Rehman Shania, Khan Muhammad Farooq, Kim Hee-Dong, Kim Sungho
Department of Semiconductor Systems Engineering and Convergence Engineering for Intelligent Drone, Sejong University, Seoul, 05006, Korea.
Department of Electrical Engineering, Sejong University, Seoul, 05006, Korea.
Nanoscale. 2023 Aug 25;15(33):13675-13684. doi: 10.1039/d2nr06853b.
Most commercial drones utilize a traditional proportional-integral-derivative (PID) controller because of its design simplicity. However, the traditional PID controller has certain limitations in terms of optimality and robustness; it is difficult to actively adjust the PID gains under some disturbances. In this study, we demonstrated an analog-digital hybrid computing platform based on double-gate SnS memtransistors to implement a self-tuning/energy-efficient PID controller in drones. The customized analog circuit with memtransistors executes the PID control algorithm with low power consumption; we experimentally verified that the energy consumption of the proposed hybrid computing-based PID controller is only 63% of that of the traditional PID controller. In addition, the precise tunability of analog conductance states in the memtransistor proved to be capable of reconfiguring the performance of the PID controller, where the developed self-tuning algorithm can automatically find the optimal PID control performance.
大多数商用无人机采用传统的比例-积分-微分(PID)控制器,因为其设计简单。然而,传统的PID控制器在最优性和鲁棒性方面存在一定局限性;在某些干扰下,很难主动调整PID增益。在本研究中,我们展示了一种基于双栅极硫化锡忆阻器的模拟-数字混合计算平台,以在无人机中实现自整定/节能PID控制器。带有忆阻器的定制模拟电路以低功耗执行PID控制算法;我们通过实验验证,所提出的基于混合计算的PID控制器的能耗仅为传统PID控制器的63%。此外,忆阻器中模拟电导状态的精确可调性被证明能够重新配置PID控制器的性能,其中开发的自整定算法可以自动找到最优的PID控制性能。