Showing papers in "Computer Simulation in 2007"

Stability Analysis of Networked Control System

Abstract: Due to the constraint of network bandwidth and the conflict of the data,the transmitted time-delay inevitably exists in the Networked Control System(NCS),which is called the network-induced delay.And it is the main problem that can degrade the performance of the control system and even destabilize the system.This paper discusses a linear networked control system model with uncertain parameters and presents the sufficient condition for the stability.The Razumikhin and Laypunov theorems are employed to investigate the problem and obtain the maximal transmitted time-delay.The simulation proved the validity of the conclusion.

Determination of Embedding Parameters for Phase Space Reconstruction Based on Improved C-C Method

Abstract: A new algorithm to determine delay time and embedding window was proposed based on the improved C-C method modifying the classical C-C method in three aspects Considering precision and rapidity of computation, an optimal parameter was introduced into the computation of correlation integral On the foundation of theory study, phase space reconstruction of three kinds of chaotic time series was carried out, and the result of simulations verifies that the algorithm is more applicable for determining appropriate delay time and embedding window

Research on Subjective Trust Management Model Based on Cloud Model

Abstract: Trust management model is fundamental for information security in open networksA formalism method for subjective trust use cloud model was proposed which was the transforming model between qualitative and quantitativeThe exploration of uncertainty and fuzziness characters which was always considered by two internal properties of trust provided a step in the direction of proper understanding and definition of human trustThe qualitative reasoning mechanisms of trust cloud were given to enable trust-based decisions

Improved Sage-Husa Adaptive Filtering and Its Application

Abstract: In order to avoid the divergence and improve the real-time property of the filter, an adaptive filtering based on the covariance matching technique was proposed, which synthesized the covariance matching technique and simplified Sage-Husa filtering. The adaptive filtering was realized by changing and computing the measurement noise covariance, according to the state of the filtering. This algorithm was used to the INS/DS(Double Star) integrated navigation system and it was compared with the simplified Sage-Husa filtering. The simulation results show that the new algorithm simplifies the computation and improves the real-time property with the same accuracy.

Study on Microscopic Traffic Simulation Model Systematic Parameter Calibration

Abstract: Microscopic simulation models have been widely used in traffic system management,control and optimization;however,most of the simulation parameters are determined according to the foreign situations and not always suit for our china.Firstly,the procedure for microscopic simulation model calibration was put forward.Then a VISSIM simulation example of Big-East-Door area in Hefei was used.The application of a Genetic Simulated Annealing(GSA)algorithm as an optimization method for finding a suitable combination of micro-simulation parameter values was proposed.Finally,field experimental results and simulation analysis were compared,which have proven that the algorithm is proper.

Study on Energy-saving Control for Train Based on Genetic Algorithm

Abstract: In order to reduce the railway operation cost, study on how to reduce the energy consumed for train’s moving was provided. Based on the train energy-saving control model, "ramp divided into three parts" joystick manipulating principle was put forward, transforming the problem of optimal control into an optimization problem, and it was solved with genetic algorithm (GA). In the end, a simulation was made to validate the effectiveness of the given method with Matlab.

Improved Ant Colony Algorithm for Solving Continuous Space Optimization Problems

Abstract: Ant colony algorithm is a novel category of bionic meta-heuristic algorithm,and parallel computation and positive feedback mechanism are adopted in this algorithm.The ant colony algorithm has strong robustness and easy to combine with other methods in optimization.Although the ant colony algorithm for the heuristic solution of discrete space optimization problems enjoys a rapidly growing popularity,but few are reported for the heuristic solution of continuous space optimization problems.Based on the introduction of the mechanism and mathematical model of basic ant colony algorithm,an improved ant colony algorithm for solving continuous space optimization problems was proposed.The solution vector of continuous space optimization problem was decomposed into finite grids.Meanwhile,the cost function related to the transition probability was constructed.In order to enhance the global convergence performance of the improved ant colony algorithm,meeting search strategy was adopted in the improved ant colony algorithm,and the range of possible pheromone trails on each solution component was limited to a maximum-minimum interval.The numerical simulation results demonstrate that the improved ant colony algorithm can find better global solution for continuous space optimization problems than the adaptive ant colony algorithm proposed in the literature[11],and this new algorithm presents a feasible and effective way to solve various continuous space optimization problems.

A Variable Step Size LMS Adaptive Filtering Algorithm

Abstract: In this paper, a new adaptive filtering algorithm with fast and variable step size is proposed. On the one hand, theoretical analysis shows that in different channels, the proposed algorithm accomplishes faster convergence and smaller MSE than the LMS and LMSISA . On the other hand , three algorithms (LMS, LMSISA and NLMSISA) are adopted to identify two structure (FIR and IIR ), and the computer simulations demonstrate the characteristics of proposed algorithms. The algori thm is suitable for the adaptive filtering in engineering.

