Regulating Control of In-Pipe Intelligent Isolation Plugging Tool Based on Adaptive Dynamic Programming

In-pipe intelligent isolation plugging tools (IPTs) are crucial in pipeline maintenance. During the process, flow field around IPT changes drastically, resulting vibration and instability of process. Therefore, three foldable spoilers were designed at tail to reduce IPT. First, a disturbing experiment with was designed. A mathematical model pneumatic spoiler control system established regulate angles. Second, based on experimental data, bidirectional long short-term memory (Bi-LSTM) neural network predictor between states, angles, pressure gradient established. Then, an adaptive dynamic programming controller select optimal action for each state, thereby reducing gradient. Finally, Python MATLAB/Simulink used simulation. The results showed that prediction errors controlled within 9%, could during process by average 25.94%, which alleviated achieved smooth operation.