基于混沌控制的采摘机器人防碰撞系统设计

针对采摘机器人在作业过程中遇到障碍物导致路径规划出现混沌现象的问题,基于混沌控制对采摘机器人防碰撞系统进行设计,并采用模糊自适应控制算法和滑模变结构控制算法结构的方式对系统进行控制。为了验证防碰撞系统的有效性,对采摘机器人进行了防碰撞和采摘仿真试验,结果表明:采摘机器人在作业过程中可以避开障碍物,按照规划路线到达预设位置,完成果蔬的采摘。

旋转导向钻井系统稳定平台变结构控制研究

通过构建旋转导向钻井系统稳定平台的数学模型和分析稳定平台的工作环境,提出了稳定平台变结构控制方案。验证了稳定平台控制系统对于变结构控制的不变性条件,构造了滑动模态。采用指数趋近率和柔化符号函数法,设计了大幅度削减振颤的控制律。对设计出的变结构控制系统进行了计算机仿真和地面模拟试验,结果表明,该控制算法鲁棒性强,控制精度比较高,跟踪速度快,具有良好的控制效果。

多变量模糊控制的研究现状

从控制算法结构和规则获取两个方面，介绍了多变量模糊控制新近发展成果，并对其中存在的理论与实际问题进行了探讨。

基于滑模变结构控制算法的气压ABS控制器设计

根据商务车的制动过程,建立了车辆单轮制动模型.针对制动过程中的高度非线性,设计了基于滑模变结构控制算法的气压ABS(Anti-lock Braking System)系统,分为总体设计、硬件设计、滑模变结构控制算法和系统软件实现4部分.气压ABS的电控单元由轮速信号调理电路、阀驱动电路和CAN总线通信电路组成;系统软件的实现采用模块化编程思想,分为初始化、车辆行驶状态监测和ABS算法介入共3部分内容.高附着路面试验证明了系统的鲁棒性和可靠性.

Study on LQR control algorithm using superelement model

The conventional linear quadratic regulator(LQR) control algorithm is one of the most popular active control algorithms.One important issue for LQR control algorithm is the reduction of structure's degrees of freedom(DOF). In this work, an LQR control algorithm with superelement model is intended to solve this issue leading to the fact that LQR control algorithm can be used in large finite element(FE) model for structure. In proposed model, the Craig-Bampton(C-B) method, which is one of the component mode syntheses(CMS), is used to establish superelement modeling to reduce structure's DOF and applied to LQR control algorithm to calculate Kalman gain matrix and obtain control forces. And then, the control forces are applied to original structure to simulate the responses of structure by vibration control. And some examples are given. The results show the computational efficiency of proposed model using synthesized models is higher than that of the classical method of LQR control when the DOF of structure is large. And the accuracy of proposed model is well. Meanwhile, the results show that the proposed control has more effects of vibration absorption on the ground structures than underground structures.

The IMC Structure of Multi-rate Multivariable Predictive Control Systems and An Improved Algorithm

Multirate multivariable predictive control system with the sampling mechanism that adjusts the plant inputs only once but detects the plant outputs several times during a period is examined. The IMC structure of the system is derived, and its robust stability and zero steady state error characteristics are analyzed. A new control algorithm is developed by adding the variation of the outputs to the index performance. The simulation results show that the method is effective and has zeros steady-state error.

PTCP Incast in Data Center Networks

In recent years,dual-homed topologies have appeared in data centers in order to offer higher aggregate bandwidth by using multiple paths simultaneously.Multipath TCP(MPTCP) has been proposed as a replacement for TCP in those topologies as it can efficiently offer improved throughput and better fairness.However,we have found that MPTCP has a problem in terms of incast collapse where the receiver suffers a drastic goodput drop when it simultaneously requests data over multiple servers.In this paper,we investigate why the goodput collapses even if MPTCP is able to actively relieve hot spots.In order to address the problem,we propose an equally-weighted congestion control algorithm for MPTCP,namely EW-MPTCP,without need for centralized control,additional infrastructure and a hardware upgrade.In our scheme,in addition to the coupled congestion control performed on each subflow of an MPTCP connection,we allow each subflow to perform an additional congestion control operation by weighting the congestion window in reverse proportion to the number of servers.The goal is to mitigate incast collapse by allowing multiple MPTCP subflows to compete fairly with a single-TCP flow at the shared bottleneck.The simulation results show that our solution mitigates the incast problem and noticeably improves goodput in data centers.

Market based framework for multiple AUVs cooperation

A“Market” based framework for multiple AUVs team is introduced in this paper.It is a distributed meta-level task allocation framwork. The formulation and the basic concepts of the “Market” such as “goods” and “price” are discussed first, then the basic algorithm of the “auction”. The loosely coupled v-MDTSP tasks are considered as an example of the task allocation mission. A multiple AUV team controller and a detailed algorithm are developed for such applications. The simulation results show that the controller has the advantages such as robustness and low complexity and it can achieve better optimization results than the classical central controller (such as GA) in some tasks. And the comparison of two different local solvers also implies that we should get the reasonable task allocation even not using the high quality algorithm, which can considerably decrease the cooperation computation.