Research on Multiple UAV Cooperative Area Coverage Searching

Abstract: Focusing on the problem of cooperatively searching a given area to detect objects of interest, using multiple heterogenous unmanned aerial vehicles (UAVs), the whole problem was divided into two sub-problems, which are cooperative mission area assignment and coverage route planning, to find optimal solution to the sub-problems respectively. The cost model of UAV’s mission execution was established and a new approach to UAV’s relative capabilities assessment was proposed using hierarchical fuzzy inference. The whole mission area was divided based on the results of UAV capabilities assessment and initial locations using polygon area decomposition, and the resulting areas were assigned among the UAVs. The optimal searching pattern was analyzed and a best searching route was given to cover the UAV mission area. Simulation results demonstrate the validity of the approach.

Study on Simulation System of Fully Mechanized Mining Face Based on Virtual Reality

Abstract: Virtual reality is an important developing direction of modern simulation technology,and it has been used in the field of mine. Applying virtual reality technology and combining with OpenGL and Visual C++ 6.0,a simulation system of fully mechanized mining face was established. Five function modules were designed in this system,including data inputting,scene modeling,scene roaming,interaction controlling and technics simulation. Taking the hydraulic-powered-support and shearer loader for example,the realization process of behavior modeling and interaction control was analyzed. The system had interaction functions of navigation and equipments operation,moreover,the production process of fully mechanized mining face was simulated. The realization of this system put forward a feasible method to the simulation of entire mine.

Adaptive Control for a Class of Nonlinear Systems

Abstract: This paper proposes an adaptive RBF neural network controller based on hybrid genetic algorithm(HGA-RBFNNC)for controlling a class of unknown MIMO nonlinear systems,thus making the system track the desired outputs.The structure and parameters of RBF neural network are determined online by hybrid genetic algorithm.When the error condition is satisfied,the weights of controller are further adjusted and obtained by the adaptive law based on Lyapunov theory,which not only builts the nueral network online but also guarantees the global stability and convergence of the system.Simulation results show that the controller can track the desired outputs fast and has perfect stability and convergence.

Novel EMD Algorithm and Its Application

Abstract: Empirical mode decomposition (EMD), the core of Hilbert-Huang transformation, is reckoned on the algorithm of the extrama extending and generation of envelope curves. With the piecewise power function and an improved algorithm of extrama extending, a novel EMD algorithm was proposed. An error estimation of the piecewise power function interpolation was proposed to show the advantage of this algorithm. At last, a simulation on a stock model is presented to show that this novel EMD algorithm is more applicable to analyze the nonlinear and non-stationary signal than the previous EMD algorithm.

New Method for Phase Space Reconstruction

Abstract: The relationship between the appearance of chaos and saddle point was discussed by analyzing the nonlinear system dynamic behavior.The characteristic point pair lying on the attractor was discovered and then a new phase space reconstruction method was proposed according to the two properties of the characteristic distance.Simulation results show that the method is effective and it is robust under the noisy and small data.

Method of defogging image of outdoor scenes based on PDE

Abstract: Images of outdoor scenes captured in fog suffer from poor contrast and color. It is important to remove weather effects from the degraded image in order to make vision systems more reliable and more robust. It has the prior knowledge that degradation of color and contrast quality due to bad weather is exponential in the depths of the scene points. Based on the atmospheric scattering physics-based models, the global defogging model and the local defogging model were constructed in terms of energy optimization methodology, and the key partial differential equation was deduced accordingly. The algorithm of defogging was advanced using only a single image in terms of simple additional information provided interactively by the user. The experiment results demonstrate that the algorithms can effectively restore clear day color and contrast from weather degraded image and can be applied in practice.

Dynamic Simulation Study of Gear Meshing Based on Virtual Prototyping Technology

Abstract: Gear drive is an important kind of driving device in mechanical equipment.Three-dimensional models of gears were created by Pro/E,and the data matrices of the teeth outline were constructed by using MATLAB.The driving model and virtual prototype of gear meshing transmission was established based on ADAMS.Aiming at the limitation of gaining the forces acting on the teeth,the real-time dynamic simulations of discrete and continuous teeth mesh were achieved with the theory of Hertz embedded.The effect of decentrations and teeth shape imperfections were examined by virtual prototyping model,which provided references to research on dynamic characteristics of gear driving device.

New Type of Adaptive Fuzzy Controllers Based on Variable Universe in Application of Traffic Signal Control

Abstract: Based on the dual fuzzy controllers which are responsible for traffic signal control, with regard to troubles noted in fuzzy control such as universe width determination and rational distribution of membership functions within the universe of the discourse, in order to improve the scheme that acquires the scaling factors both for input and output variables, a new algorithm, according to the values of input and output variables, to achieve the varying universe widthes by means of fuzzy inference in place of function models was proposed. All simulation results prove that this new algorithm is more able to solve the problems, such as the difficulties of the determination upon function coefficients and model parameters than the fuzzy controllers with variable universe based on function models, and realizes the self-tuning and self-adaptiveness of controllers as well. As a result, it not only reduces the average delay time each vehicle, but also secures the smoother vehicle passthrough than before.

