Control of a 3D piezo-actuating table by using an adaptive sliding-mode controller for a drilling process

AbstractRecently, the micropositioner has become an important developing target for achieving the requirements of precision machinery. The piezo-actuating device plays a very important role in this application area. In this paper, a model-free adaptive sliding-mode controller is proposed for a 3D piezo-actuating system because of the system’s hysteresis nonlinearity and time-varying characteristics. This control strategy employs the functional approximation technique to establish the unknown function for releasing the model based requirements of the sliding-mode control. The update laws for the coefficients of the Fourier series function parameters are derived from a Lyapunov function to guarantee the control system stability. To verify the effectiveness of the proposed controller, drilling process control using the designed controller is investigated in this paper

Adaptive Temporal Encoding Network for Video Instance-level Human Parsing

Beyond the existing single-person and multiple-person human parsing tasks in static images, this paper makes the first attempt to investigate a more realistic video instance-level human parsing that simultaneously segments out each person instance and parses each instance into more fine-grained parts (e.g., head, leg, dress). We introduce a novel Adaptive Temporal Encoding Network (ATEN) that alternatively performs temporal encoding among key frames and flow-guided feature propagation from other consecutive frames between two key frames. Specifically, ATEN first incorporates a Parsing-RCNN to produce the instance-level parsing result for each key frame, which integrates both the global human parsing and instance-level human segmentation into a unified model. To balance between accuracy and efficiency, the flow-guided feature propagation is used to directly parse consecutive frames according to their identified temporal consistency with key frames. On the other hand, ATEN leverages the convolution gated recurrent units (convGRU) to exploit temporal changes over a series of key frames, which are further used to facilitate the frame-level instance-level parsing. By alternatively performing direct feature propagation between consistent frames and temporal encoding network among key frames, our ATEN achieves a good balance between frame-level accuracy and time efficiency, which is a common crucial problem in video object segmentation research. To demonstrate the superiority of our ATEN, extensive experiments are conducted on the most popular video segmentation benchmark (DAVIS) and a newly collected Video Instance-level Parsing (VIP) dataset, which is the first video instance-level human parsing dataset comprised of 404 sequences and over 20k frames with instance-level and pixel-wise annotations.Comment: To appear in ACM MM 2018. Code link: https://github.com/HCPLab-SYSU/ATEN. Dataset link: http://sysu-hcp.net/li

Active control for non-autonomous diaphragm-type pneumatic isolation system by using an augmented adaptive sliding-mode controller

An augmented adaptive sliding-mode controller is proposed in this paper for a diaphragm-type pneumatic vibration isolation (PVI) system containing nonlinear characteristics and time-varying uncertainties with unknown bounds. To capture and deal with the time-varying uncertainties, a controller design based primarily on the functional approximation (FA) technique complemented with an adaptive fuzzy sliding-mode control (AFSMC) is adopted. The resultant hybrid design is denoted as FA+AFSMC to differentiate itself from other attempting solutions. Lyapunov stability theory is utilized not only to stabilize the closed-loop system but also to formulate updating laws for weighting coefficients of the FA and tuning parameters of the AFSMC. This developed scheme has online learning ability when it faces the system’s nonlinear and time-varying behaviors. Experimental explorations which incorporates both pressure and velocity measurements as feedback signals reveals that the proposed FA+AFSMC scheme outperforms other attempting solutions, such as passive isolation and pure AFSMC scheme, by a significant margin