Self-adapting control parameters modifieddifferential evolution for trajectoryplanning of manipulators

Control parameters of original differential evolution （DE） are kept fixed throughout the entire evolutionary process. However, it is not an easy task to properly set control parameters in DE for different optiinization problems. According to the relative position of two different individual vectors selected to generate a difference vector in the searching place, a self-adapting strategy for the scale factor F of the difference vector is proposed. In terms of the convergence status of the target vector in the current population, a self-adapting crossover probability constant CR strategy is proposed. Therefore, good target vectors have a lower CFI while worse target vectors have a large CFI. At the same time, the mutation operator is modified to improve the convergence speed. The performance of these proposed approaches are studied with the use of some benchmark problems and applied to the trajectory planning of a three-joint redundant manipulator. Finally, the experiment results show that the proposed approaches can greatly improve robustness and convergence speed.

Self-adaptive PID controller of microwave drying rotary device tuning on-line by genetic algorithms

The control design, based on self-adaptive PID with genetic algorithms(GA) tuning on-line was investigated, for the temperature control of industrial microwave drying rotary device with the multi-layer(IMDRDWM) and with multivariable nonlinear interaction of microwave and materials. The conventional PID control strategy incorporated with optimization GA was put forward to maintain the optimum drying temperature in order to keep the moisture content below 1%, whose adaptation ability included the cost function of optimization GA according to the output change. Simulations on five different industrial process models and practical temperature process control system for selenium-enriched slag drying intensively by using IMDRDWM were carried out systematically, indicating the reliability and effectiveness of control design. The parameters of proposed control design are all on-line implemented without iterative predictive calculations, and the closed-loop system stability is guaranteed, which makes the developed scheme simpler in its synthesis and application, providing the practical guidelines for the control implementation and the parameter design.

Variable Parameter Self-Adaptive Control Strategy Based on Driving Condition Identification for Plug-In Hybrid Electric Bus

A variable parameter self-adaptive control strategy based on driving condition identification is proposed to take full advantage of the fuel saving potential of the plug-in hybrid electric bus(PHEB).Firstly,the principal component analysis(PCA)and the fuzzy c-means clustering(FCM)algorithm is used to construct the comprehensive driving cycle,congestion driving cycle,urban driving cycle and suburban driving cycle of Chinese urban buses.Secondly,an improved particle swarm optimization(IPSO)algorithm is proposed,and is used to optimize the control parameters of PHEB under different driving cycles,respectively.Then,the variable parameter self-adaptive control strategy based on driving condition identification is given.Finally,for an actual running vehicle,the driving condition is identified by relevance vector machine(RVM),and the corresponding control parameters are selected to control the vehicle.The simulation results show that the fuel consumption of using the variable parameter self-adaptive control strategy is reduced by 4.2% compared with that of the fixed parameter control strategy,and the feasibility of the variable parameter self-adaptive control strategy is verified.

Frequency detection of self-adaption control based on chaotic theory

Low-order Duffing and high-order Rossler chaotic oscillator are connected together and new self-adaption frequency detection method is presented. The frequency difference control between unknown signal and the periodic driving force is realized in this paper and the self-adaption is obtained. Thus, the detection precision and speed are promoted. The limitation that there are too many chaotic oscillators in Duffing system is broken. Meanwhile the disadvantage that the detection speed is lower in R ssler chaotic control is overcome. The self-adaption choice of frequency difference control is realized using the Duffing and Rssler different chaotic oscillators to obtain unknown signal frequency. The simulation results show that the presented method is feasible and effective.

Self-Adaptive QoS Control in Cognitive Networks That Is Based on Service Awareness

This paper analyzes a self-adaptive Quality of Service （QoS） control architecture for cognitive networks （CNs） that is based on intelligent service awareness. In this architecture, packets can be identified and classified using an intelligent service-aware classification model. Drawing on Control Theory, network traffic can be controlled with a self-adaptive QoS control mechanism that has side-road collaboration. In this architecture, perception, analysis, correlation, feedback, decision making, allocation, and implementation QoS mechanisms are created automatically. These mechanisms can adjust resource allocation, adapt to a changeable network environment, optimize end-to-end performance of the network, and ensure QoS.

A self-adaptive synchronization controller for Liu chaotic systems

A kind of synchronization controller for Liu chaotic systems whose nonlinear components are subject to Lipschitz condition was proposed. By using Lyapunov function and linear matrix inequality technique, a self-adaptive synchronization controller was constructed for Liu chaotic systems. There are two components of our derived synchronization controller: linear and nonlinear component. Linear component is composed of errors of the state variables between driving-systems and responding-stems, and nonlinear component is a self-adaptive synchronization controller. a proof was given for proving the feasibility of this method, and numerical simulations of Liu chaotic systems show its effectiveness. Furthermore, this method can be applied to other chaotic systems, such as Chen systems, Lorenz systems, Chua systems and Rssler systems,etc.

