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In most working scenarios of tower cranes, the load swings around the hooks, resulting in a double-pendulum effect. This makes the tower crane more underactuated and nonlinear, and thus more difficult to control. To solve these problems, we design an improved Active Disturbance Rejection Controller (I-ADRC). First, we propose a smooth and non-linear function to reduce the high-frequency oscillation of the system at steady-state and avoid the “chattering” phenomenon. Second, we construct a new type of Extended State Observer (ESO) to improve the dynamic response performance of the system. Then we prove that the closed-loop system is asymptotically stable under reasonable parameters by using the Hurwitz criterion and Lyapunov technique. Numerical simulation results show that our proposed controller has superior control performance and strong robustness.

Thrusters are the bottom actuators of the amphibious spherical robot, and play an important role in the motion control of these robots. To realize accurate motion control, a thrust model for a new water-jet thruster based on hydrodynamic analyses is proposed in this paper. First, the hydrodynamic characteristics of the new thruster were numerically analyzed using computational fluid dynamics (CFD) commercial software CFX. The moving reference frame (MRF) technique was utilized to simulate propeller rotation. In particular, the hydrodynamics of the thruster were studied not only in the axial flow but also in oblique flow. Then, the basic framework of the thrust model was built according to hydromechanics theory. Parameters in the basic framework were identified through the results of the hydrodynamic simulation. Finally, a series of relevant experiments were conducted to verify the accuracy of the thrust model. These proved that the thrust model-based simulation results agreed well with the experimental results. The maximum error between the experimental results and simulation results was only 7%, which indicates that the thrust model is precise enough to be utilized in the motion control of amphibious spherical robots.

This paper designs a novel legged, multi-vectored water-jet composite driving mechanism (LMWCDM) for the amphibious spherical robot (ASRobot) and presents modeling and experimental evaluation of this composite driving mechanism. In order to crawl on land flexibly, the robot was designed in SolidWorks and simulated in ADAMS environment with the sit to stand motion and a crawling gait. Then the simulation results, such as driving torques, guided the selection of servomotors in different joints. In aquatic environment, the dynamic modeling of ASRobot was analyzed by synthesizing the propulsive vectors of four propellers in each workspace of legs. Simplistically, multiple underwater locomotion, such as longitudinal and lateral motion, rotary motion, sinking and floating motion and cruising motion, were proposed. Thus, using a six-axis force/torque sensor at the equivalent mass center, a force and torque measuring mechanism was developed to obtain the direct propulsive effect and validate the modeling of the driving system. To evaluate the robot design and selection of servomotors, experiments of the sit to stand motion and crawling motion were conducted. Underwater testing experiments of LMWCDM were carried out to verify the modeling of rotary motion, sinking and floating motion. Besides, underwater test of the robot prototype also proved the highly flexible and swift motion.

When the double pendulum crane works in three-dimensional motion mode, it can significantly improve transportation efficiency. However, controlling the two-stage swing angles in the three-dimensional motion mode is complex and challenging. This paper presents a coordinated control method for the track and trolley of the double pendulum crane to improve the working efficiency of the crane, which realizes the anti-swing control of the double pendulum crane in three-dimensional movement mode. A three-dimensional double pendulum crane model is established, and the model is simplified by the differential flatness theory. A sliding mode control (SMC) method with an extended state observer (ESO) is designed to position and two-stage swing suppression of the three-dimensional double pendulum crane. For the actuator deadband, a transition process is introduced. The stability of the system is analyzed by the Lyapunov method. The proposed method has strong robustness and anti-interference ability. Theoretical and experimental results show that the proposed method can achieve fast and accurate positioning and effectively suppress the two-stage swing. This method is introduced into a nonlinear experimental platform. Compared with other technologies in the literature, the proposed method shortens the transit time, improves work efficiency, and reduces the safety risk.

Hilbert-Huang transform is widely used in signal analysis. However, due to its inadequacy in estimating both the maximum and the minimum values of the signals at both ends of the border, traditional HHT is easy to produce boundary error in empirical mode decomposition (EMD) process. To overcome this deficiency, this paper proposes an enhanced empirical mode decomposition algorithm for processing complex signal. Our work mainly focuses on two aspects. On one hand, we develop a technique to obtain the extreme points of observation interval boundary by introducing the linear extrapolation into EMD. This technique is simple but effective in suppressing the error-prone effects of decomposition. On the other hand, a novel envelope fitting method is proposed for processing complex signal, which employs a technique of nonuniform rational B-splines curve. This method can accurately measure the average value of instantaneous signal, which helps to achieve the accurate signal decomposition. Simulation experiments show that our proposed methods outperform their rivals in processing complex signals for time frequency analysis.

