Distributed Temperature Control in Laser-Based Manufacturing
Distributed Temperature Control in Laser-Based Manufacturing
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DOI：
10.1115/1.4046154
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发表时间：
2020-06
影响因子：
1.7
通讯作者：
C. Zheng;J. Wen;M. Diagne
中科院分区：
文献类型：
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作者：
C. Zheng;J. Wen;M. Diagne
在激光制造中，温度控制是调节材料性能的关键。扫描激光的运动和功率影响局部温度演变，进而决定了后验微观结构。本文解决了调节激光速度和功率以达到冷却速度和熔池尺寸等关键工艺参数所需值的问题。扫描激光系统的动力学用一维（1D）热传导方程来建模，以激光功率为热输入和热耗散到环境中。由于模型是一维的，长度和尺寸基本相同。我们把这个问题看作是（运动）激光机架中的调节问题。第一步是根据期望的冷却速率和熔池大小获得稳态温度分布和相应的输入。控制器根据测量温度场与稳态分布的偏差来调整稳态前馈周围的输入。我们证明，通过适当的定义输出，系统对激光运动和功率严格无源。为了避免对模型的过度依赖，对稳态激光速度和功率进行自适应更新，使前馈系统具有类似积分的更新规律。此外，对环境的换热系数可能是不确定的，也可以自适应更新。控制律的最终形式是将无源误差温度场反馈与自适应前馈和参数估计相结合。利用李雅普诺夫参数证明了该控制器的闭环渐近稳定性，并通过仿真验证了控制器的性能。
Temperature control is essential for regulating material properties in laser-based manufacturing. Motion and power of the scanning laser affect local temperature evolution, which in turn determines the a posteriori microstructure. This paper addresses the problem of adjusting the laser speed and power to achieve the desired values of key process parameters: cooling rate and melt pool size. The dynamics of a scanning laser system is modeled by a one-dimensional (1D) heat conduction equation, with laser power as the heat input and heat dissipation to the ambient. Since the model is 1D, length and size are essentially the same. We pose the problem as a regulation problem in the (moving) laser frame. The first step is to obtain the steady-state temperature distribution and the corresponding input based on the desired cooling rate and melt pool size. The controller adjusts the input around the steady-state feedforward based on the deviation of the measured temperature field from the steady-state distribution. We show that with suitably defined outputs, the system is strictly passive from the laser motion and power. To avoid over-reliance on the model, the steady-state laser speed and power are adaptively updated, resulting in an integral-like update law for the feedforward. Moreover, the heat transfer coefficient to the ambient may be uncertain, and can also be adaptively updated. The final form of the control law combines passive error temperature field feedback with adaptive feedforward and parameter estimation. The closed-loop asymptotical stability is shown using the Lyapunov arguments, and the controller performance is demonstrated in a simulation.