Linear Motor Phase-Adaptive Control for Precise, Energy-Saving Motion
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing control systems for linear motors lack flexibility in adapting to different movement phases and control objectives, leading to inefficient energy use and limited accuracy in transport unit movement.
Innovation Solution
The implementation of a quality functional that evaluates deviations from setpoint variables, allowing for flexible adaptation of control strategies across different movement phases, combined with off-line optimization and the use of a reluctance network model for improved control accuracy and energy efficiency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If a fixed control strategy is used for linear motor operation, then the control system is simple, but it cannot adapt to different movement phases and control objectives, leading to inefficient energy use and limited accuracy
Solution Approach 1:
The patent implements a dynamic control strategy where the quality functional and its weighting factors are adaptively changed according to different movement phases (acceleration, constant speed, deceleration). This allows the control system to optimize performance for each phase while maintaining a unified control framework, resolving the contradiction between adaptability and complexity.
Solution Approach 2:
The patent changes parameters of the quality functional (weighting factors k1, k2, k3) based on movement phase and control objectives. By adjusting these parameters dynamically, the system achieves high adaptability without requiring completely different control strategies for each phase, thus balancing adaptability with manageable complexity.
2Use of energy by moving object
If conventional control methods are used, then the control system is straightforward, but energy efficiency is poor and movement accuracy is limited
Solution Approach 1:
The patent optimizes energy efficiency by dynamically adjusting the weighting factors in the quality functional according to movement phase. For example, during constant speed operation, the system can prioritize energy-saving modes, while during acceleration, it prioritizes performance. This parameter adaptation simultaneously improves energy efficiency and maintains movement accuracy.
Solution Approach 2:
The quality functional incorporates feedback from actual system performance to continuously optimize control decisions. By evaluating deviations from desired behavior and adjusting control parameters accordingly, the system achieves both energy efficiency and high movement accuracy without requiring complex additional hardware.
3Productivity
If a single quality functional is used for all movement phases, then the control system is simple, but it cannot achieve optimal performance across different operational requirements
Solution Approach 1:
The patent implements a dynamic quality functional that adapts its weighting factors based on movement phase and control objectives. This dynamic approach allows the system to achieve optimal performance for each phase (acceleration, constant speed, deceleration) while maintaining a unified control structure, thus improving productivity without excessive complexity.
Solution Approach 2:
The patent creates a universal control framework that handles multiple movement phases and control objectives through a single quality functional structure. By making this single functional multi-functional through parameter adaptation, the system achieves high performance across all phases without requiring separate control strategies, balancing productivity and complexity.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
This approach enables more flexible and efficient control of linear motors, allowing for energy-saving operations and precise movement control by optimizing the quality functional and utilizing a reluctance network model.
Implementation Method 1
an electromagnetic field, which interacts with the drive magnets of the transport unit for moving the transport unit, is generated by energizing drive coils
Implementation Method 2
Due to the interaction of the (electro)magnetic fields of the drive magnets and the drive coils, forces act on the secondary part, which forces move the secondary part relative to the primary part
Implementation Method 3
utilizing a reluctance network model
Data Source
AI summary
To control movement of a transport unit of a linear motor, a quality functional J(SG) with quality terms JTk(SG) is used as a function of manipulated variables (SG) of active drive coils. The quality functional J(SG) controlling movement of the transport unit along the stator is optimized with regard to the manipulated variable (SG) to determine optimal manipulated variables (SGopt) for the relevant time step of the control of movement, active drive coils are energized according to the determined optimal manipulated variables (SGopt), and at least two movement phases are provided during the movement of the transport unit along the stator. In the at least two novement phases, different quality functionals J(SG) are used for determining the optimal manipulated variables (SGopt), the different quality functionals J(SG) differing by the number k of the quality terms JTk(SG) used and/or by the quality terms JTk(SG) and/or by the weighting factors kk.