:49 Issue: 2, Autumn 2017

Journal of Modeling and Simulation
Volume:49 Issue: 2, Autumn 2017

  • تاریخ انتشار: 1396/09/30
  • تعداد عناوین: 12
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  • M. Ghayekhloo, M. B. Menhaj, R. Azimi, E. Shekari Pages 133-142
    Identifying clusters is an important aspect of data analysis. This paper proposes a novel data clustering algorithm to increase the clustering accuracy. A novel game theoretic self-organizing map (NGTSOM ) and neural gas (NG) are used in combination with Competitive Hebbian Learning (CHL) to improve the quality of the map and provide a better vector quantization (VQ) for clustering data. Different strategies of Game Theory are proposed to provide a competitive game for nonwinning neurons to participate in the learning phase and obtain more input patterns. The performance of the proposed clustering analysis is evaluated and compared with that of the K-means, SOM and NG methods using different types of data. The clustering results of the proposed method and existing state-of-the-art clustering methods are also compared which demonstrates a better accuracy of the proposed clustering method.
    Keywords: Clustering, game theory, self-organizing map, vector quantization
  • N. Sepehry, F. Bakhtiari-Nejad*, M. Shamshirsaz Pages 143-152
    In recent years, impedance measurement method by piezoelectric (PZT) wafer active sensor (PWAS) has been widely adopted for non-destructive evaluation (NDE). In this method, the electrical impedance of a bonded PWAS is used to detect a structural defect. The electro-mechanical coupling of PZT materials constructs the original principle of this method. Accordingly, the electrical impedance of PWAS can sense any change in the mechanical impedance of the structure. A thermal stress on a structure, which was generated by environmental temperature, could change the electrical impedance of PWAS. The thermal stress which affects the output impedance of PWAS is also developed. A temperature-dependent model, the temperature dependency of PWAS, and structure material properties are investigated for a PWAS bonded to an Euler Bernoulli clamped-clamped beam. The Rayleigh-Ritz and spectral element methods are studied and, then, verified by 3D finite element method (FEM).
    Keywords: Thermal Stress, Euler Bernoulli Beam, Spectral Element Method, Impedance-based Structural Health, Monitoring, 3D FEM
  • A. Mohammad-Shahri *, M. Khodabandeh Pages 153-162
    In this paper, Generalized Aggregated Uncertainty measure 2 (GAU2), as a new uncertainty measure, is considered to evaluate uncertainty in a localization problem in which cameras’ images are used. The theory that is applied to a hierarchical structure for a decision making to combine cameras’ images is Dezert-Smarandache theory. To evaluate decisions, an analysis of uncertainty is executed at every level of the decision-making system. The second generalization of Aggregated Uncertainty measure (GAU2) which is applicable for DSmT results is used as a supervisor. The GAU2 measure in spite of the GAU1 measure can be applied to the problems with vague borders or continuous events. This measure may help to make decisions based on better preference combinations of sensors or methods of fusion. GAU2 is used to evaluate uncertainty after applying classic DSmT and hybrid DSmT with extra knowledge. Therefore by using the decision making system, results with less uncertainty are generated in spite of high conflict sensory data.
    Keywords: Data Fusion, Camera Image, Uncertainty Measurement, Dezert-Smarandache Theory
  • S. Nazem-Zadeh *, M.T. Hamidi-Beheshti Pages 163-172
    A singularly perturbed model is proposed for a system comprised of a PEM Fuel Cell (PEM-FC) with Natural Gas Hydrogen Reformer (NG-HR). This eighteenth order system is decomposed into slow and fast lower order subsystems using singular perturbation techniques that provides tools for separation and order reduction. Then, three different types of controllers, namely an optimal full-order, a near-optimal composite controller based on the slow and the fast subsystems, and a near-optimal reduced-order controller based on the reduced-order model, are designed. The comparison of closedloop responses of these three controllers shows that there are minimal degradations in the performance of the composite and the reduced order controllers.
