FORCE FEEDBACK MODEL OF ELECTRO-HYDRAULIC SERVO TELE-OPERATION ROBOT BASED ON VELOCITY CONTROL

The tele-operation robotic system which consists of an excavator as the construction robot, and two joysticks for operating the robot from a safe place are useful for performing restoration in damaged areas. In order to accomplish a precise task, the operator needs to feel a realistic sense of task force brought about from a feedback force between the fork glove of slave robot and unfamiliar environment. A novel force feedback model is proposed based on velocity control of cylinder to determine environment force acting on fork glove. Namely, the feedback force is formed by the error of displacement of joystick with velocity and driving force of piston, and the gain is calculated by the driving force and threshold of driving force of hydraulic cylinder. Moreover, the variable gain improved algorithm is developed to overcome the defect for grasping soft object. Experimental results for fork glove freedom of robotic system are provided to demonstrate the developed algorithm is available for grasping soft object.

Development of a displacement-reactivity feedback model for dynamic behavior simulation in fast burst reactor

In this study, a displacement-reactivity feedback model, which can directly represent the inherent ‘‘thermal expansion extinction effect'' of fast burst reactors(FBRs),was developed with the aid of the static neutron transport component of the FBR-MPC code. Dynamic behaviors of bursts in the Godiva I reactor were simulated by coupling the simplified multiphysics models consisting of the point kinetic equations for neutronics, adiabatic equation for temperature, and thermoelastic equations for displacement/stress with the developed model. The results were compared with the corresponding experimental data and those obtained using the traditional fission yield(temperature rise)-reactivity feedback models. It was found that the developed model can provide good results for the bursts with no or a small inertia effect. For the bursts with a prominent inertia effect, the smaller burst width and asymmetric distribution of the fission rate curve, noticed in the experiments but not evident using the traditional models, can be reproduced. In addition, the realistic oscillations in reactivity and fission rate caused by the core vibration, as well as the deeper sub-prompt criticality in the plateau following the burst, can be observed. Therefore, the developed displacement-reactivity feedback model can be expected to be an effective tool for calculating the dynamic behaviors of bursts.

Feedback linearization of the nonlinear model of a small-scale helicopter

In order to design a nonlinear controller for small-scale autonomous helicopters, the dynamic characteristics of a model helicopter are investigated, and an integrated nonlinear model of a small-scale helicopter for hovering control is presented. It is proved that the nonlinear system of the small-scale helicopter can be transformed to a linear system using the dynamic feedback linearization technique. Finally, simulations are carried out to validate the nonlinear controller.

An improved car-following model with consideration of the lateral effect and its feedback control research

A car-following model is presented, in which the effects of non-motor vehicles on adjacent lanes are taken into ac- count. A control signal including the velocity differences between the following vehicle and the target vehicle is introduced according to the feedback control theory. The stability condition for the new model is derived. Numerical simulation is used to demonstrate the advantage of the new model including the control signal; the results are consistent with the analytical ones

A population-feedback control based algorithm for well trajectory optimization using proxy model

Wellbore instability is one of the concerns in the field of drilling engineering.This phenomenon is affected by several factors such as azimuth,inclination angle,in-situ stress,mud weight,and rock strength parameters.Among these factors,azimuth,inclination angle,and mud weight are controllable.The objective of this paper is to introduce a new procedure based on elastoplastic theory in wellbore stability solution to determine the optimum well trajectory and global minimum mud pressure required(GMMPR).Genetic algorithm(GA) was applied as a main optimization engine that employs proportional feedback controller to obtain the minimum mud pressure required(MMPR).The feedback function repeatedly calculated and updated the error between the simulated and set point of normalized yielded zone area(NYZA).To reduce computation expenses,an artificial neural network(ANN) was used as a proxy(surrogate model) to approximate the behavior of the actual wellbore model.The methodology was applied to a directional well in southwestern Iranian oilfield.The results demonstrated that the error between the predicted GMMPR and practical safe mud pressure was 4%for elastoplastic method,and 22%for conventional elastic solution.

Energy feedback and synchronous dynamics of Hindmarsh–Rose neuron model with memristor

We analyze the energy aspects of single and coupled Hindmarsh–Rose(HR) neuron models with a quadratic flux controlled memristor. The energy function for HR neuron with memristor has been derived and the dynamics have been analyzed in the presence of various external stimuli. We found that the bursting mode of the system changes with external forcing. The negative feedback in Hamilton energy function effectively stabilizes the chaotic trajectories and controls the phase space. The Lyapunov exponents have been plotted to verify the stabilization of trajectories. The energy aspects during the synchronous dynamics of electrically coupled neurons have been analyzed. As the coupling strength increases, the average energy fluctuates and stabilizes at the point of synchronization. When the neurons are coupled via chemical synapse,the average energy variations show three important regimes: a fluctuating regime corresponding to the desynchronized, a stable region indicating synchronized and a linearly increasing regime corresponding to the amplitude death states have been observed. The synchronization transitions are verified by plotting the transverse Lyapunov exponents. The proposed method has a large number of applications in controlling coupled chaotic systems and in analyzing the energy change during various metabolic processes.

