From 3c649a91f121e9a26653058f0e4ffebfb3a5784a Mon Sep 17 00:00:00 2001
From: Andru Liu <90433630+WallabyLester@users.noreply.github.com>
Date: Mon, 7 Oct 2024 23:14:47 -0700
Subject: [PATCH] Example training usage with simulation data.

---
 first_order_sim.py | 24 ++++++++++++++++++++++++
 1 file changed, 24 insertions(+)

diff --git a/first_order_sim.py b/first_order_sim.py
index 5f3e5c6..0f208e5 100644
--- a/first_order_sim.py
+++ b/first_order_sim.py
@@ -118,3 +118,27 @@ if __name__ == "__main__":
     plt.legend()
     plt.grid()
     plt.show()
+
+    # Training RBF model with simulated data
+    rbf_tf = RBFAdaptiveModel(n_centers=5, input_dim=3)
+    rbf_tf.compile(optimizer="adam", loss="mean_squared_error")
+
+    apid_tf = AdaptivePIDTf(Kp=4.0, Ki=0.6, Kd=0.08, rbf_model=rbf_tf)
+
+    errors, control_signals = simulate_rbf_train_data(rbf_tf, apid_tf)
+    train_rbf_adaptive(rbf_tf, errors, control_signals, epochs=50)
+
+    target = 1.0
+    dt = 0.1
+    T = 10.0
+    time, measurements = simulate_system(apid_tf, target, dt, T)
+
+    plt.plot(time, measurements, label="Measured Value")
+    plt.axhline(y=target, color="r", linestyle="--", label="Target")
+    plt.ylim(max(measurements)-0.6, max(measurements)+0.1)
+    plt.xlabel("Time (s)")
+    plt.ylabel("Output")
+    plt.title("Adaptive RBF Neural PID Controller TF Trained")
+    plt.legend()
+    plt.grid()
+    plt.show()