A gradient-based parameter identification method for time-delay chaotic systems

In this paper, the parameter identification problem for a general class of time-delay chaotic systems is considered. The objective of the problem is to determine optimal values for an unknown time-delay and unknown system parameters such that the dynamic model of the system best fits given experimental data. We propose a gradient-based optimization algorithm to solve this problem, where accurate values for the partial derivatives of the error function are obtained by solving a set of auxiliary time-delay systems. Simulation results for two example problems show that the proposed algorithm is robust and efficient

Vibration control of super tall buildings subjected to wind loads

Excessive vibration due to wind loads is a major obstacle in design and construction of a super tall building. The authors recently introduced an innovative method for controlling the wind response of super tall buildings, which takes advantage of the so-called mega-sub structural configuration. Preliminary investigation was performed under the assumption that the wind load is a white noise and the building can be modeled as a shear structure. In this paper, a more reasonable tall building model (a cantilever beam) and a more realistic wind load model (a non-white stochastic process in time and space) are employed to design passive and hybrid mega-sub control systems and to examine the performance of such controlled buildings. Building vibration in both along-wind and across-wind directions is examined. The control parameters of the proposed systems, including the frequency ratio of the sub to the mega structures, the damping ratio of the sub structure, and the feedback gains of the actuator force, are studied and their optimal values are obtained. For comparison, a tall building without control and one with the conventional tuned-mass-damper control are also studied under the same load conditions. The significant cost-effectiveness of the proposed mega-sub systems is demonstrated in reducing the acceleration and deformation responses of tall buildings to wind loads, not only enhancing the safety of structure and its contents but also improving the comfort of occupants

Design of a mega-sub-controlled building system under stochastic wind loads

Vibration control of high-rise buildings under wind loads with application of the mega-sub-control method is studied in this paper. A building with a megasub-configuration consists of two major structural components - a megastructure as the main structural frame and several sub-structures for residential and/or commercial usage. The authors have previously proposed a ‘megasub-control method’ in which the sub-structures are designed to serve as vibration control dampers. The control objective is to suppress certain critical building responses such as inter-story drifts of the mega-structure for the purpose of structural safety and acceleration response of the sub-structures for the purpose of protecting contents and improving human comfort. The feasibility of this method has been explored by the authors in previous publications. In this study, the procedure of optimally designing dynamic parameters of a megasub-controlled building under stochastic wind loads is developed, together with two possible structural configurations which provide a mega-sub-control mechanism. The mega-structure of a mega-sub-building is modeled as a cantilever beam to retain the dominant bending mode characteristics of highrise buildings, and the sub-structure as a shear building to retain the shear mode. The fluctuating wind speed is modeled as a non-white random process in both time and space domains. The power spectral density (PSD) of critical building responses is obtained using the random vibration theory. The mean square value (MSV) of those responses, as functions of the dynamic parameters including the stiffness and damping ratio of the sub-structures, are evaluated from their PSD by numerical integration in the frequency domain. The optimal values of the dynamic parameters are determined by minimizing the MSV of certain critical building responses. An example building is used to demonstrate the design procedure and the numerical simulation of the response quantities in the time domain is carried out to verify the MSV of the building responses obtained from the random vibration theory in the frequency domain. The results show that the proposed design procedure is suitable to apply to a mega-sub-building with different sub-structural configurations. The MSV obtained from the random vibration theory in the frequency domain and from the numerical simulation in the time domain exhibit an excellent agreement. It is also found that the megasub-control method is robust in the sense that slight change in the dynamic parameters affects the building's performance very little. With the design procedure developed, and the corresponding favorable building response demonstrated, this paper has enhanced the feasibility of application of the mega-sub-control method to actual high-rise buildings for wind vibration suppression

Determination of Intrinsic Ferroelectric Polarization in Orthorhombic Manganites with E-type Spin Order

By directly measuring electrical hysteresis loops using the Positive-Up Negative-Down (PUND) method, we accurately determined the remanent ferroelectric polarization Pr of orthorhombic RMnO3 (R = Ho, Tm, Yb, and Lu) compounds below their E-type spin ordering temperatures. We found that LuMnO3 has the largest Pr of 0.17 uC/cm^2 at 6 K in the series, indicating that its single-crystal form can produce a Pr of at least 0.6 \muuC/cm^2 at 0 K. Furthermore, at a fixed temperature, Pr decreases systematically with increasing rare earth ion radius from R = Lu to Ho, exhibiting a strong correlation with the variations in the in-plane Mn-O-Mn bond angle and Mn-O distances. Our experimental results suggest that the contribution of the Mn t2g orbitals dominates the ferroelectric polarization.Comment: 16 pages, 4 figure

Time-delay estimation for nonlinear systems with piecewise-constant input

We consider a general nonlinear time-delay system in which the input signal is piecewise-constant. Such systems arise in a wide range of industrial applications, including evaporation and purification processes and chromatography. We assume that the time-delays—one involving the state variables and the other involving the input variables—are unknown and need to be estimated using experimental data. We formulate the problem of estimating the unknown delays as a nonlinear optimization problem in which the cost function measures the least-squares error between predicted and measured system output. The main difficulty with this problem is that the delays are decision variables to be optimized, rather than fixed values. Thus, conventional optimization techniques are not directly applicable. We propose a new computational approach based on a novel algorithm for computing the cost function’s gradient. We then apply this approach to estimate the time-delays in two industrial chemical processes: a zinc sulphate purification process and a sodium aluminate evaporation process

A class of optimal state-delay control problems

We consider a general nonlinear time-delay system with state-delays as control variables. The problem of determining optimal values for the state-delays to minimize overall system cost is a non-standard optimal control problem – called an optimal state-delay control problem – that cannot be solved using existing optimal control techniques. We show that this optimal control problem can be formulated as a nonlinear programming problem in which the cost function is an implicit function of the decision variables. We then develop an efficient numerical method for determining the cost function’s gradient. This method, which involves integrating an auxiliary impulsive system backwards in time, can be combined with any standard gradient-based optimization method to solve the optimal state-delay control problem effectively. We conclude the paper by discussing applications of our approach to parameter identification and delayed feedback control

Virtual Reality Based Robot Teleoperation via Human-Scene Interaction

Robot teleoperation gains great success in various situations, including chemical pollution rescue, disaster relief, and long-distance manipulation. In this article, we propose a virtual reality (VR) based robot teleoperation system to achieve more efficient and natural interaction with humans in different scenes. A user-friendly VR interface is designed to help users interact with a desktop scene using their hands efficiently and intuitively. To improve user experience and reduce workload, we simulate the process in the physics engine to help build a preview of the scene after manipulation in the virtual scene before execution. We conduct experiments with different users and compare our system with a direct control method across several teleoperation tasks. The user study demonstrates that the proposed system enables users to perform operations more instinctively with a lighter mental workload. Users can perform pick-and-place and object-stacking tasks in a considerably short time, even for beginners. Our code is available at https://github.com/lingxiaomeng/VR_Teleoperation_Gen3

Activation of NRG1-ERBB4 signaling potentiates mesenchymal stem cell-mediated myocardial repairs following myocardial infarction

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