Existence of Two Periodic Solutions of a Delayed Single Species Model with Feedback Regulation and Harvest Term

借助于巧合度理论的继续定理，有反馈规定和收获术语的一个推迟的单个种类模型的二个周期的答案的存在被获得。

Confidence domain in the stochastic competition chemostat model with feedback control

This paper studies a stochastically forced chemostat model with feedback control in which two organisms compete for a single growth-limiting substrate. In the deterministic counterpart, previous researches show that the coexistence of two competing organisms may be achieved as a stable positive equilibrium or a stable positive periodic solution by different feedback schedules. In the stochastic case, based on the stochastic sensitivity function technique,we construct the confidence domains for different feedback schedules which allow us to find the configurational arrangements of the stochastic attractors and analyze the dispersion of the random states of the stochastic model.

Model-Following Designs Using Direct State Derivative Measurement Feedback in Novel Reciprocal State Space Form

The paper introduces effective and straightforward algorithms of both explicit and implicit model-following designs with state derivative measurement feedback in novel reciprocal state space form (RSS) to handle state derivative related performance output and state related performance output design cases. Applying proposed algorithms, no integrators are required. Consequently, implementation is simple and low-cost. Simulation has also been carried out to verify the proposed algorithms. Since acceleration can only be modeled as state derivative in state space form and micro-accelerometer which is the state derivative sensor is getting more and more attentions in many microelectromechanical and nanoelectromechanical systems (MEMS/NEMS) applications, the proposed algorithms are suitable for MEMS/NEMS systems installed with micro-accelerometers.

Atmospheric feedbacks on Arctic summer sea-ice anomalies in ensemble simulations of a coupled regional climate model

Ensemble simulations with the Arctic coupled regional climate model HIRHAM-NAOSIM have been analyzed to investigate atmospheric feedbacks to September sea-ice anomalies in the Arctic in autumn and the following winter. Different ＂low- minus high ice＂ composites have been calculated using selected model runs and different periods. This approach allows us to investigate the robustness of the simulated regional atmospheric feedbacks to detected sea-ice anomalies. Since the position and strength of the September sea-ice anomaly varies between the different ＂low- minus high ice＂ composites, the related simulated atmospheric patterns in autumn differ depending on the specific surface heat flux forcing through the oceaaa-atmosphere interface. However, irrespective of those autumn differences, the regional atmospheric feedback in the following winter is rather insensitive to the applied compositing. Neither the selection of simulations nor the considered period impacts the results. The simulated consistent large-scale atmospheric circulation pattern show-s a wave-like pattern with positive pressure anomaly over the region of the Barents/Kara Seas and Scandinavia/western Russia （＂Scandinavian-Ural blocking＂） and negative pressure anomaly over the East Siberian/Laptev Seas.

Robust State Feedback H_∞Control for Dynamic Biped Robot Based on T-S Fuzzy Model

T-S fuzzy model was applied to describe nonlinear system and global fuzzy model was expressed by the form of uncertain system.Based on robust state feedback H_∞control strategy,designed a global asymptotic steady fuzzy model.This control system can use the experimental input-output data pairs for the biped robot learning and walking with dynamic balance.It is proved by simulation result that robust state feedback H_∞control method based on T-S fuzzy model can effectively restrain the effect of model uncertainties and external disturbance acting on biped robot.From these works,we showed the satisfactory performance of joint tracking without any chattering.

Generating Li-Yorke chaos in a stable continuous-time T-S fuzzy model via time-delay feedback control

This paper investigates the chaotification problem of a stable continuous-time T S fuzzy system. A simple nonlinear state time-delay feedback controller is designed by parallel distributed compensation technique. Then, the asymptotically approximate relationship between the controlled continuous-time T-S fuzzy system with time-delay and a discrete-time T-S fuzzy system is established. Based on the discrete-time T-S fuzzy system, it proves that the chaos in the discrete- time T-S fuzzy system satisfies the Li-Yorke definition by choosing appropriate controller parameters via the revised Marotto theorem. Finally, the effectiveness of the proposed chaotic anticontrol method is verified by a practical example.

POSITIVE PERIODIC SOLUTION FOR A NONAUTONOMOUS LOGISTIC MODEL WITH LINEAR FEEDBACK REGULATION

A nonautonomous delayed logistic model with linear feedback regulation is proposed in this paper. Sufficient conditions are derived for the existence, uniqueness and global asymptotic stability of positive periodic solution of the model

Mathematical Model of Cell Growth for Biofuel Production under Synthetic Feedback

In this paper, mathematical model for cell growth and biofuel production under synthetic feedback loop is discussed. The nonlinear differential equations are solved analytically for the maximum production of biofuel under synthetic feedback. The closed-form of analytical expressions pertaining to the concentrations of cell density, repressor proteins, pump expressions, intracellular biofuel and extracellular biofuel are presented. The constant pump model is compared with feedback loop model analytically to know the biofuel production. The numerical solution of this problem is also reported using Scilab/Matlab program. Also, the analytical results are compared with previous published numerical results and found to be in good agreement.

