电加热器温度仿人智能多模型控制

Human-simulated Intelligent Multi-model Control of Electric Heater

对于实验室电加热器温度一类具有大范围工况、非线性和大惯性特性的对象,用单一模型无法准确描述模型特征,影响控制精度;采用常规控制策略无法解决响应快速性与系统稳定性的矛盾。针对上述问题,利用MATLAB辨识工具箱分别在大幅升温、大幅降温、小幅升温、小幅降温四种工况下对模型参数进行辨识,得到对象模型集;根据仿人智能思想将控制分为"全压加速-零制动-稳态调节"三个阶段,各控制阶段根据对象特性选取相应模型,并利用辨识模型获得控制器参数和切换点,在稳态调节阶段针对升温和降温的正反模型特性引入多模型加权控制方法。在加热器装置上实验的结果表明,该方法控制精度高,系统响应速度和稳定性都有了很大提升。

The temperature of laboratory furnace device is a plant featuring in large range working conditions,non-linearity and large inertia,single model can＇t describe models＇characteristics accurately and regular controller can＇t satisfy both the response rapidity and the system stability.In order to solve the problem,system＇s models in four working conditions were identified by MATLAB identification toolbox： large range heating,large range cooling,small range heating and small range cooling,these models make up of the model set.Based on the human-simulated intelligent control theory,the response process was divided into three modes： the full load mode,the braking mode and the steady control mode,every mode has different models according to object＇s characteristics.By using the identified models,the controller＇s parameters and the switching point could be calculated.Multi-model weighted method was used in steady control mode by the reason of the models＇asymmetry.The test results on laboratory furnace device show that the controller has high control precision.The response speed and the system stability are also greatly improved.