量测噪声情况下基于自适应D-S证据推理的滑模控制

在滑模控制中 ,当状态量测传感器存在噪声时 ,控制器不能获得准确的滑模函数信息。面向一类不确定非线性系统 ,根据滑模控制依赖滑模函数符号的特点 ,提出利用基于Dempster Shafer证据推理的多传感器信息融合方法 ,其作用是压缩滑模函数符号的不确定性 ,并基于闭环原理给出了对信息融合结果进行自适应补偿的改进方法。仿真表明了该方法的有效性。

Sliding Mode Control Based on Adaptive D-S Evidential Reasoning in the Presence of Measuring Noise

In sliding mode control, the controller could not get correct information of the sliding mode function when measuring noise of state sensors exists.For a class of uncertain nonlinear systems, according to the nature of sliding mode control--depending on the sign of the sliding mode function, a scheme of applying Dempster-Shafer evidence reasoning-based multi-sensor fusion is proposed, which could reduce the uncertainty of the sign of the sliding mode function. additionally, based on close loop principle, an improved method with adaptive compensation is presented. Simulations indicate the methods' effectiveness.