A design method for a self-tuning regulator for a distributed-parameter system

A design method for a self-tuning regulator for a distributed-parameter system is presented. This system is assumed to have some actuators fixed in the spatial domain. The power of each actuator is estimated by a least-squares algorithm. Some numerical examples are given.     

A self-tuning regulator for distributed parameter systems

The control of distributed parameter systems with constant, but unknown parameters is considered. A weighted average of the distributed output on the spatial domain is defined as a new variable and is used to generate the control. The parameters of the model are estimated using recursive least squares estimation. The control is obtained using a minimum variance strategy based on the estimated parameters. Distributed disturbances and measurement noise are allowed to be present. Measurements at a finite number of points in the spatial domain are used in obtaining a discrete-time model. From the simulation of a one-sided heating diffusion process the self-tuning regulator is shown to have attractive characteristics and hence can be recommended for practical on-line control of distributed parameter systems.     

基于参数自整定和模糊前馈的疏浚系统控制

在疏浚工程中抽砂系统一般采用PID控制器调节泥浆浓度,但当河床形态及河水流速等工况变化时,基于固定参数的PID控制难以达到满意效果。针对被控对象的特性,提出将参数模糊自整定PID与模糊前馈结合的控制方案。该方案能根据工况变化动态调节PID参数,并根据龙头吸咀与河底距离提供前馈补偿,能及时抑制吸咀位置对泥浆浓度灵敏度的影响。仿真结果表明,与传统PID控制相比,该方案对不同工况均能表现出较低的超调量,更快的响应速度,以及更强的抗干扰能力和稳定性。     

Modelling for an expert system and a parameter validation method

A model–based engineering diagnostic method is typically based on the evaluation of the residuals generated from a comparison of important variable values from a simulated system and the corresponding measured values from the system's performance. Consequently, a model should describe the dynamic behaviour of the system as accurately as possible using suitably selected parameter values. This implies the need for validation of the performance of the model by comparison with the measurements of the actual system. This process is especially important when the detection of faults is performed in real–time conditions. In this paper, the modelling process for hydraulic systems as well as a new parameter validation method that has been developed using the DASYLab data acquisition and control software for the estimation of the uncertain parameter values of the model is presented. This model validation process led to the establishment of a model–based expert system that is able to diagnose real–time faults working in parallel with actual dynamic industrial automated processes.     

基于工程化参数优化的遥测伺服系统仿真分析

针对试凑法研制的XX设备的天线伺服系统无法得到最优化的PID参数情况,研究该设备伺服系统的PID参数优化。首先从设备原始资料及说明书着手,分析设备的组成原理、各元器件的性能以及天线伺服系统指定角度跟踪的机理,其次查阅相关资料,分析该系统关键部件的传递函数模型从而建模整套天线伺服系统,从系统的三环结构依次按照工程化设计的原则对天线伺服系统的参数进行理论优化,最后,采用Matlab/Simulink软件对优化后的整套伺服系统进行仿真分析。仿真分析结果表明采用工程设计优化后参数其总体天线伺服系统的阶跃动态响应性能相比于当前天线的伺服系统性能更佳。该方法从理论上对天线伺服系统的控制性能优化提出了一定的指导作用,对设备到的优化和性能提升提供了一定的实用价值。     

用模糊控制自整定PID参数的研究

针对复杂的非线性时变系统,研究了将模糊系统与普通PID相结合的自适应模糊PID控制系统,总结了该控制器的设计过程及设计方法。仿真结果表明,这种控制器是一种易于理解、便于实现、性能良好的控制器,能适用于非线性、时变、较强干扰的复杂系统。     

