改进的广义预测控制算法在热力站控制中的应用

在集中供暖的热力站控制系统中,由于被控对象本身具有非线性、纯滞后、参数时变等特点,常规的PID控制器难以达到理想的温度控制效果.结合广义预测控制的优点,本文提出了一种基于遗忘因子递推增广最小二乘法的广义预测控制的算法.首先介绍了该算法的原理和控制器的设计方法,然后在系统参数突变的情况下进行了仿真研究.仿真结果表明该算法具有动态响应快、超调量小,稳态精度高的特点,而且稳定性和鲁棒性良好,适用于参数变化的大滞后热力站控制系统.     

一种广义预测自适应控制算法

广义预测控制是一种基于被控对象参数模型的控制算法,适用于复杂的、数学模型难以精确建立的控制系统。现研究了该算法,并对一个被控对象模型进行了仿真。结果表明,广义预测控制算法响应速度快,无超调,控制效果理想。     

认知雷达转向控制系统优化设计研究

神经网络是一种模仿动物神经网络行为特征，进行分布式并行信息处理的算法数学模型。为了能更好地实现对认知雷达转向系统的精确控制，文中将神经网络的概念引入到认知雷达转向控制系统中，提出一种基于神经网络的认知雷达转向控制系统。首先介绍了神经网络的模型算法，然后基于此，对雷达转向系统进行跟踪仿真，进而得到预计的转向控制系统的输入量。最后，结合模型预测控制算法，对转向系统的角度和速度进行精确控制。为了验证理论分析结果，基于MATLAB搭建了认知雷达转向控制系统的仿真模型并进行仿真验证，结果表明，所提出的方法能够对转向系统的角度和速度进行精确控制，转矩脉动减小了56%,超调量减小了61%。     

神经网络预测控制在车辆横向半主动悬挂控制中的应用设计

结合神经网络和预测控制的优点,提出了一种神经网络模型预测控制算法。给出了将该算法应用到车辆荷香半主动悬挂控制系统中的应用设计方法。仿真实验表明,该控制算法具有良好的控制效果并能适应被控对象参数的变化,同时具有较强的鲁棒性和稳定性。     

基于灰色模型的网络控制系统预测函数算法研究

网络控制系统存在不确定性的时间迟延和数据丢包,可视作具有随机干扰和参数时变的灰色系统.将广义被控对象建模为灰色系统模型,在此模型基础上设计了预测函数控制算法,推导出模型预测输出和控制量计算方程的求解;设计了控制器采用事件-时间混合驱动方式,传感器和执行器采用时间驱动方式的网络控制系统仿真平台.仿真结果表明该算法在线计算量小、抗干扰能力强,跟踪速度快、控制效果良好.     

旋转导向钻井稳定平台前馈模糊算法研究

稳定平台控制系统是调制式旋转导向钻井系统的关键,提出采用前馈模糊算法实现对稳定平台的控制,设计的二维模糊控制器可确定模糊变量的隶属度函数及控制规则,并利用MATLAB软件进行仿真。仿真试验表明稳定平台前馈模糊控制系统在钻井参数较大范围内变化,参数扰动及负载扰动都具有良好的稳定性、自适应性、鲁棒性和抗干扰能力。     

旋转导向钻井稳定平台前馈模糊算法研究

稳定平台控制系统是调制式旋转导向钻井系统的关键,提出采用前馈模糊算法实现对稳定平台的控制,设计的二维模糊控制器可确定模糊变量的隶属度函数及控制规则,并利用MATLAB软件进行仿真.仿真试验表明稳定平台前馈模糊控制系统在钻井参数较大范围内变化,参数扰动及负载扰动都具有良好的稳定性、自适应性、鲁棒性和抗干扰能力.     

