1,722,162 research outputs found
MPC based optimal input design for nonlinear system identification
No full textA combined nonlinear model predictive control with extended Kalman filter strategy has been proposed for optimal input design. As the designed controller depend on the identified parameters, the achievable performance highly depends on the quality of the identified information. The degradation in achieving the desired control performance is quantified b y introducing an optimality criteria which minimize the error covariance matrix of the identified parameters. The major contribution is using the information of the system parameter at every sample time to improve the control performance at next time step. The the performance of the proposed algorithm is verified by numerical simulations for a example system
Optimal Input Design for Active Parameter Identification of Dynamic Nonlinear Systems
No full textThere are many important aspects to be considered while designing optimal excitation signal for system identification experiment in control applications. Active parameter identification is an important issue in system and control theory. In this dissertation, the problem of optimal input design for active parameter identification of dynamic nonlinear system is addressed. Real life physical systems are identified by excitation with a suitable input signal and observing the resulting output behavior of the system. It is important to choose the input signal intelligently in the sense that it is responsible to determine the accuracy and nature of the unknown system characteristics. This leads to a spurred interest in designing such an optimal excitation signals that can yield maximal information from the identification experiment. The information obtained from parameter identification is usually not accurate due to incomplete knowledge of the system, disturbance as exogenous inputs and noisy measurements. Hence, the input spectrum is designed in such a way that it can improve the system performance and shape the quality of obtained information. A welldesigned input signal can maximize the amount of information and reduce the experimental cost and time. The input signal is usually given some a-priori characteristics (knowledge on the pdf) so that “excitation” of the system is guaranteed. In this thesis, a closed-loop method is investigated which is able to improve the parameter identification on the basis of the actual system’s behavior. The effectiveness of the proposed algorithm is presented by the experimental results which corresponds to the perfect identification of the unknown parameter vector. The major technical contribution of this work is to propose an optimal feedback input design method for active parameter identification of dynamic nonlinear systems. The proposed framework can design such optimal excitation signals, considering the information from the identified parameters, that can maximize the
amount of information from the identified parameters, guarantee to meet the specified control performance and minimize some cost function of the error covariance matrix of the identified parameters. The problem is formulated in a receding horizon framework where extended Kalman filter is used for system identification and the optimal input is designed in a nonlinear model predictive control framework. In order to carry out a comparison study, also Unscented Kalman Filter and Gaussian Sum Filter are used for the active parameter identification of dynamic nonlinear system. Towards this end, a suitable optimality criterion related to the unknown parameters is proposed and motivated as an information measure. The aim of the optimal input design is to yield maximal information from the unknown system by minimizing the cost related to the unknown parameters while maintaining some process performance and satisfying the possible constraints. Simulations are performed to show the effectiveness of the proposed algorithm
Load displacement and high speed nanoindentation data set at different state of charge (SoC) for spinel LixMn2O4 cathodes
No full textNovel high speed nanoindentation data is reported for 0% and 100% state of charge (SoC) for the spinal LixMn2O4 material. The article also includes the load/displacement data for different SoC highlighting the displacement bursts corresponding to the pillar splitting for fracture toughness evaluation. For more details, please see the article; Mughal et al. (2016) [1]
A method to improve the quality of 2.5 dimensional micro-and nano-structures produced by focused ion beam machining
No full textThe present work deals with a new technique to produce complex micro- and nano-scale patterns with high accuracy by FIB micro machining. The proposed method is related to the production of stream file, which is optimized through a software interface. A unique sampling approach is used to optimize the conversion from a 3D meshed CAD object to the focused ion beam (FIB) digital to analogue converter (DAC). The method uses a novel scan strategy, sensitive to the pattern local geometry and size, to define the optimal ion beam path, dwell time and the scanning pitch. This not only allows to minimize the redeposition but also to obtain accurate and scalable milling routines. In order to show the applicability of the method, a hemisphere and a pyramid shape are milled and compared to the shapes obtained using the conventional techniques. Results show that the method is very effective in producing complex shapes while overcoming the detrimental effect of conventional raster/serpentine FIB strategies, such as redeposition. Lastly, a fish-net structure with a pitch of ∼200 nm as well as a series of truncated cones with sub-micrometrical details are realized to show the potential impact of this new method. Results show that a spatial resolution of less than 100 nm is achievable with the help of this method
Appraisal on End Products and Services Offered by Islamic Banks from Maqasid Shari’ah Perspective
Get PDFQuestion arises whether the products and services offered by the Islamic financial institutions (IFIs) genuinely meeting the requirement of Shari’ah. At present, not only Shari’ah advisors have been appointed to scrutinize and endorse the new products and services. In fact, majority of the IFIs have established units or departments to ensure the documentations, legal and Shari’ah framework, the process and procedure, and implementation are in line with the precept of Shari’ah. IFIs not only must avoid riba, but as well as other important elements such as gharar, deception, inequality, duress in developing and executing the end products of IFIs in order to ensure justice and social welfare prevail. This could only be achieved if the products and services approved uphold the importance of Maqasid Shari’ah. This paper will evaluate the key value chain in product approval process, role of Shari’ah advisor in approving products and services in IFIs as well as to raise possible issues and challenges related to the value chain. This paper will also look into the importance of Maqasid Shari’ah in product approval process as it is a vital element to be considered so as to avoid legal conflicts, litigation risk, instability (reputational risk) to the IFIs, tarnish the image of so called Shari’ah compliance products, uphold justice (contracting parties) and more importantly the pure teaching of Islam.Islamic financial institutions, Shari’ah committee, Maqasid Shari’ah.
