“不适”的适应:教学模式与学习方式关系探讨

如果环境与学习者太和谐一致,学习者就会停留在原有的舒适水平上学习,而不再需要成长的挑战。如果学习者与他所处的环境之间动力失衡,学习者身上就会出现一种与教育环境不相适应的状态,谓之＂不适＂。不适的状况经常出现在教学模式的变革、学习方式的变革以及二者关系的协同方面。

COMPENSATION CONTROL OF REAL-TIME UNBALANCE FORCE FOR ACTIVE MAGNETIC BEARING SYSTEM

Aiming at the stability and others properties of active magnetic bearing （AMB） system influenced by the periodic unbalance stimulation synchronous with rotor rotational speed, a new real-time adaptive feed-forward unbalance force compensation scheme is proposed based on variable step-size least mean square（LMS） algorithm as the feed-forward compensation controller. The controller can provide some suitable sinusoidal signals to com- pensate the feedback unbalance response signals synchronous with the rotary frequency, then reduce the fluctua- tion of the control currents and weaken the active control of AMB system. The variable step-size proportional to the rotational frequency is deduced by analyzing the principle of normal LMS algorithm and its deficiency in the application of real-time filtering of AMB system. Experimental results show that the new method can implement real-time unbalance force compensation in a wide frequency band, reduce the effect of unbalance stimulant force on the housing of AMB system, and provide convenience to improve rotational speed.

ADAPTIVE PREDICTIVE CONTROL OF NEAR-SPACE VEHICLE USING FUNCTIONAL LINK NETWORK

A novel nonlinear adaptive control method is presented for a near-space hypersonic vehicle （NHV） in the presence of strong uncertainties and disturbances. The control law consists of the optimal generalized predictive controller （OGPC） and the functional link network （FLN） direct adaptive law. OGPC is a continuous-time nonlinear predictive control law. The FLN adaptive law is used to offset the unknown uncertainties and disturbances in a flight through the online learning. The learning process does not need any offline training phase. The stability analyses of the NHV close-loop system are provided and it is proved that the system error and the weight learning error are uniformly ultimately hounded. Simulation results show the satisfactory performance of the con- troller for the attitude tracking.

Robust adaptive dynamic surface control for nonlinear uncertain systems

We propose a new method for robust adaptive backstepping control of nonlinear systems with parametric uncertainties and disturbances in the strict feedback form. The method is called dynamic surface control. Traditional backstepping algorithms require repeated differentiations of the modelled nonlinearities. The addition of n first order low pass filters allows the algorithm to be implemented without differentiating any model nonlinearities, thus ending the complexity arising due to the 'explosion of terms' that makes other methods difficult to implement in practice. The combined robust adaptive backstepping/first order filter system is proved to be semiglobally asymptotically stable for sufficiently fast filters by a singular perturbation approach. The simulation results demonstrate the feasibility and effectiveness of the controller designed by the method.

日本平安文坛对白居易闲适诗的新型接受与民族文化构建借势

白居易闲适诗是审视唐宋时期中国文学"跨文化"传播、流变及对他族文化构建意义的典型案例。以往对它的接受研究,多局限于白诗的语言浅俗以及文风契合日本民族风月审美等内容。结合白居易文学的内在矛盾性、平安时代汉学思潮的流变脉动、白居易形象的佛教化等因素,为其域外影响与创造性接受提供新的思考维度,可以发现:白居易以道禅二家为主的后期"闲适"文学,成为平安文坛"闲适"思想的主要来源;白居易闲适观中的"不适之适",成为平安文人接受白居易"闲适"文学的重要分流点;仕宦顺达的大江维时通过对《千载佳句》的编撰,呈现出平安文人的汉诗学自觉以及对白居易闲适思想的诗学偏离,却没有真正体认白居易闲适思想的"不适之适";"不适之适"注入"狂言绮语"的文学表达范式中,后来随着白居易佛教形象在日本的接受和强化,而被仕宦"不遇"的平安汉学文人发展成一种新的时代观点。

Study and Application of Fault Prediction Methods with Improved Reservoir Neural Networks

