Controllers Overview¶

Controllers are algorithms that help maintain a system at a desired setpoint by processing sensor feedback and calculating the necessary actuator output.

Common Control Applications¶

The table below provides examples of typical control systems in a laboratory setting and the recommended controller type for each.

Application	Sensor (Feedback)	Actuator (Output)	Typical Controller
Pressure	Transducer	Control Valve / Compressor	PID (Fast)
Motion	Encoder / Hall Effect	Stepper or Servo Motor	PID (High Precision)
Flow	Flow Meter	Pump Speed / Valve	PID or Feedforward
Level	Ultrasonic / Float	Intake Valve	On-Off or PID
pH	pH Probe	Peristaltic Pump	Fuzzy Logic

Available Controllers¶

Simmate provides several built-in controllers in the simmate.apps.lab_automation.controllers module. All controllers inherit from a base Controller class, which ensures a consistent interface via the .eval() method.

The Controller Base Class¶

The Controller base class defines the standard interface for all control algorithms. When creating a custom controller, you should inherit from this class and implement the eval method.

from simmate.apps.lab_automation.controllers import Controller

class MyCustomController(Controller):
    def eval(self, input_: float, dt: float = None) -> float:
        # custom control logic here
        return 1.0

PID Controller¶

The Proportional-Integral-Derivative (PID) controller is the industry standard for precise control of continuous systems.

from simmate.apps.lab_automation.controllers import PID

controller = PID(Kp=1.0, Ki=0.1, Kd=0.05, setpoint=25.0)
output = controller.eval(current_temperature)

On-Off (Bang-Bang) Controller¶

A simple controller that switches between two states. It is ideal for systems where high precision is not required and simple hysteresis (deadband) is sufficient.

from simmate.apps.lab_automation.controllers import OnOff

controller = OnOff(setpoint=25.0, deadband=1.0)
output = controller.eval(current_temperature)

Time-Proportional (PWM) Controller¶

Useful for controlling digital actuators (like a heater relay) to simulate continuous control.

from simmate.apps.lab_automation.controllers import TimeProportional

controller = TimeProportional(setpoint=25.0, cycle_time=2.0)
output = controller.eval(current_temperature)

Fuzzy Logic Controller¶

Allows for rule-based control logic, which is particularly useful for complex or non-linear systems like pH control.

from simmate.apps.lab_automation.controllers import FuzzyLogic

rules = [
    {"max": 20, "output": 1.0},
    {"min": 20, "max": 25, "output": 0.5},
    {"min": 25, "output": 0.0},
]
controller = FuzzyLogic(rules=rules)
output = controller.eval(current_temperature)