Control device, control system, and control method
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Solution Overview
Problem
Existing control methods, such as modern control and optimization techniques, face challenges in achieving precise control at target time without causing energy loss due to the controlled variable reaching the target value earlier than expected, and struggle with calculating optimal manipulated variables in complex systems.
Innovation Solution
A control device that combines modern control and optimization techniques by using a simulator to calculate stepwise target values and setting values through optimization, followed by modern control algorithms to adjust manipulated variables based on sensor feedback, ensuring the controlled variable reaches the target value at the desired time while minimizing energy consumption.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If modern control is used to calculate manipulated variable so that controlled variable reaches target value at target time, then control precision is improved, but energy loss occurs due to controlled variable quickly reaching target value
Solution Approach 1:
The patent divides the target value into multiple step target values that are applied sequentially over time. Instead of directly reaching the final target value, the controlled variable progresses through intermediate targets (first step target value, second step target value, etc.), which prevents overshooting and reduces energy consumption while maintaining control precision.
2Loss of energy
If optimization technique is used to calculate optimal control input, then energy consumption is reduced, but it is difficult to precisely calculate manipulated variable for continuous optimization
Solution Approach 1:
The patent combines optimization techniques with modern control methods. The optimization technique determines the step target values and timing to minimize energy consumption, while modern control (LQR) calculates the precise manipulated variables to track these step targets. This hybrid approach achieves both energy efficiency and precise manipulated variable calculation.
3Loss of energy
If capacity is reduced to perform highly efficient operation, then energy efficiency is improved, but control precision may deteriorate
Solution Approach 1:
The patent dynamically adjusts the manipulated variable based on the current state and the step target values. The LQR controller continuously calculates optimal control inputs that balance energy efficiency with maintaining control precision, allowing the system to operate efficiently at reduced capacity while still achieving precise target tracking through adaptive control.
Data Source
Figure 1A~1B
Figure 2
Figure 3A~3B
AI summary
An optimization unit (13) that calculates, by optimization calculation, control data including a step target value on the basis of a simulation result obtained by causing a simulator unit (21) to execute simulation, an optimal control computing unit (14) that activates a control target device (4), collects sensor data related to a controlled variable measured after the activation of the control target device (4), and calculates a manipulated variable of the control target device (4) on the basis of the collected sensor data in such a manner that the controlled variable follows the step target value calculated by the optimization unit (13), and a control unit (15) that controls the control target device (4) with the manipulated variable calculated by the optimal control computing unit (14) are included.