Health parameter monitoring via a novel wireless system

This study develops a novel remote healthcare system based on Wireless Sensors Network System (WSNs) and Radio Frequency Identification (RFID) technologies. Cloud equipment is used as sensing cloud architecture to create the system database, and Improved Particle Swarm Optimization (IPSO) is applied to build a personal physiological signal sensing system. The collected personal physiological signals are analyzed, and RFID technology is used to create an administrator identity and database. The integrated physiological instrument measures/monitors blood pressure, heart rate, blood oxygen content, body weight, BMI and cardiogram. This system can be applied to, say, employees, nursing-home residents and the elderly. Physiological changes are identified at any time via a self-health examination, promoting early diagnosis and treatment. The current ZigBee technology, which has many advantages, is used in medical institutions, industry, and agriculture, and for automated control and building monitoring. This study uses WSNs technology to transfer physiological data to the cloud for analysis, processing, and storage. The client-side and appropriate medical personnel are notified by e-mail and short messages via the Internet, such that they can provide timely diagnosis and deploy treatment. The IPSO scheme is used to increase the efficiency and accuracy when searching for at-risk groups, searching data, and defining and summing the weights of physiological data. If the first 10% of users with high weight values are a risky population that must be treated immediately, this system informs medical personnel immediately, potentially improving medical service quality and application of medical resources.     

A novel approach to robust parameter estimation using neurofuzzy systems

A novel approach for solving robust parameter estimation problems is presented for processes with unknown-but-bounded errors and uncertainties. An artificial neural network is developed to calculate a membership set for model parameters. Techniques of fuzzy logic control lead the network to its equilibrium points. Simulated examples are presented as an illustration of the proposed technique. The result represent a significant improvement over previously proposed methods.     

一种运动模糊图像的模糊参数估计方法

在摄取图像的过程中,物体间的高速运动及景物与成像设备的相对运动是引发图像退化的主要原因之一,称之为运动模糊。模糊长度和模糊方向是运动模糊中影响图像模糊程度的主要参数。提出了一种改进的误差参数分析方法,对模糊长度进行估计并比较了不同的复原方法对参数误差曲线法估计的效果,同时提出运用傅里叶分解和Hough变换从模糊图像的频谱特性上对运动模糊方向进行了估计。实验结果表明,所提出的方法对运动模糊图像的复原有良好的效果。     

图书馆机器人机械手参数自整定模糊PID控制器设计

采用PC/104系列板卡设计了一款嵌入式图书馆机器人气动机械手控制器,对机械手的参数自整定模糊PID控制算法进行了重点探讨,根据模糊子集的隶属度赋值表和模糊逻辑规则,查模糊矩阵表得出修正参数,完成对PID参数的在线自校正.用Microsoft eMbedded Visual C++(EVC)编程实现了图书取放气动机械手的智能控制,给出了控制软件算法流程及关键部分实现方法.用阶跃、正弦等典型输入信号做系统仿真,实验结果表明气动机械手能够快速、稳定、几乎无误差地跟踪系统给定值.所提出的系统设计方法对类似领域具有普遍适用性.     

A novel approach in parameter adaptation and diversity maintenance for genetic algorithms

In this paper, we propose a probabilistic rule-driven adaptive model (PRAM) for parameter adaptation and a repelling approach for diversity maintenance in genetic algorithms. PRAM uses three parameter values and a set of greedy rules to adapt the value of the control parameters automatically. The repelling algorithm is proposed to maintain the population diversity. It modifies the fitness value to increase the survival opportunity of chromosomes with rare alleles. The computation overheads of repelling are reduced by the lazy repelling algorithm, which decreases the frequency of the diversity fitness evaluations. From experiments with commonly used benchmark functions, it is found that the PRAM and repelling techniques outperform other approaches on both solution quality and efficiency.     

