The problem of finding state space realizations that minimize the sensitivity to quantization error of a finite wordlength implementation of a discrete time linear system is considered. Finite wordlength implementations which invoke quantization either before or after multiplication, and possibly include error feedback, are represented in a unified framework. This framework is used to pose and solve four different optimal realization problems. These problems are formulated in a closed loop context, which contains open loop applications (filtering/estimation) as special cases. Our results may be used to find optimal realizations for the implementation of multivariable feedback controllers, or for the implementation of multivariable filters/estimators. Optimal realizations are derived based on either an H/sub 2/ or H/sub /spl infin// roundoff noise gain subject to either H/sub 2/ or H/sub /spl infin// scaling constraints. The H/sub 2/ noise gain measures the departure from the ideal closed loop response (no signal quantization) when the spectral properties of the quantization error are known. The H/sub /spl infin// noise gain measures worst-case deviation from ideal response when the variance of the quantization error is bounded but the spectral properties are otherwise unknown. The H/sub 2/ scaling constraints limit the size of the quantized internal signals when the spectral properties of the exogenous input to the closed loop system are known, while H/sub /spl infin// scaling restricts the maximum possible size of the internal signals when the spectral properties of the exogenous input are not precisely known. One of the optimization problems has a well-known analytical solution; the other three are reduced to the problem of minimizing a linear function subject to affine matrix inequality constraints, which is a convex optimization problem whose global optimum may be readily found. This solution, together with the unified framework for the analysis of several FWL implementations, constitutes the main contribution of this paper.
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机译:考虑了寻找最小化离散时间线性系统的有限字长实现对量化误差的敏感性的状态空间实现的问题。在统一框架中表示了有限的字长实现,这些实现在乘法之前或之后调用量化,并且可能包括错误反馈。该框架用于提出和解决四个不同的最佳实现问题。这些问题是在闭环环境中提出的,在特殊情况下,其中包含开环应用程序(过滤/估计)。我们的结果可用于找到实现多变量反馈控制器或实现多变量滤波器/估计器的最佳实现。基于H / sub 2 /或H / sub 2 / spl infin //的舍入噪声增益,根据H / sub 2 /或H / sub 2 / spl infin //缩放约束,可以得出最佳实现。当量化误差的频谱特性已知时,H / sub 2 /噪声增益可测量与理想闭环响应(无信号量化)的偏离。当量化误差的方差有界但频谱特性未知时,H / sub / spl infin //噪声增益可测量与理想响应的最坏情况偏差。当已知到闭环系统的外源输入的频谱特性时,H / sub 2 /缩放约束将限制量化内部信号的大小,而H / sub 2 / spl infin //缩放将限制内部最大可能的大小当外源输入的光谱特性未知时发出信号。优化问题之一是众所周知的分析解决方案。其他三个简化为使最小化线性函数受到仿射矩阵不等式约束的问题,这是一个凸优化问题,其全局最优值很容易找到。该解决方案以及用于分析多个FWL实现的统一框架构成了本文的主要贡献。
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