This study presents a new fuzzy logic controller (FLC) for micro-electro-mechanical-system gyroscopes (MEMS-Gs). The nonlinearities and unknown dynamics are modeled by the designed non-singleton type-3 fuzzy system (NT3FS) and an adaptive control scheme is presented. To improve the control accuracy, the tracking error dynamics are identified by a deep learned Boltzmann machine (RBM) and the nonlinear model predictive controller (NMPC) is designed by the optimized RBM model. Finally, the approximation errors are tackled by an adaptive compensator. The parameters of RBM are learned by contrastive divergence (CD) method and rules of NT3FS are optimized by the tuning laws that are obtained through the stability investigation. In various simulations and comparisons with some other conventional FLCs the superiority of the designed controller is shown. A good tracking accuracy of chaotic references and well robustness performance are obtained by the suggested control scheme.

本研究提出了一种用于微机电系统陀螺仪 (MEMS-G) 的新型模糊逻辑控制器 (FLC)。非线性和未知动力学由设计的非单一类型 3 模糊系统 (NT3FS) 建模，并提出了自适应控制方案。为了提高控制精度，通过深度学习的玻尔兹曼机（RBM）识别跟踪误差动力学，并通过优化的RBM模型设计非线性模型预测控制器（NMPC）。最后，近似误差由自适应补偿器解决。RBM 的参数是通过对比散度 (CD) 方法学习的，NT3FS 的规则是通过稳定性调查获得的调整规律来优化的。在各种模拟和与一些其他传统 FLC 的比较中，显示了所设计控制器的优越性。