Dynamic matrix encoding strategy for voice-over-IP steganography

In order to optionally regulate embedding capacity and embedding transparency according to user's requirements in voice-over-IP(VoIP) steganography,a dynamic matrix encoding strategy(DMES) was presented.Differing from the traditional matrix encoding strategy,DMES dynamically chose the size of each message group in a given set of adoptable message sizes.The appearance possibilities of all adoptable sizes were set in accordance with the desired embedding performance(embedding rate or bit-change rate).Accordingly,a searching algorithm that could provide an optimal combination of appearance possibilities was proposed.Furthermore,the roulette wheel algorithm was employed to determine the size of each message group according to the optimal combination of appearance possibilities.The effectiveness of DMES was evaluated in StegVoIP,which is a typical covert communication system based on VoIP.The experimental results demonstrate that DMES can adjust embedding capacity and embedding transparency effectively and flexibly,and achieve the desired embedding performance in any case.For the desired embedding rate,the average errors are not more than 0.000 8,and the standard deviations are not more than 0.002 0;for the desired bit-change rate,the average errors are not more than 0.001 4,and the standard deviations are not more than 0.002 6.

Vector control of permanent magnet synchronous motor based on dynamic matrix control

Aiming at the control problem of strongly nonlinear and coupled permanent magnet synchronous motor(PMSM)oil rig,this paper presents a predictive control method based on dynamic matrix model.In this method,the dynamic matrix algorithm using multistep prediction technique is applied to the speed loop control of the motor vector control.And its control effect is compared with the traditional proportional integral(PI)control of the motor.By comparing the initial dynamic response and the steady-state recovery under load interference of the two methods,it is shown that the dynamic response and the robustness of the motor controlled by the new method is better than that controlled by conventional PI method.And the feasibility of new control in the application of PMSM oil rig is verified.

Theory-Intelligent Dynamic Matrix Model of Flatness Control for Cold Rolled Strips

In order to increase the precision of flatness control, considering the principle and the measured data of rolling process essence, the theory-intelligent dynamic matrix model of flatness control is established by using theory and in-telligent methods synthetically. The network model for rapidly calculating the theory effective matrix is established by the BP network optimized by the particle swarm algorithm. The network model for rapidly calculating the meas- urement effective matrix is established by the RBF network optimized by the cluster algorithm. The flatness control model can track the practical situation of roiling process by on-line selVlearning. The scheme for flatness control quantity calculation is established by combining the theory control matrix and the measurement control matrix. The simulation result indicates that the establishment of theory-intelligent dynamic matrix model of flatness control with stable control process and high precision supplies a new way and method for studying flatness on-line control model.

Implementation of Dynamic Matrix Control on Field Programmable Gate Array

High performance computer is often required by model predictive control(MPC) systems due to the heavy online computation burden.To extend MPC to more application cases with low-cost computation facilities, the implementation of MPC controller on field programmable gate array(FPGA) system is studied.For the dynamic matrix control(DMC) algorithm,the main design idea and the implemental strategy of DMC controller are introduced based on a FPGA’s embedded system.The performance tests show that both the computation efficiency and the accuracy of the proposed controller can be satisfied due to the parallel computing capability of FPGA.

Flatness Control Based on Dynamic Effective Matrix for Cold Strip Mills

Steel strips are the main of steel products and flatness is an important quality indicator of steel strips. Flatness control is the key and highly difficult technique of strip mills. The bottle-neck restricting the improvement of flatness control techniques is that the research on flatness theories and control mathematic models is not in accordance with the requirement of technique developments. To build a simple, rapid and accurate explicit formulation control model has become an urgent need for the development of flatness control technique. This paper puts forward the conception of dynamic effective matrix based on the effective matrix method for flatness control proposed by the authors under the consideration of the influence of the change of parameters in roiling processes on the effective matrix, and the concept is validated by industrial productions. Three methods of the effective matrix generation are induced： the calculation method based on the flatness prediction model; the calculation method based on the data excavation in rolling processes and the direct calculation method based on the network model. A fuzzy neural network effective matrix model is built based on the clusters, and then the network structure is optimized and the high-speed-calculation problem of the dynamic effective matrix is solved. The flatness control scheme for cold strip mills is proposed based on the dynamic effective matrix. On stand 5 of the 1 220 mm five-stand 4-high cold strip tandem mill, the industrial experiment with the control methods of tilting roll and bending roll is done by the control scheme of the static effective matrix and the dynamic effective matrix, respectively. The experiment result proves that the control effect of the dynamic effective matrix is much better than that of the static effective matrix. This paper proposes a new idea and method for the dynamic flatness control in the rolling processes of cold strip mills and develops the theory and model of the flatness control effective matrix method.