Time-series prediction is one of the major methodologies used for fault prediction. The methods based on recurrent neural networks have been widely used in time-series prediction for their remarkable non-liner mapping ability. As a new recurrent neural network, reservoir neural network can effectively process the time-series prediction. However, the ill-posedness problem of reservoir neural networks has seriously restricted the generalization performance. In this paper, a fault prediction algorithm based on time-series is proposed using improved reservoir neural networks. The basic idea is taking structure risk into consideration, that is, the cost function involves not only the experience risk factor but also the structure risk factor. Thus a regulation coefficient is introduced to calculate the output weight of the reservoir neural network. As a result, the amplitude of output weight is effectively controlled and the ill-posedness problem is solved. Because the training speed of ordinary reservoir networks is naturally fast, the improved reservoir networks for time-series prediction are good in speed and generalization ability. Experiments on Mackey–Glass and sunspot time series prediction prove the effectiveness of the algorithm. The proposed algorithm is applied to TE process fault prediction. We first forecast some timeseries obtained from TE and then predict the fault type adopting the static reservoirs with the predicted data.The final prediction correct rate reaches 81%.

Solving Severely Ill⁃Posed Linear Systems with Time Discretization Based Iterative Regularization Methods

Recently,inverse problems have attracted more and more attention in computational mathematics and become increasingly important in engineering applications.After the discretization,many of inverse problems are reduced to linear systems.Due to the typical ill-posedness of inverse problems,the reduced linear systems are often illposed,especially when their scales are large.This brings great computational difficulty.Particularly,a small perturbation in the right side of an ill-posed linear system may cause a dramatical change in the solution.Therefore,regularization methods should be adopted for stable solutions.In this paper,a new class of accelerated iterative regularization methods is applied to solve this kind of large-scale ill-posed linear systems.An iterative scheme becomes a regularization method only when the iteration is early terminated.And a Morozov’s discrepancy principle is applied for the stop criterion.Compared with the conventional Landweber iteration,the new methods have acceleration effect,and can be compared to the well-known acceleratedν-method and Nesterov method.From the numerical results,it is observed that using appropriate discretization schemes,the proposed methods even have better behavior when comparing withν-method and Nesterov method.

Chromatic Adaptation to Complex Field

Chromatic adaptation of human eyes to complex field is investigated using binocular asymmetric matching method. The results show that the leve of chromatic adapta- tion mainly depends on the average color of adapting field, whereas no obvious change oc- curs when the number of hues and their color differences vary in a complex field. The shifts of perceived color evoked by chromatic adaptation in CIE 1976 L U V color space are approximately proportional to the average color difference between the adapting field and reference field.

Congenital absence of the splenic artery and splenic vein accompanied with a duodenal ulcer and deformity

Congenital absence of the splenic artery is a very rare condition.To the best of our knowledge, congenital absence of the splenic artery accompanied with absence of the splenic vein has not been reported.We report a case of the absence of the splenic artery and vein in a 61-year-old woman who presented with postprandial epigastric discomfort. Upper gastrointestinal endoscopy showed a dilated, pulsatile vessel in the fundus and duodenal stenosis. An abdominal computed tomography(CT)scan revealed absence of the splenic vein with a tortuously engorged gastroepiploic vein.Three-dimensional CT demonstrated the tortuously dilated left gastric artery and the left gastroepiploic artery with non-visualization of the splenic artery.After administration of a proton pump inhibitor,abdominal symptoms resolved without any recurrence of symptoms during 6 mo of follow-up.

Improper Choosability of Planar Graphs without 6-circuits

A graph G is called（k,d）＊-choosable if for every list assignment L satisfying ｜L（v）｜=k for all v ∈ V（G）,there is an L-coloring of G such that each vertex of G has at most d neighbors colored with the same color as itself.In this paper,it is shown that every planar graph without 6-circuits and a triangle adjacent to itself or a quadrangle is（3,1）＊-choosable.

