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Low-risk beginning of the density control on the KSTAR plasmas

机译:低风险的密度控制在KSTAR等离子体上的开始

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During the early campaigns of the KSTAR project, feedback control of plasma density has been successfully commissioned at the very first attempt by using a transfer function analysis. In order to minimize a chance of any risk happening, a stable and robust Ohmic discharge was chosen as a test-bed of 300 kA (I-p) circular limited plasma in 2.0 T (B-t). Pre-programmed fueling modulation was carried out first by puffing the deuterium gas via a piezoelectric valve. Line-averaged plasma density was measured in real-time by a 280 GHz interferometer system. From those modulations, both the density decay time (tau(i)*) and the external fueling efficiency (f(ex)) were approximated in windows: 3.0-5.0 s and 10-20% respectively. By using the results, a simple plant model has been established based on a global particle balance equation. Then several transient responses such as rising time, settling time and overshoot ratio were estimated in a certain range depending on the windows of tau(i)* and f(ex). It is found that tau(i)* has little effect on those response characteristics while f(ex) plays primary role together with magnitude of the proportional gain G(p). This is due to predominance of valve response whose characteristic time tau(v) was approximately 60 ms, which is much shorter than tau(i)*. Considering the responses, G(p) for closed-loop control were set initially very low i.e. 2.5 being concerned on excessive fueling. It was followed by several stepwise increments to reduce steady-state error instead of using any integral gain G(I) to avoid any chance of instability and uncertainty. Similarly, the target density was also initially low and gradually growing. In this way the very first density feedback control was successfully completed although some of the transient responses were different from the anticipated results while the predicted steady-state error was in good agreement with the experimental undershoot. By investigating an arbitrary time delay tau(alpha), it is found that the digital-low-pass filter embedded in the plasma control system (PCS) of 50 ms also plays crucial role together with the tau(v). In such way, settling time tau(s) and low overshoot case were well agreed but rising time t(r) ring well predicted steady-state error, with settling time t(s), the transfer function analysis with the simple particle balance model is appropriate for relatively slow responses but not applicable for the faster responses and strong overshoot, which may not be linear-time-invariant (LTI) system anymore. More comprehensive physics-basis modeling will be necessary for more accurate prediction including fast responses and strong overshoot of feedback control of the density.
机译:在KSTAR项目的早期活动期间,通过使用传递函数分析,已经成功地委托了等离子体密度的反馈控制。为了最小化发生任何风险的可能性,选择稳定且稳健的欧姆放电作为300ka(I-P)圆形有限血浆的试验床(B-T)。通过压电阀膨化氘气来首先进行预编程的燃料调制。通过280GHz干涉仪系统实时测量线平均等离子体密度。从那些调制中,密度衰减时间(TAU(I)*)和外部加油效率(F(ex))分别近似:3.0-5.0 s和10-20%。通过使用结果,基于全局粒子平衡方程建立了一个简单的工厂模型。然后根据TAU(i)*和F(前)的窗口,在一定范围内估计了几个瞬态响应,例如上升时间,稳定时间和过冲比。结果发现,TAU(i)*对这些响应特性的影响几乎没有影响,而F(前)与比例增益G(P)的大小一起发挥着主要作用。这是由于阀门响应的优势,其特征时间tau(v)约为60 ms,这比Tau(i)*短得多。考虑到闭环控制的响应,最初非常低,即2.5涉及过度加油。接下来是几个逐步的递增,以减小稳态误差,而不是使用任何整体增益G(i)来避免任何不稳定性和不确定性的机会。类似地,目标密度也最初是低且逐渐生长。以这种方式,最虽然一些瞬态响应与预期结果不同,但在预测的稳态误差与实验性溢出良好的同时,但是虽然一些瞬态响应与预期的稳态误差有关。通过调查任意时间延迟Tau(alpha),发现嵌入在50毫秒的等离子控制系统(PC)中的数字低通滤波器也与TAU(V)一起起重要作用。以这种方式,稳定时间tau(s)和低过冲案例都很好地商定但上升时间t(r)环井预测稳态误差,稳定时间t(s),具有简单粒子平衡模型的传递函数分析适用于相对缓慢的响应,但不适用于更快的响应和强烈的过冲,这可能不再是线性时不变(LTI)系统。更精确的预测,包括快速响应和反馈密度的强烈过冲,将需要更全面的物理基础建模。

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