1,256 publications from this institution
An optimal input design method for parameter estimation in a discrete‐time nonlinear system is presented in the paper to improve the observability and identification precision of model parameters. Determinant of the information matrix is used as the criterion function which is generally a nonconvex function about the input signals to be designed. To avoid the locally optimizing problem, a randomized design method is proposed by which a globally optimizing test plan other than input signals may be obtained. Then the randomized design can be approximated by a nonrandomized design about optimal inputs. An iterative algorithm integrated with dynamic programming is given and verified by a numerical example on experimental design for self‐calibration tests of ISP system.
The UK and European framework for access to the UHF TV band by white space devices (WSDs) is predicated on the availability of instructions from white space databases (WSDBs) which specify location-specific maximum permitted WSD radiated power levels. These levels are calculated in such a way so as to afford protection to the digital terrestrial TV (DTT) service in terms of a maximum permitted degradation in DTT location probability. The contribution of this paper is two-fold. Firstly, we present an approach for the calculation of DTT location probability which improves considerably on the accuracy of the technique commonly used for this purpose. Secondly, we present a novel methodology for the calculation of the maximum permitted WSD EIRP, subject to a target degradation in location probability. We show that, despite its low computational efficiency, the methodology generates results which compare favorably with those generated via brute-force Monte Carlo simulations. Both presented techniques are suitable for implementation in TV white space databases.
This paper presents a series of estimations performed in order to establish the actual cost-effectiveness of three different small wind turbines (SWTs) design solutions. Each of them was evaluated and based on their power curves and installation costs, using wind data from a numerical weather prediction (WNP) model, a return on investment (ROI) period was calculated. The chosen turbines are: a standard three bladed horizontal axis wind turbine (HAWT), an advanced diffuser augmented HAWT and a Darrieus type vertical axis wind turbine (VAWT). The conclusions drawn from this study entertain the idea that from the economical point of view, a price reduction of SWT systems is more important than aerodynamic complexity and efficiency.
Industry 5.0 aims to prioritize the needs and capabilities of human operators and design and implement production environments that support their role. Indeed, this paper addresses the need for a human-centered framework proposing a preference-based optimization algorithm in a human-robot collaboration (HRC) scenario with an ergonomics assessment to improve working conditions. The HRC application consists of optimizing a collaborative robot end-effector pose during an object-handling task. The approach utilizes an Active multi-Preference Learning (AmPL) algorithm, a preferencebased optimization method, where the user is requested to iteratively provide qualitative feedback by expressing pairwise preferences between a couple of candidates. To address physical well-being, an ergonomic performance index (RULA) is combined with the user’s pairwise preferences, so that the optimal setting can be computed. Experimental tests have been conducted to validate the method, involving collaborative assembly during the object handling performed by the robot. Results illustrate that the proposed method can improve the physical workload of the operator while easing the collaborative task.
The Dielectric Electro Active Polymer's (DEAP's) sensing capabilities is one of the main trio-characteristics of the material applicable area's, the trio-formations as applicable use are actuator, transducer and last but not least sensor. It is noted here that one of the main value propositions whenever DEAP material is used is the dual characteristics as the sensing/actuating capability. In the following work, the DEAP membrane will be modeled and the relation between the key variables (pressure & capacitance) will be determined. Hence, such a relation depends on the geometrical shape of the used membrane. So on, conceptualization is carried out to propose alternative solution for the sensor design using the DEAP and the laminate material. In general, the DEAP material has proven to be a very good sensor for pressure taking the advantage of flexibility, wide range of operation and last but not least the sensitivity. The theoretical model is benchmarked against the acquired data from the tests, good correlation has been recorded. The desired requirements for accuracy and measuring intervals are satisfied, showing a promising potentials for the DEAP material in pressure sensing in general, and pressure sensing application in specific.
The humidity sensitive characteristics of the sensor fabricated from 10 mol% La 2 O 3 doped CeO 2 nanopowders with particle size 17.26 nm synthesized via hydrothermal method were investigated at different frequencies. It was found that the sensor shows high humidity sensitivity, rapid response-recovery characteristics, and narrow hysteresis loop at 100 Hz in the relative humidity range from 11% to 95%. The impedance of the sensor decreases by about five orders of magnitude as relative humidity increases. The maximum humidity hysteresis is about 6% RH, and the response and recovery time is 12 and 13 s, respectively. These results indicate that the nanosized La 2 O 3 doped CeO 2 powder has potential application as high-performance humidity sensor.