Robust integrated lateral guidance and control of UAVs
No full textIn this paper, a novel guidance scheme is presented for UAVs using the Integrated Guidance and Control (IGC) framework. The proposed guidance scheme is derived using H∞ Loop Shaping Design Procedure (LSDP). To recover from an initial cross track error, the proposed guidance algorithm produces such aileron commands that ensure the roll maneuvers without saturating the roll angle. The shaping of the open loop plant is carried out using the pre and post weights and then the robust stabilization is done by using the normalized left coprime factor uncertainty. The performance and robustness of the system are verified by introducing parametric uncertainties in to the system model. The results of the proposed scheme are verified by implementing it on a complete 6-DOF nonlinear model in the presence of wind disturbance. The simulation results indicate the effectiveness and robustness of the proposed guidance algorithm
Artificial intelligence for localisation of ultra-wide bandwidth (UWB) sensor nodes
Get PDFIn this chapter, we have designed an NB classifier for a UWB-based localization system. With the help of NB classifier and RMSE, the data are classified into three categories: high, medium, and low accuracy. ROCs are plotted to show the effec-tiveness of the NB classifier. As our developed technique obtains more than 90% classification accuracy, we have tested it into two different environments: LOS and partial NLOS conditions. Furthermore, to test the accuracy, small-sized and medium-sized rooms were used. From our measurements, it is observed that the accuracy of the developed NB classifier is dependent upon the environment. For LOS and NLOS envi-ronments, the accuracy are around 97% and 87.38%, respectively. Our future research will concentrate on technique that can further improve the localization classification and improve the positioning accuracy of the IP
Effect of lithiation on micro-scale fracture toughness of LixMn2O4 cathode
Get PDFAn optimized nanoindentation pillar splitting technique is used for the fracture toughness measurement of spinel LixMn2O4 cathode material under different states of charge (SoC), along with the high-speed nanoindentation results for nanomechanical property mapping. High-speed nanoindentation enables for a robust and efficient evaluation of elastic modulus and hardness as a function of the SoC on strongly heterogeneous materials. The fracture toughness decreases linearly upon de-lithiation, with an overall reduction of 53% from 0% to 100% SoC. Decrease in fracture toughness is associated with the volume change, increase of defect density and stresses related to diffusion of lithium upon de-lithiation
Design, fabrication and characterisation of multilayer Cr-CrN thin coatings with tailored residual stress profiles
No full textCompressive residual stress in hard coatings can improve adhesion and in-service toughness, since they can inhibit crack nucleation and propagation. However, the role of through thickness residual stress profile is not fully understood. This is because of (a) lack of knowledge of stress evolution mechanisms and (b) limitations of experimental techniques used for stress profiling. The present work deals with design, deposition and characterization of Cr-CrN multilayer coatings, produced by Magnetron Sputtering Physical Vapour Deposition (MS-PVD). Analytical modelling was used to determine the optimal residual stress distribution for a range of contact loading situations. On the basis of modelling activities, three different Cr-CrN multilayers were produced, with the aim of obtaining different stress gradients, as measured by incremental micro-scale focused ion beam (FIB) ring-core method, while keeping the same average stress value and same average hardness in the film. Results show a significant correlation between the observed residual stress profiles and scratch adhesion, where different optimal stress profiles are identified for different loading conditions. In particular, we show that a lower interfacial compressive stress and a reduced through thickness stress gradient gives improved scratch adhesion, when using 10 μm and 200 μm sphero-conical indenters
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