Adaptive wavenet controller design for teleoperation systems with variable time delays using singular perturbation method

The main goal of controller design in teleoperation systems is to achieve stability and optimal operation in presence of factors such as time delays, system disturbances and modeling errors. This paper proposes a new method of controller design based on wavenet with singular perturbation method for the bilateral teleoperation of robots through the internet. The wavenet controller could overcome the variable time delay in teleoperation system. This new method introduces a reduced-order structure for control and stability of teleoperation systems. By using singular perturbation method, teleoperation system is decomposed into two fast and slow subsystems. This method is a step towards reduced-order modeling. In this method, we use a feedback linearization method in master subsystem and a wavenet controller for slave subsystem. In wavenet controller, we used a learning method so that the system was Lyapunov stable. As the stability of the model is highly dependent on the learning of the system, we use Lyapunov stability in this method. It has been tried to reduce the tracking error between the master and the slave subsystems. In this structure the position of master-slave are compared together and controlling signal is applied to the slave so that they can track each other in the least possible time. In all schemes the effectiveness of the system is shown through the simulations and they have been compared with each other.     

Enhanced Hilbert–Huang transform and its application to modal identification

The well‐known Hilbert–Huang transform (HHT) consists of empirical mode decomposition to extract intrinsic mode functions (IMFs) and Hilbert spectral analysis to obtain time–frequency characteristics of IMFs through the Hilbert transform. There are two mathematical requirements that limit application of the Hilbert transform. Moreover, noise effects caused by the empirical mode decomposition procedure add a scatter to derivative‐based instantaneous frequency determined by the Hilbert transform. In this paper, a new enhanced HHT is proposed in which by avoiding mathematical limitations of the Hilbert spectral analysis, an additional parameter is employed to reduce the noise effects on the instantaneous frequencies of IMFs. To demonstrate the efficacy of the proposed method, two case studies associated with structural modal identification are selected. In the first case, through identification of a typical 3‐DOF structural model subjected to a random excitation, accuracy of the enhanced method is verified. In the second case, ambient response data recorded from a real 15‐story building are analyzed, and nine modal frequencies of the building are identified. The case studies indicate that the enhanced HHT provides more accurate and physically meaningful results than HHT and is capable to be an efficient tool in structural engineering applications. Copyright © 2012 John Wiley & Sons, Ltd.     

A hybrid fuzzy multiple criteria group decision making approach for sustainable project selection

In this paper, a new hybrid fuzzy multiple criteria group decision making (FMCGDM) approach has been proposed for sustainable project selection. First, a comprehensive framework, including economic, social, and environmental effects of an investment, strategic alliance, organizational readiness, and risk of investment has been proposed for sustainable project selection. As the relative importance of the criteria of the proposed framework are hard to find through several conflictive preferences of a group of Decision Makers (DMs) so, a goal programming (GP) has been supplied to this aim considering multiplicative and fuzzy preference relation. Then, a fuzzy TOPSIS method has been developed to assess the fitness of investment chances. It is based on Preference Ratio (PR), which is known as an efficient ranking method for fuzzy numbers, and a fuzzy distance measurement. The properties of proposed hybrid approach make it robust for modeling real case of uncertain group decision making problems. The FMCGDM has been developed through a linkage between Lingo 11.0, MS-Excel 12.0, and Visual Basic 6.0. The proposed hybrid approach has been applied in a real case study called Iranian financial and credit institute for sustainable project selection.     

Design of actively-cooled microvascular materials: a genetic algorithm inspired network optimization

Structural and Multidisciplinary Optimization - The design of a microvascular flow network embedded in an actively-cooled polymeric material is presented. A multi-objective Genetic Algorithm (GA)...     

A Method for the Estimation of the Interface Temperature in Ultrasonic Joining

Ultrasonic joining of copper foil to 1100 aluminum sheet at nominal joining temperatures of 298 K to 413 K (25 °C to 140 °C) for 1.25 second caused significant copper diffusion into the aluminum sheet, indicating very high diffusivity (D) values of 1.54 × 10^?13 to 2.22 × 10^?13 m²/s. The D values reflect high excess vacancy concentrations caused by the rapid plastic deformation in the joining surfaces. A method is presented to estimate the actual values of interface temperature from the diffusion data and expected values of vacancy concentrations. The estimated values of interface temperature were about 390 to 410 deg below the equilibrium melting point of aluminum, and in agreement with reported experimental values.     

