LQI Controller for Electromagnetic Coil Systems
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Conventional closed-loop control methods for electromagnetic coil systems (ECS) are challenging due to sensitivity to system uncertainties and external disturbances, leading to inaccurate dynamic magnetic field generation, especially at high frequencies, and are difficult to implement across diverse ECS configurations.
Innovation Solution
A method involving a dynamic model with a unified state-space form and time delay is established, using linear quadratic with integral action (LQI) control, combined with feedback signals from electric current, magnetic flux density, or displacement, to update control signals and achieve precise dynamic magnetic field control.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If conventional PID control is applied to ECS, then closed-loop control is achieved, but the system becomes sensitive to system uncertainties and external disturbances, resulting in large overshoot and settling time
Solution Approach 1:
The patent changes the control parameters by using LQI control with an augmented state-space model that includes integral action. This transforms the conventional PID control parameters into a state-space framework with matrices A, B, C, D and weighting matrices Q and R, allowing optimization of both accuracy and settling time through parameter tuning in the cost function J = ∫(x^TQx + u^TRu)dt
Solution Approach 2:
The patent substitutes the conventional PID control mechanism with a model-based LQI control system. This replacement uses a dynamic state-space model of the ECS to compute optimal control signals, replacing the simple proportional-integral-derivative mechanics with a more sophisticated state-space optimization approach that considers system dynamics and uncertainties
2Measurement precision
If model-based control is applied to ECS, then control accuracy is improved, but the device complexity increases due to diverse ECS configurations
Solution Approach 1:
The patent creates a universal state-space model that can represent different ECS configurations (single coil, dual coil, triple coil systems) through a unified mathematical framework. The model uses general matrices A, B, C, D that can be configured for various coil arrangements, making the LQI control approach applicable to multiple ECS types without requiring separate control designs for each configuration
Solution Approach 2:
The patent segments the complex ECS into manageable state variables and control inputs that can be represented in the state-space model. By dividing the system into discrete states (coil currents, magnetic field components) and control inputs (voltages applied to each coil), the complex control problem is broken down into solvable matrix equations that can be handled systematically
3Speed
If high-frequency magnetic fields are generated by ECS, then microrobot actuation capability is improved, but the output magnetic field diverges from the input command due to coil inductance effects
Solution Approach 1:
The patent applies preliminary action by using the dynamic state-space model to predict and compensate for coil inductance effects before they cause divergence. The model-based LQI controller anticipates the system's response to high-frequency commands and adjusts the control signals in advance, preventing the magnetic field output from diverging from the input command even at high frequencies
Solution Approach 2:
The patent implements feedback by using the state-space model to continuously monitor system states and adjust control signals accordingly. The LQI controller uses feedback from the augmented state (including integral of error) to compute optimal control inputs that maintain accuracy despite coil inductance effects at high frequencies, ensuring the magnetic field follows the desired trajectory
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 high-accuracy dynamic magnetic field generation with reduced overshoot and settling time, improving the control of magnetic microrobots and other applications by adapting to different ECS configurations and minimizing noise and system chattering.
Implementation Method 1
an electromagnetic coil system (ECS) is used to generate a real-time-controlled dynamic magnetic field
Data Source
AI summary
Disclosed are methods and apparatus for controlling electromagnetic field generation system to generate dynamic magnetic fields. The method can comprise: establishing a dynamic model that describes open-loop dynamics of the electromagnetic field generation system and has an unified state-space form with time delay; configuring a controller based on the dynamic model; applying, by the controller, a control signal to the electromagnetic field generation system; detecting one or more feedback signals from the electromagnetic field generation system; and updating, by the controller, the control signal for controlling the electromagnetic field generation system, according to a reference signal corresponding to a desired dynamic magnetic field, one or more compensated feedback signals, and system states. To address time delay and modeling error and to estimate system states, a Kalman filter and a Smith predictor based compensator can be incorporated.