Restoring the correct masticatory function of broken teeth is the basis of dental crown prosthesis rehabilitation. However, it is a challenging task primarily due to the complex and personalized morphology of the occlusal surface. In this article, we address this problem by designing a new two-stage generative adversarial network (GAN) to reconstruct a dental crown surface in the data-driven perspective. Specifically, in the first stage, a conditional GAN (CGAN) is designed to learn the inherent relationship between the defective tooth and the target crown, which can solve the problem of the occlusal relationship restoration. In the second stage, an improved CGAN is further devised by considering an occlusal groove parsing network (GroNet) and an occlusal fingerprint constraint to enforce the generator to enrich the functional characteristics of the occlusal surface. Experimental results demonstrate that the proposed framework significantly outperforms the state-of-the-art deep learning methods in functional occlusal surface reconstruction using a real-world patient database. Moreover, the standard deviation (SD) and root mean square (RMS) between the generated occlusal surface and the target crown calculated by our method are both less than 0.161 mm. Importantly, the designed dental crown have enough anatomical morphology and higher clinical applicability.

This paper presents the design, analysis, and verification of a novel reaching law for discrete-time sliding-mode control. The control gains of the reaching law are automatically regulated by the power function and the exponential term that dynamically adapts to the variation of the switching function. The reaching law also employs the perturbation estimation and the difference function to redefine the change rate as the second-order difference of the uncertainties. Compared with previous methods, the proposed reaching law has the capability to amend the control gains in a wise manner, further mitigate chattering and guarantee smaller width of the quasi-sliding-mode domain (QSMD). In order to describe the system dynamics in the reaching phase and the sliding phase with respect to control gain values, both the decrement band and the QSMD (ultimate band) of the proposed reaching law are theoretically analyzed. The reaching steps for the switching function to converge toward the sliding surface are also obtained. The effectiveness of the proposed method is verified through numerical simulations and experimental investigations on a piezoelectric actuator.

In this paper, a novel dead zone sliding mode reaching law with disturbance compensation is developed for uncertain discrete-time systems. The reaching law is established based on the dead zone function and a high-order disturbance compensator, which estimates and compensates the disturbance by the high-order difference function. The exponential function, which is constructed based on the switching function, is employed to regulate the control gains. Different from existing similar works, the presented new reaching law has the ability to obtain a quasi-sliding mode (QSM) with an adjustable order O(T $^n+1$ ) boundary layer. Hence, much smaller ultimate magnitude of the quasi-sliding mode domain (QSMD) can be guaranteed and the chattering can be further mitigated. Moreover, system dynamics in and out the decrement band and the QSMD is theoretically analyzed. Numerical simulations are employed to demonstrate the superiority of the developed new method.

This article reports the design and validation of a novel predefined-time barrier function adaptive sliding-mode control (PTBFASMC) strategy for robust control of disturbed systems. The PTBFASMC strategy is established by integrating the time base generator along with the barrier function. Unlike existing similar works, the proposed method enables global predefined-time convergence, i.e., the system trajectory returns to the ultimate bound even if an escape occurs at a certain time instant. Besides, the convergence time can be predefined by the user, which is independent of the initial conditions and disturbance. Moreover, the reaching phase is eliminated and the magnitude of initial control output is zero. Another attractive feature of the proposed method lies in that the ultimate bound can be predefined, i.e., the ultimate bound is independent of the upper bound of disturbance. To avoid large control magnitude, a modified control strategy is provided, which extends the proposed scheme to different scenarios. The stability of the control system is demonstrated, and its superiority is verified through numerical simulations and experimental investigations on a piezoelectric actuator.