Industrial
data across its network of intelligent sensors. Once the desired behaviour is passed along to the adaptive control engine, the self-aware motion control system begins to dynamically reconfigure the drive systems operating parameters to match the desired system behaviour. A few examples of these desired behaviours are a request to increase factory throughput or extend the motor’s operational lifetime by operating in a safe mode. As the motion control system automatically adjusts its motion control parameters to achieve this new level of requested performance, the adaptive control system continuously monitors the closed loop system to maintain its desired performance level. This state is maintained even if the drive system experiences change due to wear and tear of its mechanical systems or if a change in the motor’s working environment is encountered. Now the system has achieved the ultimate level of self-aware motion control.
Figure 2. Self-aware motion control concept map
flux current loop, velocity loop, and it’s positioning loop, we can optimise the drive system response. Once these datagrams of information are gathered and fed into an intelligent observer, an optimisation algorithm is implemented to ensure the motion control parameters are calculated and the base motion control algorithm converges to an optimal set of motion
parameters (Figure 3). Now that an indirect motion model is created to model and optimise the motion of the drive system, we can implement the next level of the self-aware motion control solution by introducing an adaptive control engine. Element IV: Adaptive control: Building on the kinematics and FOC auto-tuning capability of our system, we can now focus
Figure 3. Monitoring and auto-tuning of torque-flux current, velocity, and position loops
on the next level in implementing self- aware motion control, the adaptive control engine. This next level of intelligent motion focuses on communicating the desired system behaviour into the adaptive control engine (Figure 4). This system behaviour is provided by a production employee, plant supervisor, or generated from an AI productivity algorithm that gathers factory
Perhaps the best way to demonstrate this concept is to use a real-world example (Figure 5). This example is relevant to all beer aficionados that like to ensure their frothy glass of beer can be delivered from the bartender across the length of a bar without spilling a drop of beer in the process. Let us examine how this example is relevant to implementing a self-aware motion control system. The goal of this task is to deliver the beer in the fastest time possible from the bartender (point A) to a patron (point B) sitting down the length of the bar without spilling a drop of beer. The plant system in this case is a cup holder with a built-in weight detector to detect the weight of the various size beer mugs and move it across the length of the bar using a linear motor. So, let us think about this example. A self-aware motion control system is beneficial to deliver
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Components in Electronics
September 2022 15
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