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Derivative-Free Nonlinear Kalman Filtering for MIMO Dynamical Systems: Application to Multi-DOF Robotic Manipulators

机译:MIMO动力学系统的无导数非线性卡尔曼滤波:在多自由度机器人操纵器中的应用

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The paper proposes derivative-free nonlinear Kalman Filtering for MIMO nonlinear dynamical systems. The considered nonlinear filtering scheme which is based on differential flatness theory extends the class of systems to which Kalman Filtering can be applied without the need for calculation of Jacobian matrices. To deduce if a dynamical system is differentially flat, the following should be examined: (i) the existence of the flat output, which is a variable that can be written as a function of the system's state variables (ii) the system's state variables and the input can be written as functions of the flat output and its derivatives. Nonlinear systems satisfying the differential flatness property can be written in the Brunovsky form via a transformation of their state variables and control inputs. After transforming the nonlinear system to the canonical form it is straightforward to apply the standard Kalman Filter recursion. The performance of the proposed derivative-free nonlinear filtering scheme is ...
机译:提出了用于MIMO非线性动力学系统的无导数非线性卡尔曼滤波。所考虑的基于微分平坦度理论的非线性滤波方案扩展了无需进行雅可比矩阵计算即可应用卡尔曼滤波的系统类​​别。为了推断动力系统是否为微分平坦的,应检查以下内容:(i)平坦输出的存在,该输出是可以根据系统状态变量编写的变量(ii)系统状态变量和输入可以写为平面输出及其派生函数。满足差分平坦度特性的非线性系统可以通过状态变量和控制输入的转换以Brunovsky形式编写。将非线性系统转换为规范形式后,可以直接应用标准的卡尔曼滤波器递归。所提出的无导数非线性滤波方案的性能为...

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