How do you implement adaptive control systems for time-varying processes?

Adaptive control automatically adjusts parameters for changing process dynamics. Approaches: self-tuning regulators (continuous model identification + tuning recalculation), model reference adaptive control (adjust parameters to match reference model response), gain scheduling (pre-computed tuning vs measured operating condition), and extremum seeking (optimize performance metric continuously). Implementation considerations: identification excitation requirements, stability during adaptation, parameter bounds to prevent unrealistic values, and when to trigger adaptation. Applications: processes with varying composition, throughput-dependent dynamics, or seasonal variations. Test thoroughly before deploying to prevent instability.