Stabilization of fractional bilinear systems with multiple inputs

In this paper,we study in a constructive way the stabilization problem of fractional bilinear systems with multiple inputs.Using the quadratic Lyapunov functions and some additional hypotheses on the unit sphere,we construct stabilizing feedback laws for the considered fractional bilinear system.A numerical example is given to illustrate the efficiency of the obtained result.

SRResNet Performance Enhancement Using Patch Inputs and Partial Convolution-Based Padding

Due to highly underdetermined nature of Single Image Super-Resolution(SISR)problem,deep learning neural networks are required to be more deeper to solve the problem effectively.One of deep neural networks successful in the Super-Resolution(SR)problem is ResNet which can render the capability of deeper networks with the help of skip connections.However,zero padding(ZP)scheme in the network restricts benefits of skip connections in SRResNet and its performance as the ratio of the number of pure input data to that of zero padded data increases.In this paper.we consider the ResNet with Partial Convolution based Padding(PCP)instead of ZP to solve SR problem.Since training of deep neural networks using patch images is advantageous in many aspects such as the number of training image data and network complexities,patch image based SR performance is compared with single full image based one.The experimental results show that patch based SRResNet SR results are better than single full image based ones and the performance of deep SRResNet with PCP is better than the one with ZP.

Adaptive synchronization of Chua＇s system with uncertain inputs

The synchronization of Chua＇s system, whose inputs include an unknown constant parameter, is studied in this paper. A constructive method is applied to designing an adaptive controller, in which only one variable information of the master system is needed. With the action of control signals, the parameter of the slave system will approach the corresponding unknown parameter in the master system. At the same time, the synchronization errors will also converge to zero asymptotically. Numerical simulations show that the proposed theoretical approach is very effective.

Soft Sensor for Inputs and Parameters Using Nonlinear Singular State Observer in Chemical Processes

Chemical processes are usually nonlinear singular systems.In this study,a soft sensor using nonlinear singular state observer is established for unknown inputs and uncertain model parameters in chemical processes,which are augmented as state variables.Based on the observability of the singular system,this paper presents a simplified observability criterion under certain conditions for unknown inputs and uncertain model parameters.When the observability is satisfied,the unknown inputs and the uncertain model parameters are estimated online by the soft sensor using augmented nonlinear singular state observer.The riser reactor of fluid catalytic cracking unit is used as an example for analysis and simulation.With the catalyst circulation rate as the only unknown input without model error,one temperature sensor at the riser reactor outlet will ensure the correct estimation for the catalyst circulation rate.However,when uncertain model parameters also exist,additional temperature sensors must be used to ensure correct estimation for unknown inputs and uncertain model parameters of chemical processes.

Eigenstructure assignment of lower-order dynamical compensatorsfor linear systems with unknown inputs

Presents a systematic design method of reduced order dynamical compensator via the parametric representations of eigenstructure assignment for linear system, which provides maximum degree of freedom, and can be easily used for the design of a linear system with unknown inputs under some conditions. Even when these conditions are not satisfied, the lower order dynamical compensator can also be designed under some relaxed conditions. Some examples illustrate that the method is neat, simple and effective.

ADAPTIVE FORECAST AND CONTROL OF THE MARKET ECONOMIC SYSTEM WITH FUZZY INPUTS

In this paper, the adaptive forecast and control of the market economic system with fuzzy inputs is discussed. A new method which is adapted for the adaptive forecast and control of this kind of system is introduced. Through a living example the better result is explained concretly.