A Regularized Randomized Kaczmarz Algorithm for Large Discrete Ill-Posed Problems

Tikhonov regularization is a powerful tool for solving linear discrete ill-posed problems.However,effective methods for dealing with large-scale ill-posed problems are still lacking.The Kaczmarz method is an effective iterative projection algorithm for solving large linear equations due to its simplicity.We propose a regularized randomized extended Kaczmarz(RREK)algorithm for solving large discrete ill-posed problems via combining the Tikhonov regularization and the randomized Kaczmarz method.The convergence of the algorithm is proved.Numerical experiments illustrate that the proposed algorithm has higher accuracy and better image restoration quality compared with the existing randomized extended Kaczmarz(REK)method.

INSTABILITY OF SYMMETRIC TYPHOON CIRCULATION AND ADAPTIVE OBSERVATION

This study presents a new way to identify the sensitive areas,which are determined by invoking the negative anomalies of moist potential vorticity (MPV) for typhoon adaptive observations. It is found that the areas of negative MPV are the symmetric instability areas and can be taken as sensitive areas for typhoon adaptive observations. Three typhoons in 2008,Nuri,Fung-wong,and Fengshen,were simulated with the help of MM5 model. It is shown that these typhoons are well simulated in the first 12 hours. Based on these investigations,the calculations of MPV are carried out sequentially. The result shows that the negative maxima of MPV are always around the typhoon eyes for all the cases,which means that the sensitive areas are also near them all the time.

Discrete-Rate Adaptive Modulation with Variable Threshold for Distributed Antenna System in the Presence of Imperfect CSI

Discrete-rate adaptive modulation （AM） scheme for distributed antenna system （DAS） with imperfect channel state information （CSI） is developed, and the corresponding performance is investigated in composite Rayleigh channel. Subject to target bit error rate （BER） constraint, an improved fixed switching threshold （FST） for the AM scheme is presented by means of tightly-approximate BER expression, and it can avoid the performance loss fxom conventional FST. Based on the imperfect CSI, the variable switching threshold （VST） is derived by utilizing the maximum a posteriori method. This VST includes the improved FST as a special case, and may lower the impact of estimation error on the performance. By the switching thresholds, the spectrum efficiency （SE） and average BER of the system are respectively derived, and resulting closed- form expressions are attained. With these expressions, the system performance can be effectively evaluated. Simulation results show that the derived theoretical SE and BER can match the simulations well. Moreover, the AM with the presented FST has higher SE than that with the conventional one, and the AM with VST can tolerate the large estimation error while maintaining the target BER.

A Self-Adaptive Control Method for Uncertainty Systems Based on ANN with AEP

A self-adaptive control method is proposed based on an artificial neural network(ANN)with accelerated evolutionary programming(AEP)algorithm.The neural network is used to model the uncertainty process,from which the teacher signals are produced online to regulate the parameters of the controller.The accelerated evolutionary programming is used to train the neural network.The experiment results show that the method can obviously improve the dynamic performance of uncertainty systems.

Adaptive Energy-Efficient Power Allocation for DAS with Imperfect Channel State Information and Antenna Selection

Considering that perfect channel state information(CSI) is difficult to obtain in practice,energy efficiency(EE) for distributed antenna systems(DAS) based on imperfect CSI and antennas selection is investigated in Rayleigh fading channel.A novel EE that is defined as the average transmission rate divided by the total consumed power is introduced.In accordance with this definition,an adaptive power allocation(PA) scheme for DAS is proposed to maximize the EE under the maximum transmit power constraint.The solution of PA in the constrained EE optimization does exist and is unique.A practical iterative algorithm with Newton method is presented to obtain the solution of PA.The proposed scheme includes the one under perfect CSI as a special case,and it only needs large scale and statistical information.As a result,the scheme has low overhead and good robustness.The theoretical EE is also derived for performance evaluation,and simulation result shows the validity of the theoretical analysis.Moreover,EE can be enhanced by decreasing the estimation error and/or path loss exponents.

Adaptive control using interval Type-2 fuzzy logic for uncertain nonlinear systems

A new adaptive Type-2 （T2） fuzzy controller was developed and its potential performance advantage over adaptive Type-1 （T1） fuzzy control was also quantified in computer simulation. Base on the Lyapunov method, the adaptive laws with guaranteed system stability and convergence were developed. The controller updates its parameters online using the laws to control a system and tracks its output command trajectory. The simulation study involving the popular inverted pendulum control problem shows theoretically predicted system stability and good tracking performance. And the comparison simulation experiments subjected to white noige or step disturbance indicate that the T2 controller is better than the T1 controller by 0--18%, depending on the experiment condition and performance measure.

