Controllers

Controllers are algorithms that automatically adjust system outputs to achieve desired behaviors. In robotics, they're essential for precise motion control, maintaining setpoints, and responding to disturbances. RobotPy provides several controller types, each suited for different applications.

Control Theory Fundamentals

flowchart LR
    A[Reference/Setpoint] --> B[Controller]
    B --> C[Plant/System]
    C --> D[Output]
    C --> E[Sensor]
    E --> F[Feedback]
    F --> G[Error Calculator]
    A --> G
    G --> B
    
    subgraph "Closed Loop Control"
        B
        C
        E
        F
        G
    end
    
    style A fill:#e1f5fe
    style D fill:#e8f5e8
    style G fill:#fff3e0

Key Concepts

Plant: The system being controlled (motor, elevator, drivetrain)
Setpoint: Desired output value (target position, velocity)
Error: Difference between setpoint and actual output
Feedback: Measured system output (encoder, gyro, vision)
Control Signal: Controller output to the plant

Controller Types Comparison

Controller	Complexity	Tuning Effort	Best Use Cases	Steady-State Error
Bang-Bang	Very Low	None	Binary states, simple mechanisms	High
PID	Medium	Moderate	Position/velocity control	Low (with I term)
PIDF	Medium-High	High	Systems with known dynamics	Very Low
Profiled PID	High	High	Smooth motion profiles	Very Low

System Response Characteristics

xychart-beta
    title "Step Response Comparison"
    x-axis [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10]
    y-axis "Output" 0 --> 1.4
    line "Well-Tuned PID" [0, 0.6, 0.95, 1.05, 1.02, 1.0, 0.99, 1.0, 1.0, 1.0, 1.0]
    line "Oscillatory" [0, 0.8, 1.2, 0.9, 1.1, 0.95, 1.05, 0.98, 1.02, 0.99, 1.01]
    line "Sluggish" [0, 0.2, 0.4, 0.6, 0.75, 0.85, 0.92, 0.96, 0.98, 0.99, 1.0]

Performance Metrics

Rise Time: Time to reach 90% of setpoint
Settling Time: Time to stay within ±5% of setpoint
Overshoot: Peak value beyond setpoint
Steady-State Error: Final error after settling

Controller Selection Guide

Bang-Bang Controller

When to use: Binary operations, systems with hysteresis
Examples: Compressors, simple intakes, binary mechanisms
Advantages: Simple, robust, fast response
Disadvantages: Oscillation, wear, inefficiency

PID Controller

When to use: Continuous control, position/velocity regulation
Examples: Arm positioning, shooter speed, drivetrain heading
Advantages: Versatile, well-understood, handles disturbances
Disadvantages: Requires tuning, can be sluggish

PIDF Controller

When to use: Systems with known dynamics, gravity compensation
Examples: Elevators, arms against gravity, flywheels
Advantages: Fast response, reduced steady-state error
Disadvantages: Requires system modeling, complex tuning

Tuning Process Overview

flowchart TD
    A[Start with P-only] --> B[Increase P until oscillation]
    B --> C[Reduce P by 50%]
    C --> D[Add D to reduce overshoot]
    D --> E[Add I to eliminate steady-state error]
    E --> F[Add F for known disturbances]
    F --> G[Fine-tune all parameters]
    
    G --> H{Satisfactory?}
    H -->|No| I[Adjust parameters]
    I --> G
    H -->|Yes| J[Document final gains]
    
    style A fill:#e1f5fe
    style J fill:#e8f5e8

Implementation in RobotPy

Basic Controller Usage Pattern

# Standard pattern for controller implementation
class ControlledSubsystem(commands2.SubsystemBase):
    def __init__(self):
        super().__init__()
        self.motor = ctre.WPI_TalonFX(1)
        self.encoder = self.motor.getSelectedSensorPosition
        
        # Choose appropriate controller
        self.controller = wpilib.PIDController(
            kP=0.1, kI=0.0, kD=0.0
        )
        
        # Set constraints if needed
        self.controller.setTolerance(0.05)  # 5% tolerance
        
    def periodic(self):
        # Run controller every 20ms
        if self.controller.getSetpoint() != 0:
            output = self.controller.calculate(self.encoder())
            self.motor.set(output)
    
    def setSetpoint(self, setpoint):
        self.controller.setSetpoint(setpoint)
    
    def atSetpoint(self):
        return self.controller.atSetpoint()

Advanced Topics

The following pages provide detailed coverage of each controller type:

Bang-Bang: Simple on/off control with hysteresis
PID Control: Proportional-Integral-Derivative control theory and tuning
PIDF Control: Feedforward-enhanced PID for improved performance
Ramsete: Nonlinear trajectory following for differential drive
Higher-Order Controllers: Advanced techniques for complex systems

1757 Programming Documentation