Journal of Modeling and Simulation
Volume:49 Issue: 1, Spring 2017

This paper concerns the problem of output consensus in nonlinear non-minimum phase systems. The main contribution of the paper is to guarantee achieving consensus in the presence of unstable zero dynamics. To achieve this goal, an output redefinition method is proposed. The new outputs of agents are functions of original outputs and internal states and defined such that the dynamics of agents are minimum phase. However, since the main objective is to achieve consensus on original outputs of agents, the consensus invariant set in the new coordinate of the agents dynamics should be defined such that if the new states of the agents converge to this invariant set, the output consensus in original system is achieved. On the other words, achieving consensus in minimum phase system with redefined output is equivalent to output consensus in original system. After defining the proper invariant set, a consensus protocol is designed to guarantee that the redefined outputs and the internal states to this set. Theoretical results are mathematically proved based on Lyapunov criterion. Numerical examples are employed to show the effectiveness of the proposed approach.

The credit derivatives market has experienced remarkable growth over the past decade. As such, there is a growing interest in tools for pricing of the most prominent credit derivative, the credit default swap (CDS). In this paper, we propose a heuristic algorithm for pricing of basket default swaps (BDS). For this purpose, genetic network programming (GNP), which is one of the recent evolutionary methods with graph structure as a subgroup of machine learning methods, is applied to assess basket default swap spreads. Here GNP is an alternative way for modeling the default correlation structure among different reference entities in a basket default swap. In order to improve the efficiency of the proposed algorithm, GNP with vigorous connection (GNP-VC) is developed and used for the first time in this paper. To implement our model, we consider a basket consisting of 25 entities of the CDX.NA.IG.5Y index. We compare the heuristic results with the Monte Carlo ones and discuss the efficiency of the proposed algorithm. The impact of vigorous connection on the performance of GNP is also reported.

Turbo-expanders are used in industries for cooling, liquefaction and also power generation. An important part of these turbines is the variable angle nozzle causing a nonlinear behavior that is not well recognized among the prime movers of the dispersed generators. In this paper, at first, the turbo expander system is evaluated in details and its nonlinear behavior is investigated. Then, the system is linearized and variations of its eigenvalues are investigated by a system modal analysis for some changes in input gas stream parameters. Afterwards, variations of nozzle angle and output pressure are studied using a conventional PID controller. Due to system nonlinearity, adaptive PID and fuzzy controllers are then designed to improve the system behavior by controlling mechanical parts of turbine nozzle actuator. An adaptive controller uses fuzzy system as a nonlinear tuner that specifies the coefficients for conventional PID controller of the system. A comparison of controllers’ effects is presented. Simulation results show that the turbine response to step changes in gas flow rate or pressure would be more steady when the adaptive or fuzzy controllers are used.

This paper proposes a Time Delay nonlinear dynamic model of HIV-1 (Human Immunodeficiency Virus type 1), introducing the drug consumption efficiencies as the controlling input for the model. The paper also represents the fuzzy T-S representation and the corresponding Fuzzy T-S controller. The controller parameters are tuned using LMIs (Linear Matrix Inequalities). The main focus is on the stabilization problem for the resulting T-S fuzzy system with time-delay. In particular, it aims to present delay-dependent design of state feedback stabilizing fuzzy controller for the mentioned T-S fuzzy system with state delay. The design of the controller is based on the parallel distributed compensation.

In practice, manufacturing systems are never perfect and may have low quality outputs. Therefore, different decisions such as reprocessing, sale at lower prices or diminishing are made according to industry and market. This paper investigates the importance of supply chain coordination through developing two models in centralized decision-making for an imperfect quality manufacturing system with probabilistic defect rate. Moreover, two types of errors in inspection process are considered: Type I error (classifying perfect products as defective ones) and Type II error (classifying defective products as perfect ones). Moreover, a cost function for investment on products quality as well as selling price is considered. The algorithms to find the optimal solution for both models are suggested. Numerical results show that even by less consumer prices; more profit, more satisfied customer, and improved quality can be achieved through coordination in supply chain.

Supply chain management (SCM) is a subject that has found so much attention among different commercial and industrial organizations due to competing environment of products. Therefore, integration of constituent element of this chain is a great deal. This paper proposes a multi objective production-allocation and distribution planning problem (PADPP) in a multi echelon supply chain network. We consider multi suppliers, manufacturers, distribution centers, customers, raw materials and products in the multi-time periods. Three objective functions are minimizing of the total costs of supply chain between all echelons, the delivery time of products to customers with decrease flow time in chain, and the lost sales of products in distribution centers. Since the under investigation model is proved as a strongly NP-hard problem, we solve it with two meta-heuristics algorithms, namely genetic algorithm (GA) and particle swarm optimization (PSO). Also, to justify the performance and efficiency of both algorithms, a variable neighborhood search (VNS) is addressed. Design of experiments and response surface methodologies (RSM) have been utilized to calibrate the parameters of both algorithms. Finally, computational results of the algorithms are assessed on some classified generated problems. Statistical tests indicate that proposed GA and PSO algorithms has better performance in solving proposed model in compared to VNS.

