In the pattern recognition domain, deep architectures are currently widely used and they have achieved fine results. However, these deep architectures make particular demands, especially in terms of their requirement for big datasets and GPU. Aiming to gain better results without deep networks, we propose a simplified algorithm framework using fusion features extracted from the salient areas of faces. Furthermore, the proposed algorithm has achieved a better result than some deep architectures. For extracting more effective features, this paper firstly defines the salient areas on the faces. This paper normalizes the salient areas of the same location in the faces to the same size; therefore, it can extracts more similar features from different subjects. LBP and HOG features are extracted from the salient areas, fusion features’ dimensions are reduced by Principal Component Analysis (PCA) and we apply several classifiers to classify the six basic expressions at once. This paper proposes a salient areas definitude method which uses peak expressions frames compared with neutral faces. This paper also proposes and applies the idea of normalizing the salient areas to align the specific areas which express the different expressions. As a result, the salient areas found from different subjects are the same size. In addition, the gamma correction method is firstly applied on LBP features in our algorithm framework which improves our recognition rates significantly. By applying this algorithm framework, our research has gained state-of-the-art performances on CK+ database and JAFFE database.

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A novel energy-coupling-based control method for under-actuated double-pendulum overhead cranes with initial control force constraint is proposed in this article. The significant feature of the designed controller is its superior control performance as well as its strong robustness with respect to parameter variations and external disturbances. By incorporating a smooth hyperbolic tangent function into the control law, the proposed controller guarantees soft start of the trolley. Moreover, to improve the transient performance of the crane system, coupling behavior among the trolley movement, the hook swing, and the payload swing is enhanced by introducing a generalized payload horizontal-displacement signal. Lyapunov techniques and LaSalle's invariance theorem are utilized to prove the stability of the designed closedloop system. Simulation results demonstrate that the new energy-coupling control method achieves superior control performance and strong robustness over different payload masses, cable lengths, desired positions, and external disturbances with reduced initial control force.

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There are two main categories of force control schemes: hybrid position-force control and impedance control. However, the former does not take into account the dynamic interaction between the robot's end effector and the environment. In contrast, impedance control includes regulation and stabilization of robot motion by creating a mathematical relationship between the interaction forces and the reference trajectories. It involves an energetic pair of a flow and an effort, instead of controlling a single position or a force. A mass-spring-damper impedance filter is generally used for safe interaction purposes. Tuning the parameters of the impedance filter is important and, if an unsuitable strategy is used, this can lead to unstable contact. Humans, however, have exceptionally effective control systems with advanced biological actuators. An individual can manipulate muscle stiffness to comply with the interaction forces. Accordingly, the parameters of the impedance filter should be time varying rather than value constant in order to match human behavior during interaction tasks. Therefore, this paper presents an overview of impedance control strategies including standard and extended control schemes. Standard controllers cover impedance and admittance architectures. Extended control schemes include admittance control with force tracking, variable impedance control, and impedance control of flexible joints. The categories of impedance control and their features and limitations are well introduced. Attention is paid to variable impedance control while considering the possible control schemes, the performance, stability, and the integration of constant compliant elements with the host robot.

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An enhanced coupling nonlinear tracking control method for an underactuated 3D overhead crane systems is set forth in the present paper. The proposed tracking controller guarantees a smooth start for the trolley and solves the problem of the payload swing angle amplitude increasing as the transferring distance gets longer for the regulation control methods. Different from existing tracking control methods, the presented control approach has an improved transient performance. More specifically, by taking the operation experience, mathematical analysis of the overhead crane system, physical constraints, and operational efficiency into consideration, we first select two desired trajectories for the trolley. Then, a new storage function is constructed by the introduction of two new composite signals, which increases the coupling behaviour between the trolley movement and payload swing. Next, a novel tracking control strategy is designed according to the derivation form of the aforementioned storage function. Lyapunov techniques and Barbalat's Lemma are used to demonstrate the stability of the closed‐loop system without any approximation manipulations to the original nonlinear dynamics. Finally, some simulation and experiments are used to demonstrate the superior transient performance and strong robustness with respect to different cable lengths, payload masses, destinations, and external disturbances of the enhanced coupling nonlinear tracking control scheme.

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