Time-varying performance prediction and system identification of internal combustion engines

Design for life-time performance and proper maintenance measures are usually needed to prolong the mean-time-between-failures of complex equipments such as internal combustion engines. To reach this, it is important to obtain the information of time-varying system performance in design stage and to identify the structural change at each moment. So a multidisciplinary model based method is studied in this paper to unify the time-varying performance(TVP) prediction and system identification(SI) of equipments. The related multidisciplinary model in this paper should be not only precise to give simulation results but also sensitive to the variation of system parameters. So the varying history of system performance along with the structural change can be obtained from the model. Then the value of system parameters can be identified by seeking roots with given detected responding data and relationship between system responding data and system parameters. A case study on a low power gasoline engine shows that the method presented in this paper can provide useful information for the development and maintenance of complex equipments.     

Joint distortion model for progressive image transmission using error correcting arithmetic codes

A novel joint source channel distortion model was proposed, which can essentially estimate the average distortion in progressive image transmission. To improve the precision of the model, the redundancy generated by a forbidden symbol in the arithmetic codes is used to distinguish the quantization distortion and the channel distortion, all the coefficients from the first error one to the end of the sequence are set to be a value within the variance range of the coefficients instead of zero, then the error propagation coming from the entropy coding can be essentially estimated, which is disregarded in the most conventional joint source channel coding （JSCC） systems. The precision of the model in terms of average peak-signal-to-noise has been improved about 0.5 dB compared to classical works. An efficient unequal error protection system based on the model is developed, and can be used in the wireless communication systems.     

Joint Distortion Model for Progressive Image Transmission Using Error Correcting Arithmetic Codes

A novel joint source channel distortion model was proposed, which can essentially estimate the average distortion in progressive image transmission. To improve the precision of the model, the redundancy generated by a forbidden symbol in the arithmetic codes is used to distinguish the quantization distortion and the channel distortion, all the coefficients from the first error one to the end of the sequence are set to be a value within the variance range of the coefficients instead of zero, then the error propagation coming from the entropy coding can be essentially estimated, which is disregarded in the most conventional joint source channel coding (JSCC) systems. The precision of the model in terms of average peak-signal-to-noise has been improved about 0.5 dB compared to classical works. An efficient unequal error protection system based on the model is developed, and can be used in the wireless communication systems.     

Finite-Time Attitude Tracking Control of Spacecraft with Actuator Saturation

The attitude tracking control problem of a rigid spacecraft with actuator saturation is investigated in this paper. A finite-time attitude tracking control scheme is presented by incorporating sliding mode control (SMC) and adaptive technique. Specifically, a novel time-varying sliding mode manifold is first developed that aims at regulating the attitude tracking error to equilibrium point within a certain finite time. Moreover, it can be specified a priori by the designer according to the mission requirement. Subsequently, an adaptive controller is derived by using the SMC in conjunction with adaptive technique. The designed controller is capable of ensuring that the state trajectories reach to sliding regime within a finite time, and hence that attitude tracking error can converge to zero in a finite time with the aid of the developed sliding dynamics, despite the presence of exogenous disturbances, unknown inertia properties and saturation nonlinearities. Finally, the simulation experiments are carried out to demonstrate the effectiveness of the proposed control scheme.     

Robust Fuzzy Sampled-Data Control for Dynamic Positioning Ships

A robust H∞sampled-data stabilization problem for nonlinear dynamic positioning(DP) ships with Takagi-Sugeno(T-S) fuzzy models is discussed in this paper. Input delay approach is used to convert the sampleddata DP ship system to a fuzzy system with time-varying delay. Adequate conditions are derived to determine the system's asymptotical stability and achieve H∞performance via Lyapunov stability theorems. Then, the fuzzy sampled-data controller is obtained by analyzing the stabilization condition. Simulation result shows that the proposed method and the designed controller for a DP ship are effective so that the DP ship can maintain the desired position, heading and velocities in the existence of varying environment disturbances.     

