基于多边形边界约简的启发式在线时间序列表示算法

提出了一种新颖的可在线计算的时间序列启发式算法。算法具有多边形约简算法相同的优良的近似质量，并可在固定数据缓冲区空间内在线运算。用启发式搜索方法自动获取最佳分段数。在随机时间序列上仿真试验证明算法有很高的逼近质量和较低的计算复杂性。

基于多边形边界约简的在线时序表示算法

时间序列是一类重要的复杂数据类型。首先分析了Douglas-Peucker和多边形约简时序表示算法。然后借鉴滑动窗口思想,提出了基于多边形边界约简的启发式在线时间序列表示算法。该算法具有多边形约简算法很好的近似质量,同时可以在固定数据缓冲空间内在线运算。此外,根据最大允许误差,算法用启发式搜索方法自动获取最佳分段数。在随机时间序列上仿真试验证明算法有很高的逼近质量和较低的计算复杂性。

Direct fractional order MRAC adaptive control design for a class of fractional order commensurate linear systems

In this paper,we introduce a direct fractional order adaptive control design based on model reference adaptive control(MRAC)structure for a class of commensurate fractional order linear systems with an arbitrary relative degree,and whose parameters are unknown.By generalising the application of standard direct MRAC strategy to plants described by fractional order models,we develop a fractional adaptive control scheme(FOMRAC)based on the output feedback.We also define an adaptation control law ensuring the stability of the closed-loop system and the good tracking of the reference trajectory.The asymptotic stability of the fractional order control system is proven using an extension of the Lyapunov theorem.Simulation results show the effectiveness of the proposed control method even for plants with model parametric variations and additive noises.