Robust Design and Effective Control of Mechanical Systems

我提议的研究计划是我在之前的发现赠款中进行的工作的自然延伸。该计划现在更加集中，强调设计的鲁棒性和控制的有效性。我们在下面的G.田口的概念（1980年代），在信噪比方面。实现这一概念的困难在于噪声和信号的合理识别。在概念层面上，我们介绍了复杂性的概念，并说明了它的情况下，机构设计（“复杂性”是强烈依赖于上下文），特别强调了六个较低的运动副（旋转，棱柱，螺旋，圆柱，平面和球面）。在可获得元件或组件的数学模型的实施例和详细设计级别，信号被识别为定义设计环境的参数，例如，来自供应商线路的电力的频率和电压，设计者对其没有影响。噪声被定义为供应商参数中不可预测的变化。这些我们建模为随机高斯过程的平均值和标准差。 我们计划在机器人领域使用我们的研发范式。具体来说，我们针对两种机器人：1）用于快速拾取和放置操作的机器人，这些机器人存在于广泛的工业过程中，从设计有平面几何形状的手持消费品的制造（例如，手机）到食品包装。这些是四自由度（四自由度）机器人;和2）用于振动操作的六自由度并联机器人，由高频（> 10 Hz）（HF）和小振幅（SA）（相对于“小”）定义试验机的尺寸）。其应用也很广泛，从简单的流体混合到惯性参数识别，惯性参数识别是电信卫星姿态控制的一个主要问题，加拿大自八十年代以来一直是这方面的领导者。我们的建议包括开发一种新的方法IPI，再次使用田口的鲁棒性范例：最大限度地提高信噪比。不仅如此。我们还计划开发更简单，低成本的IPI机器，通过测试样本进行HF，SA平面位移。在提出的试样的测试机，一个平面3自由度机器人，具有不同的姿势，它将是可能的，所以我们要求，以确定所有10个惯性参数的刚性物体：质量，三个坐标的质心，和六个独立的组成部分的惯性张量。对于我们设计和原型的机械系统的有效控制，工作更多的是应用而不是理论。我们计划继续开发控制策略及其算法，用于在“小”位移下实现10 Hz及以上的快速操作。挑战是巨大的，因为激励机器运动部件的较低自然模式的风险。

The research program I am proposing is a natural extension of the work I have conducted in previous Discovery Grants. The program is now more focused, stressing robustness in design and effectiveness in control. We define robust design (RD) in following G. Taguchi's concept (1980s), in terms of the signal-to-noise ratio. The difficulty in implementing this concept lies in the plausible identification of noise and of signal. At the conceptual level we introduced the concept of complexity, and illustrated it for the case of mechanism design ("complexity" is strongly dependent on the context),  with special emphasis on the six lower kinematic pairs (revolute, prismatic, screw, cylindrical, planar and spherical). At the embodiment and the detailed-design levels, at which a mathematical model of elements or assemblies is available, the signal is identified as the parameters defining the design environment, for example, the frequency and voltage of the electric power coming from the supplier's line, over which the designer has no influence. Noise is defined as the unpredictable variations in the supplier's parameters. These we model as stochastic Gaussian processes with available values of mean and standard deviation.  We plan to use our RD paradigm in the context of robotics. Specifically, we target 2 kinds of robots: 1) Those for fast pick-and-place operations, which are present in a broad range of industrial processes, from the fabrication of hand-held consumer goods designed with a flat geometry (e.g., cell phones) to the packaging of food. These are four-degree-of-freedom (four-dof) robots; and 2) six-dof parallel robots for shaking operations, defined by high frequency (> 10 Hz) (HF) and small amplitude (SA) ("small" w.r.t. the dimensions of the testing machine). Applications thereof are also broad, from simple fluid-mixing to inertia-parameter identification (IPI), a major issue in the attitude control of telecommunications satellites, in which Canada has been a leader since the eighties. Our proposal includes the development of a novel methodology for IPI, using, again, Taguchi's robustness paradigm: maximize the signal-to-noise ratio. Not only this. We also plan to develop simpler, low-cost machines of IPI, by subjecting the test specimen to HF, SA planar displacements. Upon presenting the specimen to the testing machine, a planar 3-dof robot, with different poses, it will be possible, so we claim, to identify all 10 inertia parameters of the rigid object: mass, three coordinates of the centre of mass, and six independent components of the inertia tensor. On the effective control of the mechanical systems we design and prototype, the work is more applied than theoretical. We plan to continue developing control strategies and their algorithms for fast operations, of 10 Hz and beyond, under "small" displacements. The challenges are enormous, because of the risk of exciting the lower natural modes of the moving parts of the machine.