基于蚁群算法优化自抗扰控制器的机器人控制

研究基于线性自抗扰控制器的机器人无标定手眼协调控制,搭建了控制系统的Simulink模型,为解决控制器的参数整定问题,选择并编写了蚁群算法的MATLAB程序,通过代码与模型相结合的仿真实验,实现了六自由度机器人对运动目标的跟踪控制,仿真结果验证了算法的可行性和有效性。     

基于模糊免疫PID的时滞网络自适应主动队列管理

提出了一种基于灰预测和模糊免疫PID控制的时滞网络自适应主动队列管理（AQM）算法FIGAPID，旨在增强AQM算法动态自适应能力，同时补偿网络时滞，综合提高AQM算法性能。该算法借助免疫反馈机理进行PID参数的在线自适应调整，采用模糊非线性逼近的方法进行免疫反馈函数的确定；采用等维新息滚动灰预测实现路由器队列长度的超前预测，补偿AQM控制的反馈滞后。对比传统PID算法，仿真验证了FIGAPID的有效性，表明算法能快速稳定地适应动态时滞网络环境变化，收敛于路由器队列长度期望值，同时具有较小的数据丢包率。     

交互式多模型算法在光电跟踪控制系统中应用的仿真

分析目标运动参数滤波算法在光电跟踪控制系统中的作用,在交互式多模型算法的基础上,提出了该算法在光电跟踪控制系统中的应用问题,并建立了在光电跟踪控制系统中使用的仿真模型,通过仿真环境下光电跟踪控制系统对不同目标跟踪的数据分析可知,该算法可作为光电跟踪控制系统中复合控制前馈数据的获取算法使用,光电跟踪控制系统采用交互式多模型算法比采用--滤波算法更适合对机动目标的跟踪。     

Characterizing Temporal SNR Variation in 802.11 Networks

The analysis and design of wireless medium access control (MAC) protocols, coding schemes, and transmission algorithms can significantly benefit from an understanding of the channel quality variation. We attempt to represent channel quality variation using a finite-state birth–death Markov model. We outline a method to compute the parameters of the model based on measured traces obtained using common wireless chipsets. Using this Markov chain, we statistically evaluate the performance based on the channel quality, long-term correlations, and burst length distributions. Such a model significantly performs better than a traditional two-state Markov chain in characterizing 802.11 networks while maintaining the simplicity of a birth–death model. We interpret the variation of the model parameters across different locations and different times. A finite-state stationary model is amenable to analysis and can substantially benefit the design of efficient algorithms and make simulations for wireless network protocols faster.      

Modal analysis of board-level electronic package

The reliability of board-level electronic package subjected to drop impact is one of the most concerned issues. After drop impact, the Printed Circuit Board (PCB) experiences free vibration which leads to the deformation of PCB, hence the failure of solder joints. The free vibration is dependent on the inherent parameters of PCB. So it is necessary to study the inherent parameters of board-level package. Modal analysis is a common way to characterize the inherent dynamic parameters of a system. By modal analysis, we can understand the inherent vibration features of board-level package system. In this paper, the theoretical vibration model of the JEDEC standard PCB assembled with three Chip Size Packages (CSPs) is performed. Then the results of theoretical analysis are validated by that of finite element analysis (FEA) and modal test. A series of modal parameters are obtained during the modal analysis such as the mode shapes, the natural frequencies and the damping ratios. These parameters are useful for studying the dynamic response of PCB and the strain rate of solder joints during drop test. The Modal Assurance Criterion (MAC) value is used to validate the correlation between two modal shapes obtained from two different modal parameters estimation methods during modal analysis. The MAC value is computed for the first two order mode shapes, indicating the high correlation between the experimental and predicted (including theoretical and FE results) mode shapes.     