Influence of Agricultural Inputs on Growth and Yield of Jatropha curcas （L.） in Cameroon

A study was carried out in the Northern region of Cameroon to assess the influence of fertilizers （chemical fertilizer NPK （15-20-15 w/w/w） or cow dung） on the growth and yield ofJatropha curcas from four origins namely Cameroon, Senegal, Tanzania and Mozambique. The experimental design was factorial with 4 origins×3 fertilizers×8 month durations. After planting, growth parameters and dendrometric measurements were carried out monthly during eight months. Data were analyzed using a Statgraphics program and Duncan test. The results showed that plant of Tanzania and Mozambique origin had higher germination rate in field 75% and 69.5%, respectively. The survival rate of transplants was 100% for Cameroon origin and 98.48% for Senegal origin. NPK and cow dung significantly （P 〈 0.05） increased the growth parameters height, diameter, number of ramifications, leaves and fruits of Jatropha curcas. In addition Jatropha from Cameroon origin exhibited the highest growing conditions and high fruit yield, then highlighting its potential for the biofuel program of the country. But significant improvement needs to be done, particularly on the level of fertilizer needed.

Residual Levels and New Inputs of Chlorinated POPs in Agricultural Soils from Taihu Lake Region

Selected persistent organochlorine pesticides (OCPs), including 1,1,1-trichloro-2,2-bis(p-chlorophenyl)ethane (DDT) and its principal metabolites 1,1-dichloro-2,2-bis(p-chlorophenyl)ethylene (DDE) and 1,1-dichloro-2,2-bis(p-chlorophenyl)e- thane (DDD), hexachlorocyclohexane (HCH) and its isomers (α-,β-, γ-, and δ-HCH), hexachlorobenzene (HCB), endo- sulfan, dieldrin, and endrin were quantified to determine current levels of organochlorine pesticides, to assess the eco- toxicological potential, and to distin…

Finite-time stabilization of uncertain non-autonomous chaoticgyroscopes with nonlinear inputs

Gyroscopes are one of the most interesting and everlasting nonlinear nonautonomous dynamical systems that exhibit very complex dynamical behavior such as chaos. In this paper, the problem of robust stabilization of the nonlinear non-autonomous gyroscopes in a given finite time is studied. It is assumed that the gyroscope system is perturbed by model uncertainties, external disturbances, and unknown parameters. Besides, the effects of input nonlinearities are taken into account. Appropriate adaptive laws are proposed to tackle the unknown parameters. Based on the adaptive laws and the finite-time control theory, discontinuous finite-time control laws are proposed to ensure the finite-time stability of the system. The finite-time stability and convergence of the closed-loop system are analytically proved. Some numerical simulations are presented to show the efficiency of the proposed finite-time control scheme and to validate the theoretical results.

Finite-time control of chaotic systems with nonlinear inputs

A finite-time controller is designed for a class of nonlinear systems subject to sector nonlinear inputs. A novel and simple approach is suggested based on the finite-time control principle. The designed sliding-mode controller can drive a chaotic system to track a smooth target signal in a finite time. The chaotic Duffing-Holmes oscillator is used for verification and demonstration.

A novel adaptive finite-time controller for synchronizing chaotic gyros with nonlinear inputs

In this paper, the problem of the finite-time synchronization of two uncertain chaotic gyros is discussed. The parameters of both the master and the slave gyros are assumed to be unknown in advance. The effects of model uncertainties and input nonlinearities are also taken into account. An appropriate adaptation law is proposed to tackle the gyros＇ unknown parameters. Based on the adaptation law and the finite-time control technique, proper control laws are introduced to ensure that the trajectories of the slave gyro converge to the trajectories of the master gyro in a given finite time. Simulation results show the applicability and the efficiency of the proposed finite-time controller.

Identification of multiple inputs single output errors-in-variables system using cumulant

A higher-order cumulant-based weighted least square（HOCWLS） and a higher-order cumulant-based iterative least square（HOCILS） are derived for multiple inputs single output（MISO） errors-in-variables（EIV） systems from noisy input/output data. Whether the noises of the input/output of the system are white or colored, the proposed algorithms can be insensitive to these noises and yield unbiased estimates. To realize adaptive parameter estimates, a higher-order cumulant-based recursive least square（HOCRLS） method is also studied. Convergence analysis of the HOCRLS is conducted by using the stochastic process theory and the stochastic martingale theory. It indicates that the parameter estimation error of HOCRLS consistently converges to zero under a generalized persistent excitation condition. The usefulness of the proposed algorithms is assessed through numerical simulations.

