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FEATURE MOTION CONTROL


SELF-AWARE MOTION CONTR IN INDUSTRIAL AUTOMATION


A machine that can independently adapt its performance parameters


to complete an assigned task from a factory operator, or reconfigure itself to optimise its behaviour based on input from a productivity-enhanced artificial intelligence (AI) observer algorithm, is the next evolution in industrial automation. Jonas Proeger, senior manager, strategic


marketing at Analog Devices, examines why ‘self-aware machines’ will have the ability to maximise productivity, extend the operational lifespan of equipment, and reduce maintenance costs


for the system to achieve. In the example we use later in the article, the


• Productivity and maintenance tools provide performance targets to the self-aware motion control elements to modulate factory performance through the APIs


• Self-aware motion control system continuously drives real-time performance optimisation at the control and field levels based on the working environment conditions


goal is to ‘move the beer mug from point A to point B in the best way not to spill any beer’. Element II: Desired System Behaviour: Once this goal is established, the next level of the Motion Control Map initiates the desired Motion Behaviour. For our beer mug example, this would be ‘use a linear motion to move the beer mug while automatically adjusting its motion to compensate for the varying weight and size of the beer mug within the required control safety limits of the mechanical system’. Element III: Core Drive System: At the heart of the self-aware motion control system is its kinematics. The challenge is to observe, learn, and monitor the performance capabilities of the


Figure 1: Automation Pyramid S


elf-awareness describes a system with knowledge of itself based on an understanding of its capabilities and the


system’s performance goals. Self-aware motion control systems require the implementation of multiple control layers that interpret sensor inputs and desired system parameters and provide the capability to compare their operational behaviour vs. the desired system performance. To accomplish these goals and create self-


aware motion control systems, we need to create an adaptive motion control agent to monitor the system’s actions and dynamically adapt its performance based on the drive system’s work environment. Our focus in this article is to provide an approach to achieve a self-awareness motion control system by using an autonomous agent to detect and monitor the continuously changing working environment conditions. Once an electrical and mechanical model of the drive system is derived, this model is used to compare and adjust the desired system performance requested at the automation pyramid’ s supervisory, planning or


38 DESIGN SOLUTIONS MAY 2023


management levels (see Figure 1). The two main benefits of achieving a self-aware motion control system are the ability to self-regulate and automatically maximise the motion control system’s performance in real time.


AN UNDERSTANDING Let us examine a self-aware motion control concept map to better understand the four fundamental elements required to implement a self-aware motion control system. Self-Aware Motion Control


Concept Map: To implement this level of self-aware motion control, we need to develop a control system map. Figure 2 represents the four elements needed to implement self-aware motion control successfully. Element I: Goal or Task: A clear goal or task of the system needs to be established


Figure 2: Self-Aware Motion Control Concept Map


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