    Keywords: singular perturbation technique, two-time scale systems, Schur decomposition method, near-optimal controller, slow-fast subsystems
  • M. H. Fazel Zarandi *, F. Kashani Azad, A. H. Karimi Kashani Pages 173-180
    This paper deals with a multi-agent-based interval type-2 fuzzy (IT2F) expert system for scheduling steel continuous casting. Continuous caster scheduling is a complex and extensive process that needs expert staff. In this study, a distributed multi-agent-based structure is proposed as a solution. The agents used herein can cooperate with each other via various communication protocols. To facilitate such communication, an appropriate negotiation protocol (i.e., contract net protocol) is proposed. The due dates specified by expert staff are represented by IT2F membership functions (MFs). As a part of the objective functions, a simple procedure is proposed to calculate the total earliness and tardiness penalty when the due date’s MFs are IT2F. The proposed hybrid multi-agentbased system combines the multi-agent systems with type-2 fuzzy concepts which conforms to the real-world continuous casting problem.
    Keywords: Steel production, Continuous caster scheduling, Agent-based system, Negotiation, Fuzzy system
  • A. Kazemi *, L. Ahmadpour Pages 181-186
    For many electronic supply chain networks in the world that can comprise hundreds of companies with several tiers of suppliers and intermediate customers, there are numerous presenting risks to consider. In the electronic supply chain, the situation are even worse, for the characteristics of this supply chain: excessive lean management, global sourcing and the rather more uncertain market demand. Electronic companies are forced to manage their supply chains effectively to increase efficiency and reactivity. This paper proposes a mathematical model for estimating the severity of interactions between supply chain’s units and how their affect on the entire supply chain. Based on the model, scholars can model supply chains easily with considering interconnected units. Basic characteristics of supply chains are considered in the model. The units, which are used to simulate the members of supply chains, produce appropriate products by intelligent choices. The relationships on units are connected by their activities ; then, the proposed model is applied to an experimental example. The model yields its numerical parameters and responses by means of Lingo software.
    Keywords: Supply chain, Interconnected units, Propagated effect
  • V. Saeidi *, A. Afzalian, D. Gharavian Pages 187-198
    Distributed supervisory control is a method to synthesize local controllers in discrete-event systems with a systematic observation of the plant. Some works were reported on extending this method by which local controllers are constructed so that observation properties are preserved from monolithic to distributed supervisory control, in an up-down approach. In this paper, we find circumstances in which observation properties are preserved from monolithic to distributed supervisory control. Local observation properties, i.e. local normality and local relative observability are employed for investigating observation properties of each local controller, which are constructed by any localization algorithm that preserves control equivalency to the monolithic supervisor with respect to the plant. These properties enable us to investigate the observation properties from monolithic to distributed supervisory control. Moreover, observation equivalence property is defined according to the control equivalence in a distributed supervisory control with partial observation. It is proved that with preserving observation equivalence of the local controllers to the monolithic supervisor, the control equivalence is satisfied, if and only if the intersection of local event sets is a subset of or equal to the global observable event set.
    Keywords: Distributed Supervisory Control, Local Normality, Local Relative Observability, Observation Equivalent
  • M. Pourrahim, K. Shojaei *, A. Chatraei, O. Shahnazari Pages 199-208
    In this study, an observer-based tracking controller is proposed and evaluated experimentally to solve the trajectory tracking problem of robotic manipulators with the torque saturation in the presence of model uncertainties and external disturbances. In comparison with the state-of-the-art observer-based controllers in the literature, this paper introduces a saturated observer-based controller based on a radial basis function neural network. This technique helps the controller produce feasible control signals for the robot actuators. As a result, it efficiently diminishes the actuators saturation risk and consequently, a better transient performance is obtained. The stability analyses of the dynamics of the tracking errors and state estimation errors are given with the help of a Lyapunov-based stability analysis method. The theoretical analyses will systematically prove that the errors are semi-globally uniformly ultimately bounded and they converge to a small set around the origin whose size is adjustable by a suitable tuning of parameters. At last, some real experiments are performed on a laboratory robotic arm to illustrate the efficiency of the proposed control system for real industrial applications.