混沌背景中微弱信号参数估计新方法

本文提出一种基于单向耦合同步的混沌背景中谐波频率估计的新方法。该方法把混沌背景中的谐波频率估计问题转变为同步误差中的谐波频率估计问题,改善了信噪比,在混沌背景中存在强随机噪声情况下,仍能估计出谐波信号频率。仿真实验表明,该方法简单有效,计算量小,且估计效果要优于RBF神经网络方法。     

A novel method for real parameter optimization based on Gene Expression Programming

Gene Expression Programming (GEP) is a new technique of evolutionary algorithm that implements genome/phoneme representation in computing programs. Due to its power in global search, it is widely applied in symbolic regression. However, little work has been done to apply it to real parameter optimization yet. This paper proposes a real parameter optimization method named Uniform-Constants based GEP (UC-GEP). In UC-GEP, the constant domain directly participates in the evolution. Our research conducted extensive experiments over nine benchmark functions from the IEEE Congress on Evolutionary Computation 2005 and compared the results to three other algorithms namely Meta-Constants based GEP (MC-GEP), Meta-Uniform-Constants based GEP (MUC-GEP), and the Floating Point Genetic Algorithm (FP-GA). For simplicity, all GEP methods adopt a one-tier index gene structure. The results demonstrate the optimal performance of our UC-GEP in solving multimodal problems and show that at least one GEP method outperforms FP-GA on all test functions with higher computational complexity.     

基于TMS320F28335的永磁同步交流伺服电机矢量控制系统设计

介绍了永磁同步交流伺服电机的矢量控制理论,并根据矢量控制理论采用TMS320F28335实现了对永磁同步交流伺服电机的电流、速度和位置的三闭环控制,最后给出实验结果及其分析。     

一种基于小生境遗传算法的迟滞非线性系统参数识别方法

工程中存在着大量的具有迟滞非线性恢复力的结构与构件,但迟滞非线性系统既是非线性的,又是非解析的,造成其参数识别十分困难,阻碍了迟滞非线性模型在工程中的应用．本文提出了一种基于小生境遗传算法的迟滞非线性系统参数识别方法,该方法在遗传算法中引入了新的参数——个体活动半径．利用本算法对一木结构剪力墙的BW模型参数进行识别,识别结果误差较小,验证了算法的有效性。     

A novel communication system approach for a Smart City based on the human nervous system

The massive introduction of internet, architect of the Internet of Thingsparadigm, was expected to facilitate the spread of people out of the urban spaces. However, the reality is that increasingly people are moving to cities, which generates many challenges for the cities of tomorrow. In this context, the Smart Cityconcept emerges, where Information and Communication Technologies have a key role. This situation has revealed an important issue that needs to be addressed: the lack of an ubiquitous communication architecture able to deal with the expected requirements of a SC. To this end, a wide review of the existing communication frameworks and city services have been performed, which showed that existing proposals are classical fixed ad-hocsolutions for very specific problems with no resilience and common thread. By rethinking the nature of cities and considering them as living organisms, it is possible to relate the nervous systems with the communication architecture of a city. Therefore, this work proposes a novel communication architecture, ubiquitous and resilient, inspired in the human nervous system by the definition of Smart Gateways, able to satisfy the needs of a real SCand adaptable to the growing and specific requirements of every single city. Additionally, the research also includes the simulation of the communication channel with different technologies.     

摩擦非线性伺服系统辨识建模方法研究

针对伺服控制设计时系统精确建模的重要性,提出了一种主要针对受摩擦非线性影响的系统建模方法,即通过在辨识输入信号中叠加摩擦补偿来抵消摩擦的影响,从而实现对非线性系统的线性化处理的建模方法。并通过模型验证实验,证明经过这种处理方法得到的模型准确化程度很高。     

A self-tuning PID control for a class of nonlinear systems based on the Lyapunov approach

In this paper, we will propose a self-tuning method for a class of nonlinear PID control systems based on Lyapunov approach. The three PID control gains are adjustable parameters and will be updated online with a stable adaptation mechanism such that the PID control law tracks certain feedback linearization control, which is previously designed. The stability of closed-loop nonlinear PID control system is analyzed and guaranteed by introducing a supervisory control and a modified adaptation law with projection. Finally, a tracking control of an inverted pendulum system is illustrated to demonstrate the control performance by using the proposed method.