Recursive parameter identification of constrained systems: anapplication to electrically stimulated muscle

In the application of real-time identification methods for diagnosis or adaptive control of biomedical systems, there is often known model information that is ignored. Constraints on the allowable values of parameters, which may be based on physical considerations, are often neglected because the information does "fit" easily into commonly used parameter-identification algorithms. In this paper a method of incorporating constraints on model parameters is developed. This method is applicable to most recursive parameter-identification algorithms. It enforces linear equality constraints on identified parameters. The use of this method for the real-time identification of autoregressive moving-average-type time series models, subject to parameter constraints, is described in detail. These constraints may be time varying. At each time step, the parameter estimate obtained by a recursive least squares estimator is orthogonally projected onto the constraint surface. This simple idea, when appropriately executed, enhances the output prediction accuracy of estimated parameters. Using constraint information in this way is important when we do not wish to destroy a "natural" parameterization of the model (by an initial projection to incorporate equality constraints), or when we cannot use a single initial model simplification (because the constraints are time varying or involve inputs and outputs). Because it improves output prediction at future times, this method is advantageous for use in predictive adaptive controllers. The use of this algorithm is demonstrated in the identification of electrically stimulated quadriceps muscles in paraplegic human subjects, using percutaneous intramuscular electrodes. The nonlinear steady-state force versus pulsewidth recruitment characteristic of the electrode-muscle system is identified simultaneously with the input-output muscle response dynamics, using a Hammerstein-type model. Knowledge of the recruitment curve's shape is translated into constraints on the identified parameters. This information improves the experimental predictive quality of the identified model.     

Performance of autonomous dynamic channel assignment and powercontrol for TDMA/FDMA wireless access

We combine autonomous algorithms for dynamic channel assignment (DCA) and power control in a TDMA/FDMA wireless system as a medium access control (MAC) protocol. The DCA algorithm determines paired radio channels that experience the least interference and are least likely to cause interference. The power control algorithm uses local estimations of signal to interference ratio (SIR) at a receiver to iteratively command power adjustment on the desired transmitter. A common control frequency, which is frame-synchronized among base stations, provides all necessary information for DCA without blind slots. Computer simulations are used to evaluate system performance. Results from computer simulations demonstrate good spectrum efficiency and robustness. Although studied under a specific set of parameters, this type of MAC protocol can be applied in different wireless communications environments     

使用带外信令的CDMA媒体接入算法延时性能分析

分析使用带外信令的 CDMA 无线网络 MAC 算法的性能。在文献中,对 CDMA 带外 MAC 算法的性能分析工作一般通过计算机仿真进行,或者通过均衡点分析法(EPA)得到性能指标的一阶矩。文章将假设用户有思考过程,为系统建立了 Markov 模型,然后通过概率计算得到延时概率分布的完整解析表达式,从而可以得到延时性能的各阶矩。最后给出的仿真结果表明,文章的建模和分析方法是正确的。     

Automated simplified analysis of analogue circuit behaviour based on fully symbolic relations between parameters

Symbolic circuit analysis provides the key for understanding the mechanisms underneath circuit operation, and it can be used to obtain predictive models of circuit behaviour. Symbolic analysis has many applications in the design of analogue circuits but is severely limited by the size of the resulting expressions. Thus an efficient approximation strategy is required for successful symbolic analysis of large analogue circuits. A fully symbolic procedure for the simplification of large expressions, which mimics the heuristic procedures followed by an experienced designer (based on the relations between the parameters of the circuit), is presented in this paper. This simplification strategy is particularly well suited to be combined with some circuit level partition algorithms, leading to a blend between simplification after generation (SAG) and simplification during generation (SDG). The algorithms have been implemented and integrated on a prototype software package for the automated analysis and design of analogue circuits.     

Scheduling in Optical WDM Networks Using Hidden Markov Chain Based Traffic Prediction

This paper presents the design and performance analysis of a predictor-based scheduling algorithm for optical wavelength division multiplexed (WDM) networks. WDM technology provides multiple, simultaneous and independent gigabit-per-second channels on a single fiber. A reservation-based multiple access control (MAC) protocol is considered here for a local area WDM network based on the passive star topology. The MAC protocol schedules reservation requests from the network nodes on the multiple channels. In previous work, we have presented an on-line scheduling algorithm for such a network. We have shown earlier that schedule computation time can significantly affect performance and the scheduling algorithms should be simple for better performance. In this work, we further improve system performance by using a hidden Markov chain based prediction algorithm. The objective here is to reduce the amount of time spent in computing the schedule by predicting traffic requests. Performance analysis based on discrete-event simulation, varying parameters such as number of nodes and channels is presented. The results show that the error of prediction is reasonable for most cases: more than 70% of the time, the error between actual request and predicted request is less than 20%. Network throughput is higher with the proposed prediction algorithm due to pipelining of schedule computation.     