    Keywords: Actuator saturation, Adaptive robust control, Observer-based control, RBF neural networks, Robot manipulators
  • M. Sharifi, H. A. Talebi * Pages 209-216
    In this paper, the problem of control and stabilization of a bilateral tele-surgery robotic system in interaction with an active soft tissue is considered. To the best of the authors’ knowledge, the previous works did not consider a realistic model for a moving soft tissue like heart tissue in beating heart surgery. Here, a new model is proposed to indicate significant characteristics of a moving soft tissue, rolling as the teleoperation system environment. The model is formed by a parallel combination of a viscoelastic passive part and an active part. Furthermore, the delays in communication and parameter uncertainties of the master and slave robot dynamics are considered. Using an adaptive control strategy, the ultimate boundedness of the system trajectories while interacting with the active environment is certified, and this ultimate bound is calculated. Moreover, to evaluate the theoretical results, simulation results are presented.
    Keywords: active soft tissue, viscoelastic model, bilateral tele robotic surgery, communication time delay, adaptive control
  • M. Shahidi *, J. Keighobadi, A. R. Khoogar Pages 217-226
    In this paper, a dynamical model-based SMC (Sliding Mode Control) is proposed for trajectory tracking of a 3-RPS (Revolute, Prismatic, Spherical) parallel manipulator. With ignoring small inertial effects of all legs and joints compared with those of the end-effector of 3-RPS, the dynamical model of the manipulator is developed based on Lagrange method. By removing the unknown Lagrange multipliers, the distribution matrix of control input vector disappears from the dynamical equations. Therefore, the calculation of the aforementioned matrix is not required for modeling the manipulator. It in trun results in decreased mathematical manipulation and low computational burden. As a robust nonlinear control technique, a SMC system is designed for the tracking of the 3-RPS manipulator. According to Lyapunov’s direct method, the asymptotic stability and the convergence of 3-RPS manipulator to the desired reference trajectories are proved. Based on computer simulations, the robust performance of the proposed SMC system is evaluated with respect to FL (feedback linearization) method. The proposed model and control algorithms can be extended to different kinds of holonomic and non-holonomic constrained parallel manipulators.
    Keywords: Parallel manipulator, Dynamic modeling, Trajectory tracking, Feedback linearization, sliding mode control
  • S. S. Nourazar, H. Parsa *, A. Sanjari Pages 227-238
    In this paper, a comparison among the hybrid of Fourier Transform and Adomian Decomposition Method (FTADM) and Homotopy Perturbation Method (HPM) is investigated. The linear and non-linear Newell-Whitehead-Segel (NWS) equations are solved and the results are compared with the exact solution. The comparison reveals that for the same number of components of recursive sequences, the error of FTADM is much smaller than that of HPM. For the non-linear NWS equation, the accuracy of FTADM is more pronounced than HPM. Moreover, it is shown that as time increases, the results of FTADM, for the linear NWS equation, converges to zero. And for the non-linear NWS equation, the results of FTADM converges to 1 with only six recursive components. This is in agreement with the basic physical concept of NWS diffusion equation which is in turn in agreement with the exact solution.
    Keywords: Fourier Transform, Adomian, Decomposition Method, Homotopy Perturbation Method, Newell–Whitehead-Segel Equation, Nonlinear Partial Differential, Equation
  • N. Mansouri *, M. M. Javidi Pages 239-264
    Large-scale data management is a critical problem in a distributed system such as cloud, P2P system, World Wide Web (WWW), and Data Grid. One of the effective solutions is data replication technique, which efficiently reduces the cost of communication and improves the data reliability and response time. Various replication methods can be proposed depending on when, where, and how replicas are generated and removed. In this paper, different replication algorithms are investigated to determine which attributes are assumed in a given algorithm and which are declined. We provide a tabular representation of important factors to facilitate the future comparison of data replication algorithms. This paper also presents some interesting discussions about future works in data replication by proposing some open research challenges.
    Keywords: Data Grid, Dynamic Replication, Data Availability, Simulation