Adaptive Fuzzy Plasma Control for Asynchronous Actuators
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Solution Overview
Problem
Existing plasma processing systems face challenges with actuators responding asynchronously, leading to inefficiencies, overheating, and premature system failure due to inconsistent control over high-level and low-level actuators, and current adaptive controllers lack stability, scalability, and adaptability to handle nonlinear and uncertain systems.
Innovation Solution
A control system utilizing a fuzzy controller with an adaptive engine that adjusts actuators based on a reference signal, sensor measurements, and an estimation law module to adapt membership functions and rule bases, enabling precise control of plasma processing systems.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If existing adaptive controllers are used to control plasma processing systems, then control capability is provided, but stability and reliability are insufficient due to lack of convergence guarantee and handling of unbounded disturbances
Solution Approach 1:
The controller employs dynamic adaptation of control parameters through fuzzy logic rules that continuously adjust membership functions and rule bases based on real-time system state, enabling the controller to adapt to nonlinear plasma processes while maintaining stability through bounded control outputs
Solution Approach 2:
The system changes parameters by adapting membership function shapes and rule base configurations in real-time based on system performance and disturbances, allowing the controller to handle nonlinear and uncertain plasma processing conditions while maintaining reliability through bounded control actions
2Productivity
If actuators operate asynchronously with different response times, then system flexibility is maintained, but control precision deteriorates leading to inefficiency and overheating
Solution Approach 1:
The controller predicts future system states and adjusts control signals in advance to compensate for actuator response time differences, allowing fast and slow actuators to work together more effectively and preventing overheating by anticipating power delivery requirements
Solution Approach 2:
The system uses real-time feedback from plasma process measurements to continuously adjust control signals to multiple actuators with different response times, coordinating their operation to achieve precise power delivery and improve both efficiency and control precision
3Power
If rail voltage is held at high level for most of pulse cycle to ensure power availability, then power delivery capability is maintained, but energy consumption increases and overheating occurs
Solution Approach 1:
The controller implements periodic pulse cycling with varying duty cycles, adjusting rail voltage levels dynamically within each pulse cycle to provide necessary power only when needed, reducing energy dissipation while maintaining power delivery capability through optimized pulse timing and amplitude
Solution Approach 2:
The system dynamically adjusts rail voltage levels in real-time based on actual plasma power requirements, transitioning between different voltage states within pulse cycles to maintain adequate power delivery capability while minimizing energy consumption and preventing overheating
Data Source
AI summary
Fuzzy control systems and methods are disclosed. A method includes receiving a reference signal defining target values for a parameter that is controlled at an output of the plasma processing system and obtaining a measure of the parameter that is controlled at the output. A fuzzy controller provides a control signal to adjust at least one actuator based at least upon the reference signal and the measure of the controlled parameter. In addition, output membership functions of the fuzzy controller, input membership functions of the fuzzy controller, and a rule base of the fuzzy controller are adapted while controlling an output of a system based at least upon the based at least upon an estimated model parameter tensor, the reference signal and the measure of the controlled parameter, and the control signal.