Table 1 Simulation model and control parameters.
From: Event-triggered fuzzy neural-network PID control for nonlinear gas-blending processes
Parameter Category | Name | Symbol | Value / Description |
|---|---|---|---|
Gas Mixing Model | Low-concentration gas flow rate | \(Q_1\) | \(100\ \text {m}^3/\text {h}\) |
High-concentration gas flow rate range | \(Q_2\) | \(0 - 150\ \text {m}^3/\text {h}\) | |
Target methane concentration | \(Y_{\text {target}}\) | \(12\%, 15\%, 10\%\) (step change) | |
Temperature | T | \(298.15\ \text {K}\) | |
Pressure | p | \(101325\ \text {Pa}\) | |
Total simulation duration | \(T_{\text {total}}\) | \(60\ \text {min}\) | |
Sampling interval | \(\Delta t\) | \(0.1\ \text {min}\) | |
TSFNN Model | Number of input variables | N | 3 (low-concentration flow, high-concentration flow, high-concentration real-time concentration) |
Number of fuzzy rules | R | 49 | |
Membership function | – | Gaussian function | |
ET-FNN-PID Controller | Initial proportional gain | \(K_p(0)\) | 1.0 |
Initial integral gain | \(K_i(0)\) | 0.1 | |
Initial derivative gain | \(K_d(0)\) | 0.01 | |
Learning rates | \(\eta _c, \eta _b, \eta _w\) | 0.3, 0.3, 0.3 | |
Momentum factor | \(\alpha\) | 0.05 | |
Event-triggered threshold | Q | 0.5 |