Analysis of the hull girder vibration by dynamic stiffness matrix method

Dynamic stiffness matrix method is applied to compute vibration of hull girder in this paper. This method can not only simplify the computational model, but also get much higher frequencies and responses accurately. The analytical expressions of dynamic stiffness matrix of a Timoshenko beam for transverse vibration are presented in this paper. All effects of rotatory inertia and shear deformation are taken into account in the formulation. The resulting dynamic stiffness matrix combined with the Wittrick-Williams algorithm is used to compute natural frequencies and mode shapes of the 299,500 DWT VLCC, and then the vibrational responses are solved by the mode superposition method. The computational results are compared with those obtained from other approximate methods and experiment, and it indicates that the method is accurate and efficient.

THE DYNAMIC STIFFNESS MATRIX OF THE FINITE ANNULAR PLATE ELEMENT

The dynamic deformation of harmonic vibration is used as the shape functions of the finite annular plate element, and sonic integration difficulties related to the Bessel's functions are solved in this paper. Then the dynamic stiffness matrix of the finite annular plate element is established in closed form and checked by the direct stiffness method. The paper has given wide convcrage for decomposing the dynamic matrix into the power series of frequency square. By utilizing the axial symmetry of annular elements, the modes with different numbers of nodal diameters at s separately treated. Thus some terse and complete results are obtained as the foundation of structural characteristic analysis and dynamic response compulation.

From the new Austrian tunneling method to the geoengineering condition evaluation and dynamic controlling method

The new Austrian tunneling method （NATM） is widely applied in design and construction of underground engineering projects. When the type and distribution of unfavorable geological bodies （UGBs） associated with their influences on geoengineering are complicated or unfortunately are overlooked, we should pay more attentions to internal features of rocks grades IV and V （even in local but mostly controlling zones）. With increasing attentions to the characteristics, mechanism and influences of engineering construction-triggered geohazards, it is crucial to fully understand the disturbance of these geohazards on project construction. A reasonable determination method in construction procedure, i.e. the shape of working face, the type of engineering support and the choice of feasible procedure, should be considered in order to mitigate the construction-triggered geohazards. Due to their high sensitivity to groundwater and in-situ stress, various UGBs exhibit hysteretic nature and failure modes. To give a complete understanding on the internal causes, the emphasis on advanced comprehensive geological forecasting and overall reinforcement treatment is therefore of more practical significance. Compre- hensive evaluation of influential factors, identification of UGB, and measures of discontinuity dynamic controlling comprises the geoengineering condition evaluation and dynamic controlling method. In a case of a cut slope, the variations of UGBs and the impacts of key environmental factors are presented, where more severe construction-triggered geohazards emerged in construction stage than those predicted in design and field investigation stages. As a result, the weight ratios of different influential factors with respect to field investigation, design and construction are obtained.

DYNAMIC CHARACTERISTICS ON PRECISION NC LATHE BASED ON MULTI-BODY SYSTEM THEORY

Based on multi-body system theory and the mainshafl system of precision NC lathe as object investigated, it is treated as a coupled rigid-flexible multi-body system which is made up of some rigid and elastic bodies in an especial linking mode. And a dynamic model is established, The problems of computing vibration characteristics are resolved by using multi-body system transfer matrix method, Resutts show that the mainshaft system of NC lathe is in the stable and reliable working area all the time. The method is simple and easy, the idea is clear. In addition, the method can be easily used and popularized in the other multi-body system.

A practical predictive control algorithm for integral processes and a case study in boiler level system

The Dynamic Matrix Control （DMC） algorithm tor integral processes is investigated in this paper. The reason why the original DMC algorithm cannot be applied to these processes is analyzed. The shifting matrix is transformed into another form and the corresponding theorem is proved, then its applicable range is extended. Compared with other algorithms on the integral processes, this algorithm is more practical and simple to implement. Simulation results also prove its validity. Applying this algorithm, we succeed in the control of the boiler level system in power units.

Application of Model Predictive Control Based on Kalman Filter in Solar Collector Field of Solar Thermal Power Generation

There are two prominent features in the process of temperature control in solar collector field.Firstly,the dynamic model of solar collector field is nonlinear and complex,which needs to be simplified.Secondly,there are a lot of random and uncontrollable,measurable and unmeasurable disturbances in solar collector field.This paper uses Taylor formula and difference approximation method to design a dynamic matrix predictive control(DMC)by linearizing and discretizing the dynamic model of the solar collector field.In addition,the purpose of controlling the stability of the outlet solar field salt temperature is achieved by adjusting the mass flow of molten salt.In order to further improve the ability of the system to suppress unmeasured disturbances,a steady-state Kalman filter is designed to estimate state variables,so that the system has better stability and robustness.The simulation verification results show that the DMC control system based on Kamlan filtering has better control effect than the traditional DMC control system.In the case of large fluctuations in solar radiation intensity and consideration of undetectable interference,the overshoot of the system is reduced by 4%and the rise time remains unchanged.

