Feedback vs Feedforward: Advantages and Disadvantages
Feedback Feedforward Introduction
Feedback is a term that most people are familiar with. It’s incorporated into many elements in daily life as well as an important tool for ensuring that our systems are performing as we expect them to. A common example is the thermostat in your home. It senses the air temperature in the room and turns the heat on if it falls too low. When the air warms up, it turns the heat source off. The air temperature provides the feedback in this system and it allows a thermostat to effectively regulate the temperature of our homes without ever directly measuring anything at the heat source itself. The result is a system with a very long control loop time, or in other words, a lot of lag. For example, if the heater is on the opposite side of the room from the thermostat, it will tend to overheat the room since it takes time for the warm air to reach the thermostat’s temperature sensor.
A Feedback Control Loop
Now imagine if the heating system had a mathematical model that very accurately described the effect of its operation on the room’s temperature.
For example, this model might know that to maintain the set room temperature it must run at 500W for five minutes every hour. If a disturbance to the system is detected, such as a sensor showing an open window, the model might extend the duration the heater is running to compensate. This system is an example of a feedforward system and allows for very fast control loop times because adjustments are made to the inputs of the system before a disturbance can affect the output.The downside to this system is that the effects of a disturbance must be very accurately known. If, for example, the window is open a bit more or less than the model assumes, then the room will be over or under heated and the system would have no idea.
In practice, most systems function at their highest level of performance by incorporating both feedforward and feedback. In our home heating example, the traditional thermostat could turn the heat off if it exceeded a threshold value.
Feedforward and Feedback Control Loop Diagrams
Feedback and Feedforward in Electric Motors
Traditional hydraulic and pneumatic linear motors often incorporate load cells on their shafts to measure the force being exerted by/upon them. The output from the load cell is fed back into the motor and logic is used to make adjustments to the motor’s input to achieve the desired output force. There are three major downsides to this.
First, the adjustment can only be made after an error in the output is realized. In delicate applications, this could mean that an excessive force is applied to a fragile object before a correction is made potentially causing damage.
Second, the time it takes for the load cell’s output to become a correction is not insignificant. This delay can cause disorientation and lack of realism in human-machine interactive applications such as VR and simulation.
Third, the added complexity of the load cell and the logic and cabling to support it adds cost and points of failure to the system. The reduced reliability and increased costs can exclude linear motors from applications in which they might otherwise excel. Feedforward control helps to solve these problems.
A 6-DoF Motion Platform Powered by Orca Series Linear Motors
Iris Dynamics has a model for how the force output from a winding changes depending on the position of the shaft in the winding. This model is refined by automated calibration routines run by each Orca Series motor. This information allows a feedforward control system to be implemented by measuring the position of the shaft with an array of hall sensors. The shaft position and calibration data are fed-forward along with the target force to arrive at a control signal.
An Orca Series Linear Motor (ORCA6-24V)
Advantages of the Orca Series Feedforward Force Control
Regarding speed, Orca Series motors arrive at a new control signal every time the position is measured. By contrast, systems with force sensors arrive at a new control signal only after the previous control signal has propagated through the system, which includes measurement and communication delays. This difference gives Orca Series motors the edge in latency and control bandwidth.
Regarding reliability, Hall sensors are rugged, solid-state devices buried in epoxy within each Orca Series motor – immune to dust, debris and damage. By contrast, force sensors are expensive, delicate devices.
In terms of simplicity, the Iris Dynamics Orca Series motors require no external sensors, analog signal cables, or sensor amplifies. Installation issues including sensor interference and wiring issues wont ever come up.
Feedforward in Orca Series Motors