The core digital control algorithms serve as the “brain” of high‑voltage power supplies, determining output accuracy, dynamic response speed, stability and anti‑interference capability. They eliminate the inherent drawbacks of analog loops, such as fixed parameters, complicated tuning and poor adaptability, supporting linear regulation, switching regulation, resonant conversion, pulsed discharge and all mainstream topologies. Digital algorithm and loop optimization face eight core technical challenges.
First, nonlinear control for high‑voltage topologies. Transformers, rectifiers, high‑voltage regulators and capacitive loads introduce strong nonlinearity; conventional linear PID easily causes overshoot, oscillation and slow response across wide operating ranges. Second, stability under full working conditions. Power supplies must operate stably from no‑load to full‑load with input voltage ranging 60%–150% of rated value, requiring highly robust control with optimal dynamics in all scenarios. Third, microsecond fast dynamic response. Applications such as new energy, laser and medical equipment demand response ≤50 μs and voltage fluctuation ≤±2% during load steps, imposing extreme requirements on algorithm speed and loop bandwidth. Fourth, high precision and low drift. Metrology‑grade supplies require output accuracy better than ±0.01% and long‑term stability ≤±0.01% per 8 hours, relying on precise sampling processing, nonlinear compensation and temperature drift suppression. Fifth, robustness against strong EMI. Severe field noise contaminates sampled signals; algorithms must suppress interference to avoid output fluctuation and false protection triggering. Sixth, precise soft‑switching and resonant control. LLC and series resonant topologies require fast accurate frequency tracking to maintain ZVS/ZCS; traditional PID often fails, raising losses and risking device damage. Seventh, decoupling for multi‑input multi‑output systems. Multi‑output and series‑stacked high‑voltage structures feature strong cross‑channel coupling; single‑loop control leads to crosstalk and instability. Eighth, algorithm portability and standardization. Traditional control logic lacks universality across topologies and power ratings, causing heavy tuning workload; modular standardized algorithms are required for rapid migration and consistent mass production.
To address these challenges, the methodology establishes a universal framework: modular layered algorithm architecture + hybrid linear‑nonlinear control + full‑range adaptive loop optimization. It adapts to all high‑voltage topologies while achieving high precision, fast response and high stability throughout all operating conditions, overcoming poor robustness and complicated tuning in conventional solutions. The design follows eight core principles. First, a four‑layer modular structure comprises bottom driver layer (ADC, PWM, communication, I/O), core control layer (voltage/current loops and topology adaptation), application function layer (calibration, timing, protocol and health management), and safety protection layer (hardware safeguards, software redundancy and fault diagnosis). Standardized interfaces ensure easy portability and scalability. Second, optimized high‑precision PID combines incremental and positional PID to avoid integral saturation and overshoot, adopting integral separation, variable integration amplitude limiting and segmented parameter scheduling across input and load ranges. Automatic parameter switching guarantees optimal dynamic performance under all conditions. Third, nonlinear adaptive control integrates sliding mode control, model predictive control and fuzzy PID on the basis of PID. Accurate system modeling and feedforward compensation for input voltage and load current accelerate dynamics by more than five times compared with traditional PID, achieving voltage deviation ≤±2% and settling time ≤50 μs during load transients. Fourth, resonant frequency tracking for soft switching employs PLL‑based adaptive detection of resonant voltage and current phase to maintain inductive operating margins, ensuring ZVS on primary switches and ZCS on rectifiers across wide input and load ranges. Hybrid frequency‑plus‑phase‑shift control minimizes switching losses. Fifth, high‑precision sampling and noise suppression adopt multi‑stage digital filtering combining moving average, median filtering and Kalman algorithms to eliminate pulse interference, power‑frequency noise and high‑frequency ripple. Calibration compensates ADC nonlinearity, zero drift and gain error, ensuring sampling accuracy ≤±0.01%. Differential sampling and digital common‑mode rejection achieve common‑mode suppression ≥120 dB. Sixth, decoupling control for multi‑channel and series systems builds MIMO decoupling models with feedforward decoupling matrices to eliminate crosstalk ≤0.001%. Distributed cooperative control ensures current/voltage balancing ≤±2% in parallel and stacked systems. Seventh, full‑temperature full‑range precision calibration establishes a three‑dimensional correction model calibrated across −40 ℃~+70 ℃ and 0~100% output range. Stored parameters compensate temperature drift, nonlinearity and load regulation in real time, delivering steady accuracy better than ±0.01% and temperature coefficient ≤±1 ppm/℃. Eighth, loop stability optimization analyzes z‑domain frequency response via Bode plots to maintain phase margin ≥45° and gain margin ≥10 dB. Adaptive loop compensation dynamically adjusts bandwidth according to load characteristics (resistive, inductive, capacitive), ensuring strong robustness against grid fluctuation, load stepping and electromagnetic interference.