Research of Complex Product Assembly Path Planning in Virtual Assembly

Abstract: Based on the analysis of basic workflow in assembly path planning, the key technologies of assembly path planning in virtual assembly were pointed out. Then an optimized method for assembly path record based on effective sampling points was introduced. The method of how to control virtual object’s 3D movement in the virtual environment based on its geometry constraints was established. In order to solve components’ exact placement problem in virtual environment, a mixed method was proposed and this method was made up of geometry constraint recognition algorithm, human-computer interactive geometry constraint define and direct position constraint algorithm. Relation algorithms have been verified in the self-developed system named Virtual Assembly Process Planning System, and this VAPP system has been applied in assembly process planning of aerospace-related products.

Intelligent Control Algorithm of Cloud models and Simulation Research of Superheated Steam Temperature Control

Abstract: For implementing excellent control to nonlinear systems with long time-delay,a new intelligent control algorithm of cloud models was proposed.This algorithm presents the uncertainty reasoning of control rules based on cloud model.It represents a qualitative concept with expected value Ex,entropy En and hyper entropy He,and integrates the fuzziness and randomness of a linguistic concept in a unified way.This model is a new method for transformation between qualitative and quantitative in the knowledge.The intelligent controller uses the theory of the fuzzy control,designing a variant dimension cloud model intelligent controller containing a one-dimension cloud model controller to eliminate steady-state error,which is used for superheated steam temperature control of a supercritical once-though 600MW boiler.It also shows that the cloud controller is simple and easy,directly perceived through the senses,and has strong robustness,better control performance,and good application.

Research on Some Novel Bionic Optimization Algorithms

Abstract: Bionic optimization algorithms are stochastic search methods that mimic the natural biological behavior of species.They are mainly applied to solve various optimization problems.This paper proposes the formulation of four recent biology-based algorithms:ant colony algorithm,particle swarm optimization algorithm,artificial immune algorithm,and artificial fish-swarm algorithm.A brief description of each algorithm is presented firstly.Then,a de- tailed comparison and analysis of these bionic optimization algorithms are conducted.These bionic optimization algo- rithms are a kind of uncertain algorithm with great probability,and independent from the mathematical characters of different problems.These algorithms also have parallelism and robustness.The different points are embedded in the algorithms.Finally,some remarks on the further research contents and directions are discussed.

Soft Sensing Modeling Based on Extreme Learning Machine for Biochemical Processes

Abstract: An improved extreme learning machine (ELM) method was proposed for soft sensing modeling, and the disadvantage of profuse hidden nodes in ELM network was overcome By adding a kind of sorting neurons into the hidden layer of the single-hidden-layer feed forward neural network (SLFN), a new SLFN structure was proposed A method was proposed to solve the problem of the number difference of the sample sorts, and then the same hidden neural nodes could be used to fit the different kind of samples By this way, the number of hidden nodes was decreased, the model structure was simplified, and the on-line computation speed was increased markedly The proposed method provided a new approach to build soft sensing models, and it was successfully applied to the soft sensing modeling the of thalli concentration for the Nosiheptied fermentation process to realize the on-line prediction of the thalli concentration

New Constant Modulus Blind Equalization Algorithm Based on Variable Segment Error Function

Abstract: In order to overcome the slow convergence rate and large steady state error of Constant Modulus Algorithm(CMA),a new CMA based on a variable segment error function was proposed.This blind equalization algorithm can change the characteristic of error function by adjusting the segment position,so it can obtain a suitable odd symmetric error function used in channel equalization.The efficiency of the method is proved by computer simulations with two-twist underwater acoustic channel and negative acoustic gradient underwater acoustic channel.

Development and Application of Integrated Human Machine Interaction Simulation System

Abstract: Based on virtual reality technology and related ergonomics principles, a virtual simulation environment was created allowing human to interact with virtual operation/simulation system in the computer, using multi-channel fused wide screen projection, human motion tracking and data glove gesture tracking, Vega, Creator, and other virtual reality hardware/software techniques. It can be used for dynamically and objectively measuring the interaction performance and can be further used for control panel design quality evaluation. It can be also used for operation training of various 2D control panels. Primary experimental result demonstrates the feasibility of the developed system.

