Adaptive Engine Control Laws for Stable Nonlinear Plasma Processing
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Solution Overview
Problem
Existing adaptive controllers struggle with stability, scalability, and adaptability in controlling plasma processing systems, particularly due to asynchronous actuator responses and modeling uncertainties, leading to inefficiencies and premature system failures.
Innovation Solution
An adaptive engine that utilizes a series of estimation law modules to estimate model parameters and generate control signals, incorporating a time-varying linear system derived from Lyapunov equations, allowing for real-time adaptation and blending of control signals to manage nonlinear and chaotic systems.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If existing adaptive controllers are used to control plasma processing systems, then basic control functionality is provided, but the controllers lack stability and struggle with nonlinear systems and modeling uncertainties
Solution Approach 1:
The controller dynamically adapts its control law selection based on real-time system conditions. The adaptive engine continuously monitors system state and selects from multiple pre-processed control laws to match current operating conditions, enabling the controller to adapt to nonlinear behaviors while maintaining stability through systematic law selection rather than arbitrary parameter changes.
Solution Approach 2:
The invention changes the fundamental parameter of control law selection by maintaining a library of pre-processed control laws with different characteristics. Instead of adjusting parameters within a single control law, the system switches between different control laws optimized for different operating regimes, providing both stability through proven control strategies and adaptability through selective law switching.
2Adaptability or versatility
If existing adaptive controllers utilize transfer functions to handle control signals, then control functionality is maintained, but the controllers are difficult to scale to arbitrary waveforms and coupled inputs and outputs
Solution Approach 1:
The controller segments the control problem by dividing it into multiple independent control laws, each optimized for specific operating conditions or waveform types. This segmentation allows the system to handle arbitrary waveforms by selecting and combining appropriate segments (control laws) rather than attempting to scale a single monolithic transfer function, reducing the complexity of handling diverse waveforms and coupled inputs/outputs.
Solution Approach 2:
The adaptive engine serves as a universal controller that can handle arbitrary waveforms and coupled MIMO systems by selecting from its library of pre-processed control laws. Each control law in the library can be configured for different waveform types and system configurations, making the overall controller universally applicable to plasma processing systems with various actuator configurations and waveform requirements.
3Adaptability or versatility
If existing adaptive controllers are limited to a single control law, then the controller structure is simple, but the controller lacks adaptability to various situations that may arise within a given recipe
Solution Approach 1:
The controller transitions from a static single control law structure to a dynamic multi-control law system. The adaptive engine continuously evaluates system conditions and dynamically selects the most appropriate control law from its library, enabling the controller to adapt to various situations within a recipe while maintaining a relatively simple overall structure through systematic law selection rather than complex real-time control law generation.
Solution Approach 2:
The adaptive engine acts as an intermediary layer between the multiple pre-processed control laws and the actual control output. This intermediary selectively combines or switches between different control laws based on current system conditions, providing adaptability to various situations while keeping the individual control laws themselves relatively simple and well-structured.
4Reliability
If existing adaptive controllers struggle with unbounded computed control values, then basic control is maintained, but the controllers cannot handle arbitrary input and output bounded disturbances
Solution Approach 1:
The controller applies prior cushioning by pre-processing and bounding control laws before they are selected and applied to the system. Each control law in the library is designed with inherent bounds and constraints to prevent unbounded control values. This preliminary bounding protects the system from arbitrary disturbances while maintaining reliability, as the control laws are already prepared to handle bounded disturbances within their designed operating ranges.
Data Source
AI summary
This disclosure describes systems, methods, and apparatus for an adaptive engine with a bifurcated nonlinear model partially represented by a mapping function. The adaptive engine uses a nonlinear model able to produce a possible control signal via a mapping function. The model also has estimation portion using a time-varying linear system to approximate nonlinear behavior of a power system. A boot up phase can be used wherein the mapping function provides possible control signals based on measured system outputs rather than an estimated model parameter tensor.