论文标题
具有非分离非线性参数化的两类非线性系统的参数估计
Parameter Estimation of Two Classes of Nonlinear Systems with Non-separable Nonlinear Parameterizations
论文作者
论文摘要
在本文中，我们解决了设计全球收敛估计量的挑战性问题，该估计量含有非线性系统的参数，该系统包含不可分割的指数非线性。这类术语出现在许多实际应用中，并且现有的参数估计器都无法以有效的方式处理它们。提出的估计程序用两种现代应用说明：燃料电池和人类肌肉骨骼动力学。该过程不假定参数生活在已知的紧凑型集中，非线性可以满足某些Lipschitzian特性，也不依赖于注入高增益或使用复杂的，计算苛刻的方法。取而代之的是，我们建议设计一个经典的在线估计器，其动力学由以紧凑的精确形式给出的普通微分方程描述。本文的进一步贡献是证明参数收敛可以通过极度弱的间隔激发要求保证。
In this paper we address the challenging problem of designing globally convergent estimators for the parameters of nonlinear systems containing a non-separable exponential nonlinearity. This class of terms appears in many practical applications, and none of the existing parameter estimators is able to deal with them in an efficient way. The proposed estimation procedure is illustrated with two modern applications: fuel cells and human musculoskeletal dynamics. The procedure does not assume that the parameters live in known compact sets, that the nonlinearities satisfy some Lipschitzian properties, nor rely on injection of high-gain or the use of complex, computationally demanding methodologies. Instead, we propose to design a classical on-line estimator whose dynamics is described by an ordinary differential equation given in a compact precise form. A further contribution of the paper is the proof that parameter convergence is guaranteed with the extremely weak interval excitation requirement.