Multi-standard software-definable radios which are capable of operation according to a variety of different mobile radio standards represent an extremely powerful tool for evolution towards future third-generation cellular systems. This is particularly the case in Europe where the emergence of advanced UMTS air-interfaces needs to be accompanied with some degree of backward compatibility with the well-established GSM/DCS systems. This paper examines a number of the architectural issues and trade-offs involved in the design of wideband multi-standard GSM/UMTS digital radios and presents an examination of the filtering and ADC technology requirements for their implementation. This work has been undertaken in the context of the FIRST project (Flexible Integrated Radio System Technology) as part of the ACTS mobile line.
In this paper, a robust data-driven fault detection approach is proposed with application to a wind turbine benchmark. The main challenges of the wind turbine fault detection lie in its nonlinearity, unknown disturbances as well as significant measurement noise. To overcome these difficulties, a data-driven fault detection scheme is proposed with robust residual generators directly constructed from available process data. A performance index and an optimization criterion are proposed to achieve the robustness of the residual signals related to the disturbances. For the residual evaluation, a proper evaluation approach as well as a suitable decision logic is given to make a correct final decision. The effectiveness of the proposed approach is finally illustrated by simulations on the wind turbine benchmark model.
Input-to-state stability of nonlinear control system is described in several different manners, and has been a central concept since the equivalences among them were verified. In this paper, a framework of stability and dissipativity for stochastic control systems is constructed on the maximal existence interval of behaviors (states and external inputs), by the aid of stochastic Barbalat lemma and stochastic dissipativity. The main work consists of three aspects. First, input-to-state stability and robust stability are extended to the stochastic case, and several criteria are established. Second, two forms of dissipativity and their criteria are presented. Third, the key relations among the definitions of stability and dissipativity are verified. Compared with the existing results on stochastic input-to-state stability, our methods allow for non-globally Lipschitz condition, dynamic inputs without knowledge about boundedness and non-smoothness of storage functions, which are more effective and convenient to be used in practice.
This paper is concerned with the control issue for a class of networked control systems (NCSs) with packet dropouts and time-varying delays. Firstly, the addressed NCS is modeled as a Markovian discrete-time switched system with two subsystems; by using the average dwell time method, a sufficient condition is obtained for the mean square exponential stability of the closed-loop NCS with a desired disturbance attenuation level. Then, the desired controller is obtained by solving a set of linear matrix inequalities (LMIs). Finally, a numerical example is given to illustrate the effectiveness of the proposed method.
No abstract is provided for this article.
How to seek the important nodes of complex networks in product research and development (R&D) team is particularly important for companies engaged in creativity and innovation. The previous literature mainly uses several single indicators to assess the node importance; this paper proposes a multiple attribute decision making model to tentatively solve these problems. Firstly, choose eight indicators as the evaluation criteria, four from centralization of complex networks: degree centrality, betweenness centrality, closeness centrality, and eigenvector centrality and four from structural holes of complex networks: effective size, efficiency, constraint, and hierarchy. Then, use fuzzy analytic hierarchy process (AHP) to obtain the weights of these indicators and use technique for order preference by similarity to an ideal solution (TOPSIS) to assess the importance degree of each node of complex networks. Finally, taking a product R&D team of a game software company as a research example, test the effectiveness, operability, and efficiency of the method we established.
This paper considers switching stochastic delay neural networks (SSDNNs) with all unstable subsystems. By using discretized Lyapunov-Krasovskii functions (DLKFs) combined with the dwell time method, exponential stability of SSDNNs with all unstable subsystems are analyzed, and several novel stability criteria in mean square are obtained. Comparing with the existing works, our results focus on all unstable subsystems rather than other combinations such as all stable or partially stable subsystems, which is of more research significance. Finally, the correctness of the conclusion is checked by the feasible solutions of two numerical examples.
This paper is concerned with the recursive fusion estimation‐based mobile robot localization (RL) problem by employing multiple energy harvesting sensors (EHSs). In the addressed RL problem, multiple sensors with energy harvesting capacity are deployed to produce measurements used for RL. When the sensors own sufficient energy, the sensors can output measurements and then send them to the corresponding local filter. Otherwise, the sensor energy‐induced missing measurement phenomenon will occur. In order to obtain the missing measurement rate, at each time instant, the relationship between the totality of the sensor energy and its probability distribution is derived recursively. This paper aims at seeking out a practicable solution to the addressed mobile RL problem. First, in the presence of the sensor energy‐induced measurement missing phenomenon, an upper bound (UB) of the local localization error covariance is recursively acquired. Then, such a derived UB is minimized by suitably devising the desired local filter parameter. Subsequently, the covariance intersection fusion method is adopted to achieve the addressed RL problem. In the end, a simulation is conducted to verify the practicability of the developed RL scheme.