Machining Complex Oriented Compensation System for Generalized Kinematic Errors

This paper puts forward a machining complex oriented compensation strategy for the generalized kinematic errors (GKEs). According to this strategy, the error map, which is constructed by using the off line measuring information of the machined workpiece, is not oriented for the machine tool but for the machining complex to compensate the GKEs. The error map is derived by the proposed predictive learning control algorithm (PLCA), which is supported by the information model of machining complex. Experimental results show that the machining complex oriented GKEs compensation strategy and the information model based PLCA is effective.

AGC-ASC Decoupled Neural Networks Predictive Control Method

The coupling models for the thickness-crown objects is established. A Dynamic Matrix Controller based on the TH neural networks is given with the convergence property. The computer simulations with the AGC-ASC decoupled neural networks predictive control system is complemented and it shows that the stable states of neural networks are reached with on more that one μs, this has not only sahsfied the fast property of rolling process, but also obtained a higher control index.

Adaptive Predictive Inverse Control of Offshore Jacket Platform Based on Rough Neural Network

The offshore jacket platform is a complex and time-varying nonlinear system, which can be excited of harmful vibration by external loads. It is difficult to obtain an ideal control performance for passive control methods or traditional active control methods based on accurate mathematic model. In this paper, an adaptive inverse control method is proposed on the basis of novel rough neural networks （RNN） to control the harmful vibration of the offshore jacket platform, and the offshore jacket platform model is established by dynamic stiffness matrix （DSM） method. Benefited from the nonlinear processing ability of the neural networks and data interpretation ability of the rough set theory, RNN is utilized to identify the predictive inverse model of the offshore jacket platform system. Then the identified model is used as the adaptive predictive inverse controller to control the harmful vibration caused by wave and wind loads, and to deal with the delay problem caused by signal transmission in the control process. The numerical results show that the constructed novel RNN has advantages such as clear structure, fast training speed and strong error-tolerance ability, and the proposed method based on RNN can effectively control the harmful vibration of the offshore jacket platform.

Dynamic Recrystallization Behavior of Bimodal Size SiCpReinforced Mg Matrix Composite during Hot Deformation

The（submicron＋micron） bimodal size Si Cp-reinforced Mg matrix composite was compressed at the temperature of 270–420 °C and strain rate of 0.001–1 s^-1. Then, dynamic recrystallization（DRX） behavior of the composite was investigated by thermodynamic method and verified by microstructure analysis. Results illustrated that the composite possess the lower critical strain and higher DRX ratio as compared to monolithic Mg alloys during hot deformation process. The predicted DRX ratio increased with the proceeding of compression, which was well consistent with the experimental value. Results from thermodynamic calculation suggested that the occurrence of DRX could be promoted by Si Cp, which would be further proved by microstructure analysis. Formation of particle deformation zone around micron Si Cp played a significant role in promoting DRX nucleation. Nevertheless, the distribution of submicron Si Cp was increasingly uniform with the proceeding of compression, which could fully restrain grain growth. Therefore, the corporate effects of micron and submicron Si Cp on DRX contributed to the improvement of DRXed ratio and the refinement of grain size for the composite during compression process.

STUDY ON AUTOMATIC BALANCE TECHNOLOGY FOR THE RIGID ROTOR

The theory and application of automatic balance technology for the rigid rotor is re- searched. New analysis about the mechanical model of vibratory system is done in view of feature of automatic balance, and the result is that the accurate model of system can be gained by compensa- tion method and the traditional principle error of balance machines both for soft and hard bearing can be overcome. The automatic balance testing theory for sofi and hard bearing machines is pro- posed. The automatic balance system has been developed and the function and technical key is also introduced in detail.

Multi-dimensional scenario forecast for generation of multiple wind farms

A novel multi-dimensional scenario forecast approach which can capture the dynamic temporal-spatial interdependence relation among the outputs of multiple wind farms is proposed.In the proposed approach,support vector machine(SVM)is applied for the spot forecast of wind power generation.The probability density function(PDF)of the SVM forecast error is predicted by sparse Bayesian learning(SBL),and the spot forecast result is corrected according to the error expectation obtained.The copula function is estimated using a Gaussian copula-based dynamic conditional correlation matrix regression(DCCMR)model to describe the correlation among the errors.And the multidimensional scenario is generated with respect to the estimated marginal distributions and the copula function.Test results on three adjacent wind farms illustrate the effectiveness of the proposed approach.