Direct and selective functionalization of hydrocarbon chains is a fundamental problem in synthetic chemistry. Conventional functionalization of C=C double bonds and C(sp3)–H bonds provides some solutions, but site diversity remains an issue. The merging of alkene isomerization with (oxidative) functionalization provides an ideal method for remote functionalization, which would provide more opportunities for site diversity. However, the reported functionalized sites are still limited and focus on a specific terminal position and internal site; new site-selective functionalization, including multi-functionalization, remains a largely unmet challenge. Here we describe a palladium-catalysed aerobic oxidative method for the multi-site programmable functionalization, involving the C=C double bond and multiple C(sp3)–H bonds, of terminal olefins via a strategy that controls the reaction sequence between alkene isomerization and oxidative functionalization. Specifically, 1-acetoxylation (anti-Markovnikov), 2-acetoxylation, 1,2-diacetoxylation and 1,2,3-triacetoxylation have been realized, accompanied by controllable remote alkenylation. This method enables available terminal olefins from petrochemical feedstocks to be readily converted into unsaturated alcohols and polyalcohols and particularly into different monosaccharides and C-glycosides.The diverse site-selective functionalization, including multi-functionalization, of C=C double bonds and C(sp3)–H bonds remains a largely unmet challenge. Now, a palladium-catalysed aerobic oxidative method has been developed for the multi-site programmable functionalization of terminal olefins via a strategy that controls the reaction sequence between alkene isomerization and oxidative functionalization.

The problem of optimizing a quadratic form over an orthogonality constraint (QP-OC for short) is one of the most fundamental matrix optimization problems and arises in many applications. In this paper, we characterize the growth behavior of the objective function around the critical points of the QP-OC problem and demonstrate how such characterization can be used to obtain strong convergence rate results for iterative methods that exploit the manifold structure of the orthogonality constraint (i.e., the Stiefel manifold) to find a critical point of the problem. Specifically, our primary contribution is to show that the Łojasiewicz exponent at any critical point of the QP-OC problem is 1 / 2. Such a result is significant, as it expands the currently very limited repertoire of optimization problems for which the Łojasiewicz exponent is explicitly known. Moreover, it allows us to show, in a unified manner and for the first time, that a large family of retraction-based line-search methods will converge linearly to a critical point of the QP-OC problem. Then, as our secondary contribution, we propose a stochastic variance-reduced gradient (SVRG) method called Stiefel-SVRG for solving the QP-OC problem and present a novel Łojasiewicz inequality-based linear convergence analysis of the method. An important feature of Stiefel-SVRG is that it allows for general retractions and does not require the computation of any vector transport on the Stiefel manifold. As such, it is computationally more advantageous than other recently-proposed SVRG-type algorithms for manifold optimization.

Aiming at the problem that it is difficult to predict the alloy yield in the RH furnace refining process, an alloy yield prediction model based on a sparrow search algorithm (SSA) optimized ELM neural network is proposed. Firstly, because the dimensions of input parameters are different, 11 input features are reduced by factor analysis (FA), and 5 input features are obtained. Then, through the sparrow search algorithm with fast convergence, high precision, and good stability, the input weight value and threshold of the ELM neural network are optimized, the SSA-ELM alloy yield prediction model is established, the alloy yield is predicted, and the off-line operation of the model is realized, which provides a theoretical basis for the prediction of alloy yield in the actual production process. Finally, by comparing the simulation results with the actual production data, it is found that the prediction results of the target element alloy yield predicted by the SSA-ELM are within the error range, and the prediction accuracy is higher than that of the ELM prediction model, which verifies the feasibility and effectiveness of the model.

When a short circuit fault occurs in a power system, the short circuit current value in the short circuit increases greatly, and at the same time, it will reduce the voltage in the power network, even 60 percent to 70 percent of the original voltage, then the power of some users was destroyed. In order to make the system work properly, it is important to analyse the cause of bus voltage drop. The traditional solution is to increase reactive power by using external equipment, such as static capacitor or STATCOM device, but the cost of the above two devices is too high. And each bus bar lower end of the load is connected with synchronous motor in Xindu Chemical 110kv Substation. When a short circuit fault occurs in the system, the synchronous motor can be excited in a short time to reduce the voltage drop, which is economical and fast. In this paper, four excitation modes of synchronous machine are analysed in detail, including constant excitation current, constant reactive power excitation, constant power factor excitation and constant active power excitation. Finally, the constant active power excitation model is chosen to solve the problems encountered. Finally, the short circuit current is judged quickly, so that the short-circuit fault can be judged quickly according to the change rate of the current in the system.