Adaptive backstepping control for levitation system with load uncertainties and external disturbances

To explore the precise dynamic response of the levitation system with active controller, a maglev guide way-electromagnet-air spring-cabin coupled model is derived firstly. Based on the mathematical model, it shows that the inherent nonlinearity, inner coupling, misalignments between the sensors and actuators, load uncertainties and external disturbances are the main issues that should be solved in engineering. Under the assumptions that the loads and external disturbance are measurable, the backstepping module controller developed in this work can tackle the above problems effectively. In reality, the load is uncertain due to the additions of luggage and passengers, which will degrade the dynamic performance. A load estimation algorithm is introduced to track the actual load asymptotically and eliminate its influence by tuning the parameters of controller online. Furthermore,considering the external disturbances generated by crosswind, pulling motor and air springs, the extended state observer is employed to estimate and suppress the external disturbance. Finally, results of numerical simulations illustrating closed-loop performance are provided.

L_1 adaptive controller of nonlinear reference system in presence of unmatched uncertainties

An extension of L_1 adaptive control is proposed for the unmatched uncertain nonlinear system with the nonlinear reference system that defines the performance specifications. The control law adapts fast and tracks the reference system with the guaranteed robustness and transient performance in the presence of unmatched uncertainties. The interval analysis is used to build the quasi-linear parameter-varying model of unmatched nonlinear system, and the robust stability of the proposed controller is addressed by sum of squares programming. The transient performance analysis shows that within the limit of hardware a large adaption gain can improve the asymptotic tracking performance. Simulation results are provided to demonstrate the theoretical findings of the proposed controller.

Adaptive robust output force tracking control of pneumatic cylinder while maximizing/minimizing its stiffness

The system considered in this work consists of a cylinder which is controlled by a pair of three-way servo valves rather than a four-way one.Therefore,the cylinder output stiffness is independently controllable of the output force.A discontinuous projection based adaptive robust controller (ARC) was constructed to achieve high-accuracy output force trajectory tracking for the system.In ARC,on-line parameter adaptation method was adopted to reduce the extent of parametric uncertainties due to the variation of friction parameters,and sliding mode control method was utilized to attenuate the effects of parameter estimation errors,unmodelled dynamics and disturbance.Furthermore,output stiffness maximization/minimization was introduced to fulfill the requirement of many robotic applications.Extensive experimental results were presented to illustrate the effectiveness and the achievable performance of the proposed scheme.For tracking a 0.5 Hz sinusoidal trajectory,maximum tracking error is 4.1 N and average tracking error is 2.2 N.Meanwhile,the output stiffness can be made and maintained near its maximum/minimum.

Comparing dynamical systems concepts and techniques for biomechanical analysis

Traditional biomechanical analyses of human movement are generally derived from linear mathematics.While these methods can be useful in many situations,they do not describe behaviors in human systems that are predominately nonlinear.For this reason,nonlinear analysis methods based on a dynamical systems approach have become more prevalent in recent literature.These analysis techniques have provided new insights into how systems(1) maintain pattern stability,(2) transition into new states,and(3) are governed by short-and long-term(fractal) correlational processes at different spatio-temporal scales.These different aspects of system dynamics are typically investigated using concepts related to variability,stability,complexity,and adaptability.The purpose of this paper is to compare and contrast these different concepts and demonstrate that,although related,these terms represent fundamentally different aspects of system dynamics.In particular,we argue that variability should not uniformly be equated with stability or complexity of movement.In addition,current dynamic stability measures based on nonlinear analysis methods(such as the finite maximal Lyapunov exponent) can reveal local instabilities in movement dynamics,but the degree to which these local instabilities relate to global postural and gait stability and the ability to resist external perturbations remains to be explored.Finally,systematic studies are needed to relate observed reductions in complexity with aging and disease to the adaptive capabilities of the movement system and how complexity changes as a function of different task constraints.