Hydraulic Actuator Supply Control With Knowledge-Based Setpoint Tuning
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Solution Overview
Problem
Existing hydraulic systems face challenges in optimizing energy consumption and dynamic behavior due to the complexity of operating systems with adjustable displacement units and variable-speed drives, and existing optimization methods require additional system parameters.
Innovation Solution
Implementing a knowledge-based decision system, such as fuzzy logic or a neural network, to set speed and displacement volume setpoints, optimizing these parameters based on expert knowledge, simulations, and experiments to improve energy consumption and dynamic behavior.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Use of energy by moving object
If a model-based optimization problem is integrated into the control system to improve energy consumption, then energy efficiency is improved, but device complexity increases due to additional system parameters required
Solution Approach 1:
The patent replaces complex model-based optimization algorithms with a knowledge-based decision system that uses fuzzy logic and neural networks. This substitution simplifies the control architecture by using pattern recognition and expert knowledge stored in knowledge bases, rather than requiring real-time solution of complex optimization problems with multiple system parameters.
Solution Approach 2:
The knowledge-based decision system autonomously determines optimal control actions by querying its internal knowledge base and applying fuzzy logic rules, without requiring external optimization models or additional system parameters. The system serves itself by using pre-stored expert knowledge to make real-time decisions.
2Manufacturing precision
If the delivery system with two adjustable parameters is operated to achieve the specified size profile, then the size profile accuracy is improved, but ease of operation deteriorates due to difficulty in optimal operation
Solution Approach 1:
The patent introduces a knowledge-based decision system as an intermediary between the operator and the complex delivery system. This intermediary automatically coordinates the two adjustable parameters (displacement volume and drive speed) based on the specified size profile, eliminating the need for operators to manually optimize multiple parameters while maintaining accurate size profile achievement.
Solution Approach 2:
The system automatically adjusts the two adjustable parameters (displacement volume and drive speed) based on the specified size profile and knowledge base rules. By automating parameter changes, the system maintains precise size profile accuracy while eliminating the operational difficulty of manually coordinating multiple parameters.
3Ease of manufacture
If commissioning is simplified, then ease of manufacture is improved, but productivity may deteriorate due to reduced optimization capability
Solution Approach 1:
The patent performs optimization work in advance by pre-populating the knowledge base with expert knowledge, fuzzy logic rules, and neural network training data. This preliminary action allows the system to be commissioned simply without complex setup, while still maintaining high optimization capability during operation through the pre-prepared knowledge base.
Data Source
Figure 1
AI summary
The present invention relates to a method for adjusting a pressure medium supply for at least one hydraulic actuator (1), wherein the actuator (1) is supplied with a pressure medium by a displacement unit (2) adjustable in its displacement volume, the displacement unit (2) is driven by a variable-speed drive (3) and a quantity of pressure medium to be supplied to the actuator is predetermined by a size profile (4), wherein a speed setpoint value of the drive (3) and/or a setpoint value for the displacement volume of the displacement unit (2) is set taking into account a knowledge-based decision system. The invention also relates to a hydraulic system.