Control Design for Harmonic Disturbance Rejection for Robot Manipulators with Bounded Inputs

Currently most of control methods are of one degree of freedom（1-DOF） control structure for the robot systems which are affected by unmeasurable harmonic disturbances,at the same time in order to obtain perfect disturbance attenuation level,the controller gain must be increased.In practice,however,for robotic actuators,there are physical constraints that limit the amplitude of the available torques.This paper considers the problem of tracking control under input constraints for robot manipulators which are affected by unmeasurable harmonic disturbances.A new control scheme is proposed for the problem,which is composed of a parameter-dependent nonlinear observer and a tracking controller.The parameter-dependent nonlinear observer,designed based on the internal model principle,can achieve an estimation and compensation of a class of harmonic disturbances with unknown frequencies.The tracking controller,designed via adaptive control techniques,can make the systems asymptotically track the desired trajectories.In the control design,the continuous piecewise differentiable increasing function is used to limit control input amplitude,such that the control input saturation is avoided.The Lyapunov stability of closed loop systems is analyzed.To validate proposed control scheme,simulation results are provided for a two link horizontal robot manipulator.The simulation results show that the proposed control scheme ensures asymptotic tracking in presence of an uncertain external disturbance acting on the system.An important feature of the methodology consists of the fact that the designed controller is of 2-DOF control structure,namely,it has the ability to overcome the conflict between controller gain and robustness against external disturbances in the traditional 1 -DOF control structure framework.

Nonsingular terminal sliding mode approach applied to synchronize chaotic systems with unknown parameters and nonlinear inputs

This paper deals with the design of a novel nonsingular terminal sliding mode controller for finite-time synchro-nization of two different chaotic systems with fully unknown parameters and nonlinear inputs. We propose a novel nonsingular terminal sliding surface and prove its finite-time convergence to zero. We assume that both the master＇s and the slave＇s system parameters are unknown in advance. Proper adaptation laws are derived to tackle the unknown parameters. An adaptive sliding mode control law is designed to ensure the existence of the sliding mode in finite time. We prove that both reaching and sliding mode phases are stable in finite time. An estimation of convergence time is given. Two illustrative examples show the effectiveness and usefulness of the proposed technique. It is worthwhile noticing that the introduced nonsingular terminal sliding mode can be applied to a wide variety of nonlinear control problems.

Laboratory development of high performance steel plates with excellent HAZ toughness at large heat inputs

Presented in this study is the result of steel plates developed at laboratory by using the technique of chemistry design based on microstructure evolution.It has been shown that the produced 50mm thickness steel plates with yield and tensile strength being 420 MPa and 530 MPa respectively exhibit excellent large heat input weldability:the Charpy impact tests in the whole range of heat affected zone(HAZ) including the fusion line at the welded joint with large heat input of 100 -300 kJ/cm showed uniform impact toughness of above 140 J at -40℃.Welding simulations were also performed for heat inputs of 200-600 kJ/cm,which showed far better toughness at -20℃.Analysis on the results of the simulations and the practical welding tests were done and the microstructure evolution mechanisms were proposed.Finally suggestions were given to improve the simulation processes as well as chemistry modification.

Adaptive projective synchronization of different chaotic systems with nonlinearity inputs

We investigate the projective synchronization of different chaotic systems with nonlinearity inputs. Based on the adaptive technique, sliding mode control method and pole assignment technique, a novel adaptive projective synchro- nization scheme is proposed to ensure the drive system and the response system with nonlinearity inputs can be rapidly synchronized up to the given scaling factor.

High-Gain Approach Based Full-Order Observers for Linear Systems with Unknown Inputs

In this paper, a full-order observer which can be fully decoupled from the unknown inputs as the conventional full-order observer does is designed by using auxiliary outputs, but the requirement of the matching condition is removed. The procedure of calculating the parameter matrices of the full-order observer is also presented. Compared with the existing auxiliary outputs based sliding-mode observers, the designed observer has a simpler design procedure, which is systematic and does not involve solving linear matrix inequalities. The simulation results show that the proposed method is effective.

