Intelligent Automation Control of High-Voltage Power Supplies: Architectural Evolution and Application Breakthroughs

1. Layered Architecture of Automation Control Systems 
The intelligent control system for high-voltage power supplies comprises a closed-loop structure of sensing layer, decision layer, and execution layer: 
Sensing Layer: High-precision voltage/current sensors and temperature probes collect real-time parameters with sampling rates exceeding 100k samples/s and data errors below ±0.05%. 
Decision Layer: Digital signal processors (DSP) or programmable logic controllers (PLC) run adaptive algorithms for microsecond-level responses. For example, in semiconductor testing, DSP adjusts high-voltage output via PID algorithms, maintaining voltage fluctuations at picoampere-level current resolution. 
Execution Layer: High-frequency switching topologies (e.g., Buck-Boost) and modular power units (e.g., PSM technology) reconfigure output within milliseconds by adjusting switching frequency (10kHz–100kHz) or submodule switching. 
2. Evolution of Core Control Algorithms 
To address complex operating conditions, control strategies have evolved from single PID to multimodal fusion: 
Enhanced PID: Feedforward compensation suppresses load disturbances, limiting voltage overshoot to ±0.1% in nuclear fusion power supplies. 
Fuzzy Logic Control: For nonlinear loads (e.g., electrostatic precipitator flashover), dynamic adjustments based on rules like low voltage or current fluctuation prevent model drift failures. 
Multi-Objective Optimization: Particle swarm algorithms balance voltage accuracy (±5mV) and energy consumption in multi-module semiconductor testing, improving efficiency by 15%. 
Table: Comparison of Control Algorithms in Different Scenarios 
| Algorithm Type     | Response Speed | Accuracy | Typical Applications       | 
|-------------------------|---------------------|--------------|--------------------------------| 
| Enhanced PID            | Microsecond        | ±0.1%        | Nuclear Fusion Power | 
| Fuzzy Logic Control     | Millisecond        | ±0.5%        | Flashover Suppression | 
| Multi-Objective (PSO)   | Second-level       | ±0.01%       | Multi-Module Testing | 
3. Precision Control in Critical Applications 
1. Electrostatic Precipitators: Systems respond to arc signals within microseconds. PSM module reconfiguration reduces voltage recovery time to 50ms, increasing dust removal efficiency by 12%. 
2. Semiconductor Wafer Testing: Picoampere-level current resolution at 10kV requires feedforward-feedback control. Temperature drift compensation algorithms reduce yield deviation to <0.01%. 
3. Nuclear Fusion Devices: For 100kV/50A outputs, carrier phase-shift control minimizes ripple from ±0.3% to ±0.05% by coordinating 30 series modules. 
4. Future Trends: AI-Driven Resilience 
Predictive Maintenance: Historical data trains fault models to preempt capacitor aging (increasing ESR) or switch failures, reducing maintenance costs by 30%. 
Heterogeneous Hardware: FPGA+DSP architectures accelerate multi-objective optimization, cutting computational latency from milliseconds to microseconds. 
Modular Redundancy: Hot-swappable submodules with N+1 backup ensure 99.999% availability during single-point failures.