Cross-layer analysis of protocol delay in mobile devices receiving BCMCS

Broadcast and multicast services allow the high-speed delivery of multimedia content to multiple subscribers over CDMA2000 wireless networks. This relies on a high-rate broadcast packet data system with an air interface governed by two interacting protocols: the medium access control (MAC) protocol specifies the methods of multiplexing and of forward error correction used to reduce the radio link error-rate seen by the higher layers; and the security protocol specifies the procedures used to encrypt and decrypt content, following the Advanced Encryption Standard. We investigated the mutual effect of these protocols, in the context of an ARM9-based mobile platform, and their influence on delay. This allowed us to propose a novel analytic model that can predict the total delay by summing the separate but related delays incurred by implementations of the MAC and security protocols with particular parameters. This cross-layer model includes the characteristics of error control in the MAC layer and the varying condition of the fading channel in the physical layer. We can use this model to estimate the size of data buffers that mobiles require to provide a seamless multimedia service.     

Model predictive controller design for boost DC–DC converter using T–S fuzzy cost function

This paper proposes a Takagi–Sugeno (T–S) fuzzy method to select cost function weights of finite control set model predictive DC–DC converter control algorithms. The proposed method updates the cost function weights at every sample time by using T–S type fuzzy rules derived from the common optimal control engineering knowledge that a state or input variable with an excessively large magnitude can be penalised by increasing the weight corresponding to the variable. The best control input is determined via the online optimisation of the T–S fuzzy cost function for all the possible control input sequences. This paper implements the proposed model predictive control algorithm in real time on a Texas Instruments TMS320F28335 floating-point Digital Signal Processor (DSP). Some experimental results are given to illuminate the practicality and effectiveness of the proposed control system under several operating conditions. The results verify that our method can yield not only good transient and steady-state responses (fast recovery time, small overshoot, zero steady-state error, etc.) but also insensitiveness to abrupt load or input voltage parameter variations.     

Supporting service differentiation in wireless packet networksusing distributed control

This paper investigates differentiated services in wireless packet networks using a fully distributed approach that supports service differentiation, radio monitoring, and admission control. While our proposal is generally applicable to distributed wireless access schemes, we design, implement, and evaluate our framework within the context of existing wireless technology. Service differentiation is based on the IEEE 802.11 distributed coordination function (DCF) originally designed to support best-effort data services. We analyze the delay experienced by a mobile host implementing the IEEE 802.11 DCF and derive a closed-form formula. We then extend the DCF to provide service differentiation for delay-sensitive and best-effort traffic based on the results from the analysis. Two distributed estimation algorithms are proposed. These algorithms are evaluated using simulation, analysis, and experimentation. A virtual MAC (VMAC) algorithm passively monitors the radio channel and estimates locally achievable service levels. The VMAC estimates key MAC level statistics related to service quality such as delay, delay variation, packet collision, and packet loss. We show the efficiency of the VMAC algorithm through simulation and consider significantly overlapping cells and highly bursty traffic mixes. In addition, we implement and evaluate the VMAC in an experimental differentiated services wireless testbed. A virtual source (VS) algorithm utilizes the VMAC to estimate application-level service quality. The VS allows application parameters to be tuned in response to dynamic channel conditions based on “virtual delay curves.” We demonstrate through simulation that when these distributed victual algorithms are applied to the admission control of the radio channel then a globally stable state can be maintained without the need for complex centralized radio resource management