The Design of Output Feedback Distributed Model Predictive Controller for a Class of Nonlinear Systems

For a class of nonlinear systems whose states are immeasurable, when the outputs of the system are sampled asynchronously, by introducing a state observer, an output feedback distributed model predictive control algorithm is proposed. It is proved that the errors of estimated states and the actual system's states are bounded. And it is guaranteed that the estimated states of the closed-loop system are ultimately bounded in a region containing the origin. As a result, the states of the actual system are ultimately bounded. A simulation example verifies the effectiveness of the proposed distributed control method.

超导磁储能装置提高柔性直流配电系统稳定性的研究

柔性直流配电系统中定功率控制的换流器具有恒功率负载特性,会降低系统阻尼,对系统的稳定性产生不利影响。针对该问题,在直流配电系统中加入超导磁储能SMES(superconducting magnetic energy storage)装置来提高系统的稳定性。推导了柔性直流配电系统的反馈控制模型,采用频域分析法研究了换流器恒功率负载特性对系统稳定性的影响,并结合数学模型和频域分析,指出SMES装置能够为电网提供正阻尼,增大了系统开环传递函数在剪切频率处的相位裕度,从而改善了系统稳定性。为防止超导磁体两端电压过高,SMES装置与直流配电网连接的DC/DC换流器需具备一定的电压调节性能,因此研究了采用模块化多电平DC/DC换流器DC-MMC(modular multilevel DC/DC converter)的SMES装置,通过调节子模块个数灵活设置换流器电压变比,在实现换流器能量双向流动的同时控制超导磁体两端电压,以保护储能装置。最后通过时域仿真波形验证了采用DC-MMC的SMES装置在提高柔性直流配电系统稳定性方面的可行性和有效性。

A deep learning–based U-Net model for ENSO-related precipitation responses to sea surface temperature anomalies over the tropical Pacific

SST–降水反馈过程在热带太平洋ENSO演变过程中起着重要作用,能否真实地在数值模式中表征SST–降水年际异常之间的关系及相关反馈过程,对于准确模拟和预测ENSO至关重要.例如,在一些模拟ENSO的混合型耦合模式中,通常采用大气统计模型(如经验正交函数;EOF)来表征降水(海气界面淡水通量的一个重要分量)对SST年际异常的线性响应.然而在当前的耦合模式中,真实观测到的降水–SST统计关系还不能被很好地再现出来,从而引起ENSO模拟误差和不确定性.在本研究中,使用基于深度学习的U-Net模型来构建热带太平洋降水异常场对SST年际异常的非线性响应模型.研究发现:U-Net模型的性能优于传统的基于EOF方法的模型.特别是在热带西太平洋海区,U-Net模型估算的降水误差远小于EOF模型的模拟.此外,当SST和降水异常的趋势信息作为输入变量也被同时引入以进一步约束模式训练时,U-Net模型的性能可以进一步提高,如能使热带辐合带区域的误差显著降低.

基于PSO-BP神经网络的分拣机器人视觉反馈跟踪

针对分拣机器人视觉反馈跟踪精度差、耗时较长的问题,研究基于粒子群算法-反向传播(particle swarm optimization-back propagation,PSO-BP)神经网络的分拣机器人视觉反馈跟踪方法,以提升视觉反馈跟踪效果。依据分拣机器人的视觉反馈信息,建立分拣机器人运动学模型,并求解分拣机器人机械臂输出位置和输入位置的误差函数;利用PSO算法优化BP神经网络的权值与偏置;在权值与偏置优化后的BP神经网络内,输入误差函数,预测分拣机器人视觉反馈跟踪控制量;利用预测视觉反馈跟踪控制量,在线调整增量式比例-积分-微分(proportional-integral-derivative,PID)的参数,输出高精度的分拣机器人视觉反馈跟踪控制量,实现分拣机器人视觉反馈跟踪。实验结果表明,该方法可有效视觉反馈跟踪分拣机器人机械臂的关节角;存在干扰情况下,在运行时间为10 s左右时,阶跃响应趋于稳定;有干扰情况下,视觉反馈跟踪的平均误差为0.09 cm,耗时平均值为0.10 ms;无干扰情况下,平均误差为0.03 cm,耗时平均值为0.04 ms。

“电力电子技术基础”闭环型教学控制模型分析与实践

自动控制原理中的反馈闭环控制结构可以消除设定值与输出值之间的误差,使输出值跟随设定值或输入值。本文给出几种单闭环或双闭环反馈型教学控制结构,在与自动控制原理中反馈闭环控制结构进行对比分析后,分析了反馈型教学控制结构的工作原理,并给出了过去反馈型教学控制获得的经验,表明反馈型教学控制结构概念清晰,互操作性强,执行效率高,可扩展性强,易于推广应用。