Voltage sag/swell is one of the most frequently power quality problems which affects the power systems with sensitive loads. The unified power quality conditioner (UPQC) is capable of mitigating the effect of voltage sag/swell at the load or point of common coupling (PCC). In this paper, a new control of UPQC is proposed based on combining the sag detection and voltage injection established on d-q frame. The voltage sag is detected based on vector control which can immediately discover all of voltage sag in different directions. This method is used the phase-locked loop and positive-negative sequence to detect the sags and the injected voltage in produced by series converter. The proposed UPQC is investigate in two case studies including the different sags/swells in main bus and forward and backward sags in main and load buses. Also proposed control can improve the other power quality phenomena such as voltage and current harmonics and power factor in the main bus. The simulation results show the accuracy the proposed method.

In this paper, target differentiation based on pattern of data which are obtained by a set of two ultrasonic sensors is considered. A neural network based target classifier is applied to these data to categorize the data of each sensor. Then the results are fused together by Dempster–Shafer theory (DST) and Dezert–Smarandache theory (DSmT) to make final decision. The Generalized Aggregated Uncertainty measure named GAU1, as an extension to the Aggregated Uncertainty (AU) is used to evaluate DSmT. Then the GAU1 and AU as the uncertainty measures are applied to the obtained results of the decision makers to evaluate DSmT and DST accordingly. The introduced configuration for decision making has enough flexibility and robustness to use as a distributed sensor network.

This paper studies the problem of fault detection and isolation (FDI) for multi-agent systems (MAS) via complex Laplacian subject to actuator faults. A planar formation of point agents in the plane using simple and linear interaction rules related to complex Laplacian is achieved. The communication network is a directed, and yet connected graph with a fixed topology. The loss of symmetry in the digraph Laplacian matrix is also considered. Both the partial actuator effectiveness and the actuator bias faults are taken into account. For this purpose, a virtual agent whose dynamics structure is identical to that of the leader agent is introduced to determine the center of planar formation. The FDI scheme requires no additional fault isolation model which is a necessary part in the traditional active FDI scheme. Finally, numerical example results are presented to show the effectiveness of the proposed scheme.

In impulsive orbital maneuvers, a large disturbance torque is generated by the thrust vector misalignment from the center of mass (C.M). The purpose of this paper is to reject the mentioned disturbance and stabilize the spacecraft attitude, based on the combination of a one degree of freedom (1DoF) gimbaled-thruster, two reaction wheels (RWs) and spin-stabilization. In this paper, the disturbances are assumed to be unknown and reaction control systems (RCS) are not employed. The nonlinear two-body dynamics of the proposed system is formulated and validated by the Simmechanics model. The closed-loop controller includes a full state feedback controller based on the gimbal actuator, a self-tuning controller (STC) based on the two RWs and a least squares based disturbance estimator. The simulation results are given by which the applicability of the proposed method is illustrated.

Wing rock phenomenon is an undesired motion appears in high angles of attack where a rolling in the aircraft in positive and negative roll angles with specified amplitude and frequency is occurred. In this paper two adaptive controllers suggested to control the rolling dynamics under wing rock phenomenon for a delta wing aircraft with presence of disturbance. Disturbance was considered as unmatched disturbance. Classical MRAC and σ-modified MRAC are the targeted controllers. Matlab/Simulink is used to simulate the wing rock phenomenon and to test the designed controllers. The simulated results show that the modified controller gives more robust characteristics than its counterpart; as it could confine different aircraft responses within bounded limits. Moreover, the modified controller shows lower control effort than classical one.

This paper presents a numerical investigation for laminar forced convection flow of a radiating gas in a rectangular duct with a solid element that makes a backward facing step. The fluid is treated as a gray, absorbing, emitting and scattering medium. The governing differential equations consisting the continuity, momentum and energy are solved numerically by the computational fluid dynamics techniques. Since the present problem is a conjugate one and both gas and solid elements are considered in the computational domain, simultaneously, the numerical solution of Laplace equation is obtained in the solid element for temperature calculation in this area. Discretized forms of these equations are obtained using the finite volume method and solved by the SIMPLE algorithm. The radiative transfer equation (RTE) is also solved numerically by the discrete ordinate method (DOM) for computation of the radiative term in the gas energy equation.The streamline and isotherm plots in the gas flow and the distributions of convective, radiative and total Nusselt numbers along the solid-gas interface are presented. Besides, the effects of radiation conduction parameter and also solid to gas conduction ratio as two important parameters on thermo hydrodynamic characteristics of such thermal system are explored. It is revealed that the radiative Nusselt number on the interface surface is much affected by RC parameter but the radiation conduction parameter has not considerable effect on the convective Nusselt number. Comparison between the present numerical results with those obtained by other investigators for the case of non-conjugate problems shows good consistency.