Abstract: Surrogate model has received increasing attention for use in detecting damage of structures based on vibration modal parameters. However, uncertainties existing in the measured vibration data may lead to false or unreliable output result from such model. In this study, an efficient approach based on Monte Carlo simulation is proposed to take into account the effect of uncertainties in developing a surrogate model. The probability of damage existence (PDE) is calculated based on the probability density function of the existence of undamaged and damaged states. The kriging technique allows one to genuinely quantify the surrogate error, therefore it is chosen as metamodeling technique. Enhanced version of ideal gas molecular movement (EIGMM) algorithm is used as main algorithm for model updating. The developed approach is applied to detect simulated damage in numerical models of 72-bar space truss and 120-bar dome truss. The simulation results show the proposed method can perform well in probability-based damage detection of structures with less computational effort compared to direct finite element model.
Abstract: Model updating method has received increasing
attention in damage detection structures based on measured modal
parameters. Therefore, a probability-based damage detection
(PBDD) procedure based on a model updating procedure is
presented in this paper, in which a one-stage model-based damage
identification technique based on the dynamic features of a structure
is investigated. The presented framework uses a finite element
updating method with a Monte Carlo simulation that considers the
uncertainty caused by measurement noise. Enhanced ideal gas
molecular movement (EIGMM) is used as the main algorithm for
model updating. Ideal gas molecular movement (IGMM) is a multiagent
algorithm based on the ideal gas molecular movement. Ideal
gas molecules disperse rapidly in different directions and cover all
the space inside. This is embedded in the high speed of molecules,
collisions between them and with the surrounding barriers. In IGMM
algorithm to accomplish the optimal solutions, the initial population
of gas molecules is randomly generated and the governing equations
related to the velocity of gas molecules and collisions between those
are utilized. In this paper, an enhanced version of IGMM, which
removes unchanged variables after specified iterations, is developed.
The proposed method is implemented on two numerical examples in
the field of structural damage detection. The results show that the
proposed method can perform well and competitive in PBDD of
structures.
Abstract: This paper presents a combination of both robust
nonlinear controller and nonlinear controller for a class of nonlinear
4Y Octorotor UAV using Back-stepping and sliding mode controller.
The robustness against internal and external disturbance and
decoupling control are the merits of the proposed paper. The
proposed controller decouples the Octorotor dynamical system. The
controller is then applied to a 4Y Octortor UAV and its feature will
be shown.
Abstract: Frequency stability of microgrids under islanded
operation attracts particular attention recently. A new cooperative
frequency control strategy based on centralized multi-agent system
(CMAS) is proposed in this study. Based on this strategy, agents sent
data and furthermore each component has its own to center operating
decisions (MGCC).After deciding on the information, they are
returned. Frequency control strategies include primary and secondary
frequency control and disposal of multi-stage load in which this study
will also provide a method and algorithm for load shedding. This
could also be a big problem for the performance of micro-grid in
times of disaster. The simulation results show the promising
performance of the proposed structure of the controller based on
multi agent systems.
Abstract: This paper proposes the designing direct adaptive
neural controller to apply for a class of a nonlinear pendulum
dynamic system. The radial basis function (RBF) neural adaptive
controller is robust in presence of external and internal uncertainties.
Both the effectiveness of the controller and robustness against
disturbances are importance of this paper. The simulation results
show the promising performance of the proposed controller.
Abstract: This paper presents a new method to design nonlinear
feedback linearization controller for PEMFCs (Polymer Electrolyte
Membrane Fuel Cells). A nonlinear controller is designed based on
nonlinear model to prolong the stack life of PEMFCs. Since it is
known that large deviations between hydrogen and oxygen partial
pressures can cause severe membrane damage in the fuel cell,
feedback linearization is applied to the PEMFC system so that the
deviation can be kept as small as possible during disturbances or load
variations. To obtain an accurate feedback linearization controller,
tuning the linear parameters are always important. So in proposed
study NSGA (Non-Dominated Sorting Genetic Algorithm)-II method
was used to tune the designed controller in aim to decrease the
controller tracking error. The simulation result showed that the
proposed method tuned the controller efficiently.
Abstract: Diabetes is a growing health problem in worldwide.
Especially, the patients with Type 1 diabetes need strict glycemic
control because they have deficiency of insulin production. This
paper attempts to control blood glucose based on body mathematical
body model. The Bergman minimal mathematical model is used to
develop the nonlinear controller. A novel back-stepping based sliding
mode control (B-SMC) strategy is proposed as a solution that
guarantees practical tracking of a desired glucose concentration. In
order to show the performance of the proposed design, it is compared
with conventional linear and fuzzy controllers which have been done
in previous researches. The numerical simulation result shows the
advantages of sliding mode back stepping controller design to linear
and fuzzy controllers.
Abstract: In this paper, the optimum weight and cost of a laminated composite plate is seeked, while it undergoes the heaviest load prior to a complete failure. Various failure criteria are defined for such structures in the literature. In this work, the Tsai-Hill theory is used as the failure criterion. The theory of analysis was based on the Classical Lamination Theory (CLT). A newly type of Genetic Algorithm (GA) as an optimization technique with a direct use of real variables was employed. Yet, since the optimization via GAs is a long process, and the major time is consumed through the analysis, Radial Basis Function Neural Networks (RBFNN) was employed in predicting the output from the analysis. Thus, the process of optimization will be carried out through a hybrid neuro-GA environment, and the procedure will be carried out until a predicted optimum solution is achieved.
Abstract: Through 1980s, management accounting researchers
described the increasing irrelevance of traditional control and
performance measurement systems. The Balanced Scorecard (BSC)
is a critical business tool for a lot of organizations. It is a
performance measurement system which translates mission and
strategy into objectives. Strategy map approach is a development
variant of BSC in which some necessary causal relations must be
established. To recognize these relations, experts usually use
experience. It is also possible to utilize regression for the same
purpose. Structural Equation Modeling (SEM), which is one of the
most powerful methods of multivariate data analysis, obtains more
appropriate results than traditional methods such as regression. In the
present paper, we propose SEM for the first time to identify the
relations between objectives in the strategy map, and a test to
measure the importance of relations. In SEM, factor analysis and test
of hypotheses are done in the same analysis. SEM is known to be
better than other techniques at supporting analysis and reporting. Our
approach provides a framework which permits the experts to design
the strategy map by applying a comprehensive and scientific method
together with their experience. Therefore this scheme is a more
reliable method in comparison with the previously established
methods.