Study of NURBS Interpolation Algorithm Based on Self-adaptive Control

Aimed at problems such as profile error increasing and acceleration enlarging and tool machine working instability and quality decreasing of workpiece surfaces in processing complicated curved surfaces because of several variable curvatures, an improved method of NURBS interpolation is adopted. According to self-adaptive programming principles, self-adaptive control of profile errors and accelerations and speed-converting is realized with increasing or descending self-adaptive control strategy. This method meets real-time and high-precision requirements of high speed and precision processing, and solves various problems caused by several variable curvatures of a complicated surface.

Adaptive Self‐Tuning Fuzzy Controller for a Soft Rehabilitation Machine Actuated by Pneumatic Artificial Muscles

Pneumatic artificial muscles (PAMs) have the highest power to weight and power to volume ratios of any actuator. Therefore, they can be used not only in rehabilitation engineering, but also as actuators in robots, including industrial and therapy robots. Because PAMs have highly nonlinear and time‐varying behavior associated with gas compression and the nonlinear elasticity of bladder containers, achieving excellent tracking performance using classical controllers is difficult. An adaptive self‐tuning fuzzy controller (ASTFC) including adaptive fuzzy sliding mode control (AFSMC) and functional approximation (FA) was developed in this study for overcoming the aforementioned problems. The FA technique was used to release the model‐based requirements and the update laws for the coefficients of the Fourier series function parameters were derived using a Lyapunov function to guarantee control system stability. The experimental results verified that the proposed approach can achieve excellent control performance despite external disturbance.

A New Self-Adapting Admission Control Algorithm for Differential Service in Web Clusters

A new admission control algorithm considering the network self-similar access characteristics is proposed. Taking advantage of the mathematical model of the network traffic admission control which can effectively overcome the self-similar characteristics of the network requests, through the scheduling of the differential service qucue based on priority while at the same time taking into account various factors including access characteristics of requests, load information, etc, smoothness of the admission control is ensured by the algorithm proposed in this paper. We design a non-linear self-adapting control algorithm by introducing an exponential admission function, thus overcomes the negative aspects introduced by static threshold parameters. Simulation results show that the scheme proposed in this paper can effectively improve the resource utilization of the clusters, while at the same time protecting the service with high priority. Our simulation results also show that this algorithm can improve system stability and reliability too. Key words Web cluster - admission control - differential service - self-similar - self-adapting CLC number TP 393 Foundation item: Supported by the National Natural Science Foundation of China (10375024) and the Hunan Natural Science Foundation of China(03JJY4054)Biography: LIU An-feng(1971-), male, Ph. D candidate, majoring in network computing, Web QoS.

Adaptive Fuzzy Attitude Control of Flexible Satellite

The adaptive fuzzy control is applied in the attitude stabilization of flexible satellite. The detailed design procedure of the adaptive fuzzy control system is presented. Two T-S models are used as both controller and identifier. The parameters of the controller could be modified according to the information of the identifier. Simulation results show that the method can effectively cope with the uncertainty of flexible satellite by on-line learning and thus posses the good robustness. With the proposed method, the precise attitude control is accomplished.

An Application of a Multivariable Self-Tuning Regulatorto the Control System of a Equipment Spare Parts

A discrete-dine control system model of equipment spare parts is proposed In this model,the stochastic demand, of the spare parts is described by the state equation disturbance. The controlpolicy of the system was deduced by means of the methods of a multivariable self-tuning regulatorand reduced-cud r state observer. An example was given in the end.

Adaptive Fuzzy Control of Constrained Flexible-Link Manipulators

In this paper, a novel adaptive fuzzy control scheme is presented. The controller is constructed by using a table lookup scheme and self tuning techniques, which includes the identification block, the fuzzification, the updating rule base, the defuzzification, and the crisp controller (sub controller), etc. The adaptive fuzzy controller is designed in detail by means of a triangular membership function and the center of gravity method. The control scheme addressed here is implemented to control the motion of the end effector of a two link constrained flexible manipulator. Computer simulation results show that the novel adaptive fuzzy control scheme works quite well.

RESEARCH ON THE ADAPTIVE CONTROL OF DRILLING PROCESS

A self-tuning adaptive controller is presented which is used for the adaptive control (AC) of drlling process. The parameters of the controller can be regulated in-processly by on line system identification, so as to fit the variation of the cutting conditions. This control method has been successfully applied to the adaptive control of drilling process. The experimental results indicate that the controller has the ability to adapt to the variation of the cutting process parameters and is good in performance.