Sliding mode robust fault-tolerant control for uncertain systems with time delay

Considering the modeling uncertainties and external disturbance, a kind of sliding mode robust H∞fault-tolerant control method for time delay system with actuator fault is proposed. The upper-bound of the uncertainties is considered as a known constant, while the upper-bound of the actuator fault is unknown. A sufficient condition for the existence of an integral sliding mode dynamics is given in terms of linear matrix inequality(LMI). A novel adaptive law is given to estimate the unknown upper-bound of faults. On this basis, a type of sliding mode robust H∞fault-tolerant control law is designed to guarantee the asymptotic stability and the H_∞ performance index of the system. Finally, the simulation on quad-rotor semi-physical platform demonstrates the reliability and validity of the method.     

信号联动修正参数计算方法分析

为研究交通信号的自适应控制方法,需要对交叉口延误进行定量的分析与计算,而HCM2000推荐的延误计算模型对于自适应控制的信号交叉口的延误计算有不错的适用性。在此模型中,信号联动修正参数PF能较好的修正由于交叉口进行自适应控制而产生的延误变化。由于HCM2000给出的PF计算方法比较繁杂,计算方法的简化成为一个很好的研究切入点。     

道路交通事故多层递阶预测方法

针对道路交通系统动态时变的特点，用多层递阶预测方法，建立了道路交通事故的多层递阶预测模型．将事故预测分解成对时变参数的预测和在此基础上对道路交通事故未来状态的预测两部分，通过对时变参数的精确预测提高事故预测精度．以1989—1999年我国某省道路交通死亡人数为原始数据建模，模拟结果显示，对2000-2001年的预测结果和实际道路交通死亡人数之间的平均误差为5．8％．     

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本文着重研究应急交通需求时空分布预测方法. 从分析应急交通需求特点入手,在总结现有研究的基础上,提出广义S型行为反应曲线的概念,并紧扣不同集结点的疏散时间要求和反应参数各异的特点,建立了广义S型需求加载曲线模型,同时给出了单位时段疏散百分比的分析方法. 应用上述方法,设计了分时段应急交通OD需求矩阵的求解算法,从而建立应急交通需求时空分布模型. 基于MATLAB软件对模型编程实现,在对给定算例进行应用后,证明模型能够准确刻画不同时刻的各集结点和整个系统的应急需求疏散比例的动态变化,并有效应用于应急交通时变需求分布的预测.     

基于故障阻抗计算的非同步故障测距新方法

为了解决双端电气量测量非同步产生的故障测距误差问题,提出基于故障阻抗计算的非同步故障测距新方法。该方法采用集中参数短线模型,首先利用双端非同步电气量和线路参数计算故障阻抗,然后基于金属性短路故障阻抗的纯电阻性采用共轭法构造出关于故障距离的一元二次方程,最后求解并判别伪根得到真实故障距离。双端量法测距在原理上克服了故障电阻和系统运行方式变化的影响。仿真与数值计算结果表明提出的新方法可靠有效,能消去非同步角的影响,具有良好的测距精度,适用于各种金属性短路故障类型,工程实际应用价值高。     

磨合的模型及其系统分析方法

本文提出了一种磨合的模型,该模型能反映磨合过程的非线性和时变 特征,以及实际的磨合趋势。同时给出了用于磨合系统研完的系统分析 方法。      

基于多质点动车组制动模型的动态牵引负荷

针对单质点模型不足以准确描述动车组制动情况的问题,根据多质点动车模型的制动力分配,建立了动车多质点制动模型.推导出多质点模型在制动工况下的基本阻力和附加阻力以及推算出牵引网侧时变功率,对多质点模型动车组在平直轨道、有坡道和弯道情况下进行制动过程仿真.通过仿真结果与动车制动实测数据的比较,其距离误差小于50 m,验证了多质点模型的准确性.      

多半径误差修正自适应布谷鸟优化DV-HOP定位算法

针对WSN节点定位中非测距DV-HOP算法存在较大定位误差,提出了一种多通信半径误差修正自适应布谷鸟优化DV-HOP定位算法（MEACS-D）. 采用锚节点多通信半径广播消息,在跳数计数时将跳数小数化,以减小跳数长短不一造成的误差;再用虚拟相交圆几何方法计算1跳内节点与锚节的距离;通过在未知节点选择平均跳距时,加入各个锚节点权重进行计算来减少平均跳距误差;另引入可自适应搜索步长的布谷鸟算法代替极大似然估计法来定位节点坐标,以提高定位精度. 通过仿真,在不同锚节点、通信半径、总节点条件下MEACS-D算法较DV-HOP算法和原布谷鸟DV-HOP算法（CS-D）算法定位误差平均下降39.7%、10.6%,证明MEACS-D算法能有效减少定位误差.      

