基于遗传算法的连续系统模型辨识

系统辨识是控制系统设计的基础,传统的系统辨识大都是对离散数学模型的参数估计,发展了以最小二乘法为基础的理论和方法．而连续模型则需经过离散模型的转换方可得到．作者基于遗传算法和系统仿真技术,建立了输出端噪声存在的连续系统模型辨识方法．遗传算法是建立在自然遗传学机理上的参数搜索方法,但常规的遗传算法具有收敛速度慢,因封闭竞争易导致“早熟”等缺点,为此,通过引入自适应适值函数和动态变异因子,采用精英保护策略,加速了寻优过程,改善了遗传算法的全局搜索及局部寻优能力,为连续系统模型辨识提供了新的途径．     

汽车起重机变幅系统机液耦合动力学建模

用键合图法建立了汽车起重机变幅系统下降工况机液耦合动力学模型,用Matlab对模型进行了仿真,分析了变幅液压回路参数、变幅机构参数对系统的影响以及机械和液压系统的耦合效应．该方法对汽车起重机变幅系统的工程设计提供了理论依据,同时也对工程机械系统的动态特性研究有一定的指导意义．     

基于机械吸振原理的多自由度薄板振动式脉动衰减器滤波特性

为了解决液压系统中由于压力脉动而引起的振动和噪声问题,提出一种多自由度薄板振动式脉动衰减器结构,其作用机理类似于有阻尼的结构共振式吸振器,以载流弹性薄板为共振体,代替结构振动式液压脉动衰减器的振动质量块,减小脉动衰减器的质量和体积,设计不同半径的弹性薄板可以方便调节脉动衰减器的共振频率,从而达到广谱滤波。将机械吸振原理应用到液压脉动衰减器的设计中,分析载流弹性薄板的固有特性,根据分析结果,完成脉动衰减器物理样机的制作,并进行实验研究。研究结果表明:该脉动衰减器结构简单、体积小,而且在较宽频带内都有较好的滤波效果。     

Identification of linear continuous-time system using wavelet modulating filters

An approach to identification of linear continuous-time system is studied with modulating functions. Based on wavelet analysis theory, the multi-resolution modulating functions are designed, and the corresponding filters have been analyzed. Using linear modulating filters, we can obtain an identification model that is parameterized directly in continuous-time model parameters. By applying the results from discrete-time model identification to the obtained identification model, a continuous-time estimation method is developed. Considering the accuracy of parameter estimates, an instrumental variable (Ⅳ) method is proposed, and the design of modulating integral filter is discussed. The relationship between the accuracy of identification and the parameter of modulating filter is investigated, and some points about designing Gaussian wavelet modulating function are outlined. Finally, a simulation study is also included to verify the theoretical results.