Farmers' Behaviors on Agricultural Technology Inputs and the Influencing Factors of Their Behaviors——Based on the Investigation of 276 Rural Households in Deyang City, Sichuan Province

On the basis of expounding farmers' behaviors on agricultural technology inputs studied by the foreign scholars; relying on the investigation data of 276 rural households in Deyang City, Sichuan Province and by using the Logistic Regression model, the farmers' behaviors on agricultural technology inputs and the influencing factors on their behaviors are analyzed. The results show the main factors that influence farmers; behaviors on agricultural inputs are whether they have the assistance of agricultural technology personnel; the choices of plantation; non-agricultural income; area of land management; the expectation on land ownership, whether it has township enterprises and the proportion of the non-agricultural labor forces and some other factors. The influencing degree of these factors descends from strong to weak. On the strength of the study results, the countermeasures on increasing local farmers' inputs on agricultural technology are put forward from the aspects of stabilizing rural land property, establishing scientific land transfer mechanism and intensifying the governmental functions of agro-technical station.

Design of space-centered interaction using invisible and intangible spatial inputs

In this paper,we investigate methodologies to improve direct-touch interaction on invisible and intangible spatial input.We firstly discuss about the motive of looking for a new input method for whole body interaction and how it can be meaningful.We also describe the role that can play spatial interaction to improve the freedom of interaction for a user.We propose a method of spatial centered interaction using invisible and intangible spatial inputs.However,given their lack of tactile feedback and visual representation,direct touch interaction on such input can be confused.In order to make a step toward understanding causes and solutions for such phenomena,we made 2 user experiments.In the first one,we test 5 setups of helper that provide information of the location of the input by constraining the dimension it is located at.The results show that using marker on the ground and a relationship with the height of the user’s body improve significantly the locative task.In the second experiment,we create a dancing game using invisible and intangible spatial inputs and we stress the results obtained in the first experiment within this cognitively demanding context.Results show that the same setup of helper is still providing very good results in that context.

MDGA2 Constrains Glutamatergic Inputs Selectively onto CA1 Pyramidal Neurons to Optimize Neural Circuits for Plasticity,Memory,and Social Behavior

Synapse organizers are essential for the development,transmission,and plasticity of synapses.Acting as rare synapse suppressors,the MAM domain containing glycosylphosphatidylinositol anchor(MDGA)proteins contributes to synapse organization by inhibiting the formation of the synaptogenic neuroligin-neurexin complex.A previous analysis of MDGA2 mice lacking a single copy of Mdga2 revealed upregulated glutamatergic synapses and behaviors consistent with autism.However,MDGA2 is expressed in diverse cell types and is localized to both excitatory and inhibitory synapses.Differentiating the network versus cell-specific effects of MDGA2 loss-of-function requires a cell-type and brain region-selective strategy.To address this,we generated mice harboring a conditional knockout of Mdga2 restricted to CA1 pyramidal neurons.Here we report that MDGA2 suppresses the density and function of excitatory synapses selectively on pyramidal neurons in the mature hippocampus.Conditional deletion of Mdga2 in CA1 pyramidal neurons of adult mice upregulated miniature and spontaneous excitatory postsynaptic potentials,vesicular glutamate transporter 1 intensity,and neuronal excitability.These effects were limited to glutamatergic synapses as no changes were detected in miniature and spontaneous inhibitory postsynaptic potential properties or vesicular GABA transporter intensity.Functionally,evoked basal synaptic transmission and AMPAR receptor currents were enhanced at glutamatergic inputs.At a behavioral level,memory appeared to be compromised in Mdga2 cKO mice as both novel object recognition and contextual fear conditioning performance were impaired,consistent with deficits in long-term potentiation in the CA3-CA1 pathway.Social affiliation,a behavioral analog of social deficits in autism,was similarly compromised.These results demonstrate that MDGA2 confines the properties of excitatory synapses to CA1 neurons in mature hippocampal circuits,thereby optimizing this network for plasticity,cognition,and social behaviors.