直接数字频率合成的杂散信号分析

介绍了直接数字频率合成技术以及分析其杂散误差,对相位截断误差和幅度量化误差进行了傅立叶级数分析研究。文章最后还简单介绍了几种改善杂散误差的方法。     

驾驶技能与追尾事故关系的仿真研究

驾驶员驾驶水平与追尾事故发生有着密切的关系.本文以交通流仿真模型中的优化速度模型为基础,考虑驾驶员的反应时间与操作失误率两方面因素,建立了一种追尾事故的微观仿真模型.随后针对由两台车辆组成的场景,通过仿真实验研究了车速、车距及驾驶技能对追尾事故发生率的影响.仿真结果表明,依据车速保持合理距离是防止事故发生最有效的手段,而反应延迟与操作失误率对事故发生都有影响,并具有不同的影响程度与影响形式,同时给出了对驾驶员驾驶水平要求的一些建议.本文结果对于人因交通事故机理研究及人因交通事故的预防有一定参考价值.     

A New MPEG-2 Rate Control Method Based on Model Classification

The paper proposed a new MPEG-2 rate control method that is based on model classification. The macro-blocks are classified according to their prediction errors, and different parameters are used in the rate-quantization and distortion quantization model. The different model parameters are calculated from the previous frame of the same type in the process of coding. These models are used to estimate the relations among rate, distortion and quantization of the current frame. Further steps, such as R-D optimization based quantization adjustment and smoothing of quantization of adjacent macroblocks, are used to improve the quality. The results of the experiments prove that the technique is effective and can be realized easily. The method presented in the paper can be a good way for MPEG rate control.     

考虑混合交通的两车道城镇道路养护优化研究

为了研究适合中国城镇道路混合交通特点的道路养护优化策略,在总结已有研究的基础上,改进了机动车延误计算模型,提出了包括养护费用、机动车延误损失、非机动车延误损失和交通事故损失在内的总耗费目标函数.通过求解该函数的最小值来确定最优作业区长度及养护作业起始时间.利用"试错法"对模型进行了求解,并通过算例进行了分析.结果显示,养护作业区长度和作业起始时间是制定养护策略的关键因素,在养护路段长度一定的情况下,通过合理设定作业区长度和起始时间可使总耗费最省.     

不确定强对流天气下动态改航路径规划

为了解决对流云团状态不确定条件下的改航路径规划问题,利用云团预测状态的不确定性测度和外推位置随机误差建立多雷暴云团的状态转移矩阵,用于预测改航路径规划网络的时变阻滞状态.以期望改航代价最小为优化目标,以航段连续性和最大穿越风险代价为约束条件,建立了动态改航路径规划模型.针对确定性和不确定性两种天气场景的16种初始状态,采用遗传算法对模型进行求解,结果表明,通过预测云团状态的不确定变化,改航路径能策略性地选择穿越初始状态不可航云团或绕飞初始状态可航云团.与确定性改航策略相比,绕飞距离减少了40%,穿越云团次数减少了30.8%,改航路径的安全性和经济性均得到有效改善.     

带时变时滞细胞神经网络的全局渐近稳定性

研究了带时变时滞的细胞神经网络的全局渐近稳定性问题,给出了带时变时滞细胞神经网络平衡点全局渐近稳定的新充分判定准则。首先,提出所研究的时滞细胞神经网络模型、系统激活函数所需满足的条件及需要的引理。然后,将所研究的系统通过一个等式进行线性变换,在定义一个与系统相关的映射操作基础上,基于Lya-punov-Krasovskii稳定性定理和线性矩阵不等式技术来讨论时滞细胞神经网络的全局渐近稳定性。所得条件是时滞相关的。最后,用一个数值例子验证所得的稳定性条件是有效的。