Fuzzy adaptive learning control network with sigmoid membership function

To get simpler operation in modified fuzzy adaptive learning control network （FALCON） in some engineering application, sigmoid nonlinear function is employed as a substitute of traditional Gaussian membership function. For making the modified FALCON learning more efficient and stable, a simulated annealing （SA） learning coefficient is introduced into learning algorithm. At first, the basic concepts and main advantages of FALCON were briefly reviewed. Subsequently, the topological structure and nodes operation were illustrated; the gradient-descent learning algorithm with SA learning coefficient was derived; and the distinctions between the archetype and the modification were analyzed. Eventually, the significance and worthiness of the modified FALCON were validated by its application to probability prediction of anode effect in aluminium electrolysis cells.

Research of the test generation algorithm based on search state dominance for combinational circuit

On the basis of EST (Equivalent STate hashing) algorithm, this paper researches a kind of test generation algorithm based on search state dominance for combinational circuit. According to the dominance relation of the E-frontier (evaluation frontier), we can prove that this algorithm can terminate unnecessary searching step of test pattern earlier than the EST algorithm through some examples, so this algorithm can reduce the time of test generation. The test patterns calculated can detect faults given through simulation.

Optimization and Control of Extractive Distillation with Heat Integration for Separating Benzene/Cyclohexane Mixtures

In this work, the extractive distillation with heat integration process is extended to separate the pressure-insensitive benzene-cyclohexane azeotrope by using furfural as the entrainer. The optimal design of extractive distillation process is established to achieve minimum energy requirement using the multi-objective genetic algorithm, and the results show that energy saving for this heat integration process is 15.7%. Finally, the control design is performed to investigate the system's dynamic performance, and three control structures are studied. The pressure-compensated temperature control scheme is proposed based on the first two control structures, and the dynamic responses reveal that the feed disturbances in both flow rate and benzene composition can be mitigated well.

Research on Intelligent Control of Roving Frame

A new model of roving frame FA467, which uses four frequency inverters to replace the complex mechanical transmission, is discussed. A Neuron-PID is designed to reduce the effect of various parametric variations such as load inertia. To ensure the constant spinning tension all over the spinning process, a feedforward controller using iterative learning control algorithm is desigend to avoid disturbances caused by changes of temperature, humidity and so on. The simulation result is shown to illustrate the effectiveness of the proposed algorithm, and now the roving frame FA467 has been developed successfully.

板球系统控制研究综述

板球系统是一种具有非线性、强耦合性、参数不确定性以及存在未知干扰的被控对象,涉及运动控制、机器视觉和智能控制算法等诸多研究领域,多领域融合的特性使得以板球系统为对象的研究具有挑战性。对板球系统数学模型和主要控制方法,包括模糊控制算法、人工神经网络控制算法、群智能优化算法、滑模变结构控制算法和一些其他先进控制算法进行综述和分析,给出在智能制造背景下该领域的研究趋势。

Controlling structural vibrations in wind turbines by constructing function V

For a variable speed large scale wind turbine, the vibration issues become a key problem that cannot be ignored in the turbine＇s life cycle. Wind turbine tower vibration will cause superfluous mechanical loads. To resolve the vibration issue, a method for constructng the energy function V is proposed to meet the demands of safe operation. The Lyapunov theorem has been em- bedded in a wind turbine control algorithm, proving the theoretical feasibility of stability control based on function V. Accord- ing to an analysis of this complex nonlinear model for the wind turbine, the general method of constructing an energy function suitable for a wind turbine is presented explicitly. The feasibility of applying an energy function to wind turbine vibration con- trol is verified experimentally using a 3.0-MW direct drive wind turbine model. The experimental results indicate that the dy- namic performance of the tested wind turbine model with energy function control is significantly better than that of the uncon- trolled structure in terms of the reduction of nacelle acceleration, velocity, and displacement response.

MATTER-ELEMENT MODELING OF PARALLEL STRUCTURE AND APPLICATION ABOUT EXTENSION PID CONTROL SYSTEM

This article describes in detail a new method via the extension predictable algorithm of the matter-element model of parallel structure tuning the parameters of the extension PID controller. In comparison with fuzzy and extension PID controllers, the proposed extension PID predictable controller shows higher control gains when system states are away from equilibrium, and retains a lower profile of control signals at the same time. Consequently, better control performance is achieved. Through the proposed tuning formula, the weighting factors of an extension-logic predictable controller can be systematically selected according to the control plant. An experimental example through industrial field data and site engineers＇ experience demonstrates the superior performance of the proposed controller over the fuzzy controller.