ControlLogix集成控制系统在氯乙酸生产过程中的应用

针对氯乙酸生产过程中氯化工序与结晶工序的特点及其控制系统性能的要求,我们选择了A-B公司的Control-Logix集成控制系统来构成氯乙酸生产过程控制。控制系统由过程控制级与监控管理级构成,形成二级分层体系结构。并在氯化工序中采用了前馈-串级复合控制,在预热水温度中采用了自适应Smith预估补偿控制。

NEW HYDRAULIC ACTUATOR'S POSITION SERVOCONTROL STRATEGY

A new hydraulic actuator-hydraulic muscle （HM） is described, and the actuator＇s features and applications are analyzed, then a position servocontrol system in which HM is main actuator is set up. The mathematical model of the system is built up and several control strategies are discussed. Based on the mathematical model, simulation research and experimental investigation with subsection PID control, neural network self-adaptive PID control and single neuron self-adaptive PID control adopted respectively are carried out, and the results indicate that compared with PID control, neural network self-adaptive PID control and single neuron self-adaptive PID control don＇t need controlled system＇s accurate model and have fast response, high control accuracy and strong robustness, they are very suitable for HM position servo control system.

基于Adaptive Interaction理论的PID控制器的设计及应用

本文在Adaptive Interaction理论的基础上,提出了一种新的自调整 PID 控制器。这种新的控制器根据输入及其误差信号进行在线训练,通过误差评价函数的最小化,在模型未知的情况下能很好地调整比例、积分、微分三个参数。对于被控对象的变化具有鲁棒性,很大程度上解决了传统的 PID 控制器对于非线性、不稳定系统控制效果不佳及在线调整困难的问题。通过仿真实例,验证了应用 Adaptive Interaction 理论的 PID 控制器的有效性和实用性。

一种混合多策略改进的麻雀搜索算法

针对麻雀搜索算法SSA求解目标函数最优解时具有过早收敛、在多峰条件下易陷入局部最优和在高维情况下求解精度不足等问题,提出了一种混合多策略改进的麻雀搜索算法MISSA。考虑到算法初始解的质量很大程度上会影响整个算法的收敛速度与精度,引入精英反向学习策略,扩大算法的搜索区域,提升初始种群的质量和多样性;对步长进行分阶段控制,以提高算法的求解精度;通过在跟随者的位置中加入Circle映射参数与余弦因子,提高算法的遍历性与搜索能力;采用自适应选择机制在麻雀个体位置更新中加入Lévy飞行,增强算法寻优和跳出局部最优的能力。将改进后的算法与麻雀搜索算法及其他算法在13个测试函数上进行对比,并进行Friedman检验。实验结果表明,改进后的麻雀搜索算法能够有效提高寻优精度与收敛速度,并在高维问题中也具备较高的稳定性。

考虑模糊多目标优化的风电场无功电压分区控制

为提升双馈风电场的无功功率补偿和电压稳定能力,提出了一种考虑模糊多目标优化的风电场无功电压分区控制方法。基于有功功率数据对风电场进行分区降维,并计算获得了各分区的无功优化限值;定义了分区无功裕度指标用以描述风电场电压运行的安全裕度,综合考虑运行安全性和稳定性,建立了风电场无功电压的模糊多目标优化模型;提出了一种可大范围全局快速寻优的自适应遗传禁忌算法,通过重新定义交叉与变异概率提升了寻优的全局时效性,通过引入禁忌算法改善了寻优准确性。最后,以某双馈风电场为例进行了仿真验证。结果表明:所提方法能够为风电场预留充足的无功裕度,显著降低系统内部的电压波动。

船舶多源微电网逆变器的下垂控制技术分析与参数设计

船舶多源微电网中逆变器性能对电网运行具有至关重要的作用。下垂控制技术通过调整其输出频率或电压来分配功率,本文对多源微电网中的下垂控制技术进行分析和研究,介绍下垂控制基本原理,阐述船舶多源微电网的基本结构,传统下垂系数调整一般为线性调整,存在超调和响应慢的问题,提出一种基于粒子群优化算法的自适应下垂系数调整方法,并进行仿真分析,结果表明自适应下垂系数调整方法能够实现有功功率的准确分配,并具有较高的实时性。

基于改进虚拟同步发电机的构网型并联储能逆变器控制研究

针对构网型变换器预同步过程时电力系统频率电压稳定性低导致变换器并网失败的问题,提出一种基于改进线性自抗扰控制(LADRC)的构网型变换器预同步控制策略。首先,采用无锁相环(PLL)控制策略,通过相位偏差的反馈控制对网侧电压的相位和幅值进行快速同步追踪,可避免因PLL精度较低和响应速度慢而引起的电力系统稳定性降低的问题。在此基础上,在有功频率支路模块的角频率输出端引入LADRC,这可以有效解决预同步控制过程中变换器输出电压频率存在过冲的问题,从而确保构网型变换器预同步控制顺利进行最终实现成功并网。最后,在MATLAB/Simulink仿真平台中搭建基于改进LADRC的构网型变换器预同步控制模型并进行仿真验证,结果表明所提控制策略可以有效抑制系统频率震荡,并能够加速系统预同步进程,确保构网型变换器安全运行最终实现成功并网,仿真结果验证了所提方法的有效性。