A novel decentralized method based on the system engineering concept for reliability‐security constraint unit commitment in restructured power environment

In the deregulated power environment, including Central operator (CO) and Micro Grids (MGs), different parts of the network are dedicated to the private sector, and each of them seeks to increase their profits independently. The CO and MGs should cooperate and collaborate in terms of operating, security and reliability in the whole power system. This article proposes a new method based on a System of System (SoS) concept for the secure and economic hourly generation scheduling to find optimal operational point. The main methodology includes three steps. In the first step, the power system is divided into several subsystems by using a spectral clustering partitioning technique to reduce converge time by decentralizes methods. And also load forecasting based on a Gaussian probability distribution function to avoid conventional calculation and considering uncertainty of the loads has been presented. To find a similar scenario, and reduction scenario with low probability, the probabilistic method has been addressed. The main contribution of this method is removing scenarios with low value of probabilities and scenarios which are similar to each other. In fact, the reduced set must include scenarios which are scattered appropriately in the uncertain space while holding high probabilities. In order to estimate the similarity (distance) between two scenarios the Kantorovich distance is implemented. In the second step, the hierarchical Bi‐level optimization approach is used to execute the decentralized decision making to solve the Security Constraints Unit Commitment (SCUC) problem between CO and MGs. Regarding all physical relations and shared data among CO and MGs, the SoS concept and Bi‐level optimization are presented to find the optimal operating point of autonomous systems. In the third step, a random number of generators will be select. Hence, the initial iteration number is set. In this step, sampling from state space to classifying reliability object achieved (The expected energy not supplied and loss of load probability are the reliability criterion). The presented method is evaluated using a 6‐bus, the RTS 24‐bus, 118‐bus, and 4672‐bus as an IEEE test systems. The suggested structure has been implemented by GAMS, and the results illustrate the usefulness of the presented methodology. To comparing proposed approach with the centralized method, the results illustrate improving total operational costs and security (in RTS‐24($603,209), 118 bus ($2 562 154) and 4672‐bus ($9 185 168)) in scenario 3 near to 9%, 10% and 8% respectively. Similarly, by comparison (in three test systems) with genetic algorithm these improvements are near to 23%, 22% and 13% respectively.     

Computational modeling and design of actively-cooled microvascular materials

The computational modeling and design of an actively-cooled microvascular fin specimen is presented. The design study is based on three objective functions: (i) minimizing the maximum temperature in the thermally loaded fin, (ii) optimizing the flow efficiency of the embedded microchannel, and (iii) minimizing the void volume fraction of the microvascular material. A recently introduced Interface-enriched Generalized Finite Element Method (IGFEM) is employed to evaluate the temperature field in a 2D model of the specimen, allowing for the accurate and efficient capturing of the gradient discontinuity along the fluid/solid interface without the need of meshes that conform to the geometry of the problem. Finding the optimal shape of the embedded microchannel is thus accomplished with a single non-conforming mesh for all configurations. Prior to the optimization study, the IGFEM solver is validated through comparison with infrared measurements of the thermal response of an epoxy fin with a sinusoidal microchannel.     

Natural convection heat transfer in a nanofluid filled semi-annulus enclosure

To investigate natural convection heat transfer in a semi-annulus enclosure filled with nanofluid, the Control Volume based Finite Element Method (CVFEM) is used. The fluid in the enclosure is Cu–water nanofluid. The inner and outer semi circular walls are maintained at constant temperatures while the two other walls are thermally insulated. The Navier Stokes equations in their vorticity-stream function form are used to simulate the flow pattern and isotherms. The numerical investigation is carried out for different governing parameters namely; the Rayleigh number, nanoparticle volume fraction and the angle of turn for the enclosure. The effective thermal conductivity and viscosity of nanofluid are calculated using the Maxwell–Garnetts (MG) and Brinkman models, respectively. The results reveal that there is an optimum angle of turn in which the average Nusselt number is maximum for each Rayleigh number. Moreover, the angle of turn has an important effect on the streamlines, isotherms and maximum or minimum values of local Nusselt number.     

Biohydrogen synthesis from catalytic steam gasification of furniture waste using nickel catalysts supported on modified CeO2

Present study evaluated the catalytic steam gasification of furniture waste to enhance the biohydrogen production. To do this, 10 wt% nickel loaded catalysts on the variety of supports (Al₂O₃, CeO₂, CeO₂-La₂O₃, and CeO₂–ZrO₂) were prepared by the novel solvent deficient method. The hydrogen selectivity (vol%) order of the catalysts was achieved as Ni/CeO₂–ZrO₂>Ni/CeO₂>Ni/Al₂O₃?Ni/CeO₂-La₂O₃. The best catalytic activity of Ni/CeO₂–ZrO₂ catalyst (~82 vol % H₂ at 800 °C) was ascribed to the smaller size of nickel crystals, finely dispersed Ni on the catalyst surface, and Ce_1-xZr_xO_2-δ solid solution. The role of Ce_1-xZr_xO_2-δ solid solution in Ni/CeO₂–ZrO₂ catalyst was observed as bi-functional; acceleration of water-gas-shift and oxidation of carbon reaction. The high resistance of Ni/CeO₂–ZrO₂ towards the coke formation showed its potential to establish a cost-effective commercial-scale biomass steam gasification process. This study is expected to provide a promising solution for the disposal of furniture wastes for production of clean energy (biohydrogen).