Function Reference¶
The following table lists the classes and methods that can be used to model and simulate various systems and control strategies.
System Definition¶
| Class | Description |
|---|---|
| TransferFunction(num, den) | Creates a Transfer Function system object |
| StateSpace(A,B,C,D) | Creates a State Space system object |
Transfer Function Methods¶
| Method | Description |
|---|---|
| display() | Displays the Transfer Function system |
| parameters(settling_time_tolerance=0.02) | Returns the parameters of the system |
| response(input_type, time_period=10, sample_time=0.05, ret=False, show=True) | Returns the time domain response on the system |
| pzplot(ret=True) | Plots the Pole-Zero plot of the system and return poles and zeros |
| stability() | Returns the stability of the system |
| rootlocus(tf, gain_range=10.0) | Returns Root Locus of the system |
State Space Methods¶
| Method | Description |
|---|---|
| display() | Displays the State Space system |
| convert2TF() | Converts State Space model to Transfer Function |
| contr() | Controllability of the system |
| obs() | Observability of the system |
| stability() | Stability of the system |
| eigplot(ret=True) | Plots eigenvalues/poles of system |
| StateResponse(t, initial_cond, u, ret=False, show=True) | Returns and plots state response |
| OutputResponse(t, initial_cond, u, ret=False, show=True) | Returns and plots output response |
System Connections¶
| Method | Description |
|---|---|
| feedback( G, H=1.0, feedback_type=”negative”) | Creates a Feedback Object |
| reduce.series(tf1, *tfn) | Return the series connection (tfn * … |
| reduce.parallel(tf1, *tfn) | Return the parallel connection (tfn + … |
Frequency Domain Analysis¶
| Method | Description |
|---|---|
| bode.freqresp(tf) | Returns the Frequency Response of the system |
| bode.bode(tf) | Returns the Bode Plot of the system |
PID Controller Design¶
| Method | Description |
|---|---|
| PID(Kp, Ki, Kd, tf) | Creates a PID object |
| response(input_type, time_period=10, sample_time=0.05, ret=False, show=True) | Return the response of the system after PID control |
| tune(input_type=”step”, set_point=1, num_itr=70, rate=0.00000000001, lambd=0.7) | Tune the PID coefficients |
| display() | Display the PID block |
| reduced_tf | Displays the reduced Transfer Function (Controller + Plant) |
State Feedback Design¶
| Method | Description |
|---|---|
| StateFeedback(ss) | Creates a StateFeedback object |
| solve(roots) | Calculates the State Feedback gain matrix |
| model(k_ref=1) | Retruns StateSpace object after applying State Feedback |
State Observer Design¶
| Method | Description |
|---|---|
| StateObserver(ss) | Creates StateObserver object |
| solve(roots) | Calculates the State Observer gain matrix |
| model(k_ref=1) | Retruns the StateSpace object after applying State Observervation |
Linear Quadratic Regulator(LQR)¶
| Method | Description |
|---|---|
| LQR(ss, Q, R, N) | Creates an LQR object |
| solve() | Calculates the optimal gain matrix |
| model() | Returns the StateSpace object after applying State Observation |
Kalman Filter / Linear Quadratic Estimator(LQE)¶
| Method | Description |
|---|---|
| KalmanFilter(ss, Q, R, P=None, x0=None) | Creates a KalmanFilter object |
| predict(u = 0): | Predict next state |
| update(z): | Update Predictions |
| solve(measurements, ret_k=False, ret_x=False): | Returns the Predictions, Kalman Gain, and States of the system |