FNN-based Intelligent Fault Diagnosis System for Vehicle Engine

Abstract: According to the fuzziness and complexity of a variety of vehicle engine malfunctions,a kind of FNN-based intelligent fault diagnosis system was put forward.The system has the characteristic of fast inference speed,strong fault-tolerance ability by combine the advantages of the neural networks,fuzzy logic and expert system.Fuzzy logic concept was injected on the basis that neural network makes fault diagnosis to electronic control gasoline engine and applying fuzzy membership functions to depict the fault extent.By applying GUI function of MATLAB,a new man-machine interaction interface was designed.It has a great improvement in convenient operation,facilitates to use and is simply and intuitively updated.

Object Tracking Based on Kalman-Mean Shift in Occlusions

Abstract: An improved Mean-Shift-based tracking algorithm was proposed to solve the poor tracking ability problem in occlusions. A time-invariant system was used to describe the movement of the target during a short time sequences,and through Kalman filter this system was identified so as to make it have ability estimate the coming states while occlusions taken place. The whole tracking system could divided into two parts: a Kalman parameter identifying system based on the object tracking and a Bhattacharyya coefficient analyzing system based on the Kalman state estimating; in the tracking process those two parts run by turns according to different cases. Experiment results of variant video sequences demonstrate that the proposed method can track the objects stably and accurately during occlusions.

Two-order Oscillating Particle Swarm Optimization

Abstract: The evolutionary equation of particle swarm optimization was analyzed from the point of control.On the basis of it,in order to increase the particle swarm's diversity and improve the performance of PSO,the two-order oscillating evolutionary equation was introduced,which could adjust the global and local search capability and avoid the local optimization.The results on benchmark functions show that this method can increase significantly the global optimization and the evolutionary speed.

Research on Real-time Prediction Algorithm of Ship Attitude Motion

Abstract: Based on the Automation Regressive (AR) model, a real-time modeling and prediction method for the huge ship attitude motion forced by random waves was introduced. A real-time fast order selection algorithm-based on improved corner condition and the RLS algorithm-recursion model parameter identification online was given. The ship longitudinal motion was simulated in the typical voyages condition, and it was compared with AIC rule order selection algorithm. The simulation results show that AR model is suitable to modeling and prediction for the ship in the condition of non-steady motion, and the two kinds of order selection algorithm both would realize estimating AR model order on-line, and prediction time would reach 7-10s. But the order selection algorithm-based on improved corner condition are simpler, programming easer, and that the prediction time is shorten. This method has important meaning in the aspects of theories and engineering application.

A Method for Automatic Detection of Ships in Harbor Area in High-Resolution Remote Sensing Image

Abstract: In high-resolution optical remote sensing images the gray-scale and texture features,of the ships docking in harbor area are similar to that of the coast,so it is difficult to automatically detect them compared with the ships at sea.In view of the stability of the geometric layout of harbor,an automatic ship detection method based on geographic information is presented.This method stores geographic information in the form of template,which integrates both advantages of vector data and grid data,then roughly segments targets using automatic threshold.After that,based on a priori information and relative knowledge,connected targets are divided and broken parts are linked.Simulation experiments show that this method can detect ship targets in harbor area accurately and efficiently.

Dynamic Response Simulation of Lifting Load System of Ship-mounted Cranes

Abstract: The wave-induced motion of the crane ship can produce large pendulation of the cargo being hoisted and cause operations to be suspended.In this work,a nonlinear three-dimensional lifting load system dynamic model was set up based on the general form of Lagrange’s equation.Basic crane maneuvers such as cable reeling and unreeling,are taken into consideration.The dynamic response of the cargo was studied using numerical methods.The result demonstrates that the dynamic response of the cargo depends on the length of cable,reeling and unreeling speed and wave frequency,and the in-plane angle have coupling with the out-of-plane angle.Conclusions drawn from this work can be used for cargo pendulation forecast and reduction.

Dissipativity for Nonlinear Neutral Delay Differential Equations

Abstract: The dissipativity of theoretical solution and numerical solution of nonlinear neutral delay differential equations(NDDEs)was investigated.The sufficient conditions for the dissipativity of theoretical solution of the mentioned problem were given,and the numerical solution was dissipative in some proper conditions for a class of linear multistep methods when they were applied to these problems.The numerical tests were given that illustrates the results.

Investigation to Coordinated Torque Control Strategy of Parallel Hybrid Electric Vehicles

Abstract: The energy management strategy of a parallel hybrid electric vehicle (PHEV) with an automatic mechanical transmission (AMT) could be realized by coordinately controlling the engine, clutch, motor and transmission. A hierarchical control system was developed to manage the energy distribution and the coordinated control of the whole vehicle. The implement layer of energy management strategy was used for determining the control rules of powertrain components in order to improve the driving smoothness and minimize the clutch abrasion. The dynamic simulation model of powertrain system of PHEV was developed to optimize and validate the proposed control strategy in Matlab/Simulink environment. Simulation and experimental results show that the good performance is achieved based on the proposed control strategy. The developed control strategy has been tested and applied in the real vehicle.