Closed-loop predictive resonance control through adaptive stiffness–damping co-regulation for continuous piezoelectric energy harvesting

Piezoelectric energy harvesting offers a sustainable solution for powering autonomous electronic devices, but conventional harvesters suffer from resonance mismatch under varying vibration frequencies. In this research, a Closed-Loop Predictive Resonance Control with Adaptive Stiffness–Damping Co-Regulation scheme is proposed for continuous and efficient energy harvesting. The goal was to design an intelligent control solution to predict resonance variation, adaptively control stiffness and damping, and optimize energy harvesting during dynamic conditions. The methodology included predictive resonance estimation, adaptive closed loop control, continuous energy harvesting, comparative evaluation, statistical validation with 150 vibration scenarios and 1500 simulation runs. The framework harvested a power of 88.74 mW, output voltage of 21.86 V, energy conversion efficiency of 94.27%, operating bandwidth of 61 Hz, resonance prediction accuracy of 98.84%, tracking error of 0.18 Hz, adaptive response time of 5.34 ms and Root Mean Square Error of 0.074. The statistical analysis showed that the numerical framework proposed in this study is statistically significant and effective compared to benchmark harvesting approaches and provided significant improvement (p < 0.001) under the vibration conditions simulated. The findings presented here are encouraging for future experimental and hardware-level testing for applications in self-powered sensing, IoT, vibration energy harvesting.