Signal processing, identification and control in switched non-linear systems

这项研究涉及对发生参数突变的控制系统进行分析和辨识，以便能够选择替代控制方案。这种系统存在于许多生理环境中，例如，那些被大脑用来控制运动的系统。由于违反了通常的恒定特性(平稳性)假设，需要特殊的算法来允许在参数突然变化和可变初始条件存在的情况下对系统动态进行一致估计。因此，本研究的第一部分解决了在MATLAB模块中开发软件工具以便于分发的问题，这将有两个目的。首先，使用简化模型将系统的响应模式快速分类为可能的配置。其次，使用考虑短响应段和可变初始条件的辨识方法将系统模型拟合到每种潜在模式。这些结果直接应用于CIHR资助的双眼控制临床诊断和建模研究。第二个主要部分研究了从生理运动控制建模(CIHR支持的工作)推导出的策略，并将如此推导出的新策略移植到机器人定位系统和感觉融合问题。例如，我们已经成功地在使用动态模式切换的双目系统中实现了快速目标跟踪，并且可以在不增加控制器的情况下协调支撑颈的运动。这种由生物激发的方法提供了更快、更准确的控制前景，尽管控制器结构简单。复杂的行为依赖于内部切换，这当然引入了非线性，必须在项目的设计和分析方面加以解决。这项技术正在扩展，以允许在机器人头部和手臂中使用感官融合的创新方法和与环境相适应的“反射”。

This research concerns the analysis and identification of control systems undergoing sudden parametric changes, to enable selection of alternate control schemes. Such systems exist in many physiological contexts,e.g., those used by the brain to control movement. Since usual assumptions of constant characteristics (stationarity) are violated, special algorithms are required to allow consistent estimation of system dynamics in the presence of sudden parametric changes and variable initial conditions.Hence, the first part of this research addresses the issue of developing software tools in MATLAB modules for easy distribution, which will have 2 purposes. First, fast classification of a system's response modes into potential configurations, using reduced models. Second, fitting system models to each of the potential modes using identification methods which take into account short response segments and variable initial conditions. Results here are finding direct application in CIHR funded research on clinical diagnosis and modelling of binocular control.The second major component examines the strategies deduced from the modelling of physiological motor control (CIHR supported work) and is porting so-deduced novel strategies to robot orientation systems and sensory fusion issues. For example, we have successfully implemented fast target pursuit in a binocular system using dynamic mode switching, and can coordinate motion of a supporting "neck" without additional controllers. The biologially-evoked approach offers the promise of faster and more accurate control, despite structurally simple controllers. Complex behaviour relies on internal switching which of course introduces non-linearities which must be addressed in the design and analysis aspects of the projects. This is being extended to allow innovative methods of sensory fusion and 'reflex' adaptation with context in both robotic heads and arms.