A robust adaptive parameter estimation method, based on the application of a full‐order filter capable of rejecting exogenous disturbances, is proposed in this article. A linear matrix inequality condition is proposed to synthesize the desired robust filter, assuming the presence of a known input control with constraints. The filter uses the output of the system to estimate the desired signal that will be employed in the adaptive estimation procedure and, to assure robustness to exogenous noise and unstructured uncertainties, the guaranteed cost is minimized in the synthesis condition. The filtered signals are then applied to an adaptive procedure to estimate the unknown system's internal parameters, which is also proposed in this article. It is shown that lower values for the guaranteed cost from the disturbance input to the error output of the filter imply more accurate estimations of the parameters. The efficiency of the proposed estimation technique is illustrated through a simulated model and a physical system has been considered to validate real‐time estimation.

中文翻译：

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受外部噪声和不确定性影响的线性系统的鲁棒实时参数估计

本文提出了一种鲁棒的自适应参数估计方法，该方法基于能够抑制外来干扰的全阶滤波器的应用。提出了线性矩阵不等式条件，以合成所需的鲁棒滤波器，并假设存在已知的带有约束的输入控件。滤波器使用系统的输出来估计将在自适应估计程序中使用的期望信号，并确保对外部噪声和非结构化不确定性的鲁棒性，在合成条件下将保证成本降至最低。然后将滤波后的信号应用于自适应过程，以估计未知系统的内部参数，这也在本文中提出。结果表明，较低的从滤波器的扰动输入到误差输出的有保证的成本意味着参数的估计更加准确。通过仿真模型说明了所提出的估算技术的效率，并考虑了一个物理系统来验证实时估算。