Penilaian kepatuhan syariat islam dalam merekabentuk tanah perkuburan islam berkonsepkan taman teknologi

Tanah Perkuburan Islam di Malaysia telah mencapai banyak pembaharuan. Antaranya pembinaan Raudhatul Sakinah iaitu tanah perkuburan dalam taman. Pada peringkat awal, dua tanah perkuburan telah dijadikan tapak pembinaan iaitu Tanah Perkuburan Islam KL-Karak dan Tanah Perkuburan Islam Bukit Kiara yang diuruskan oleh Jabatan Agama Islam Wilayah Persekutuan (JAWI). Lanjutan dari itu sekumpulan penyelidik dari UTHM melakukan penambahbaikan melalui usaha merekabentuk Tanah Perkuburan Islam Berkonsepkan Taman Teknologi menggunakan dengan aplikasi Geographical Information System (GIS) sebagai nilaitambah dalam dalam proses pembinaan tanah perkuburan Islam yang lebih sistematik. Lokasi kajian ini terletak di Tanah Perkuburan Islam, Parit Raja, Batu Pahat. Perkembangan ini memerlukan memerlukan satu garis panduan yang jelas agar usaha yang dilakukan berada dalam ruang lingkup kepatuhan syariat Islam. Justeru kertas kerja ini dihasilkan bagi menilai kepa rekabentuk tanah perkuburan Islam berkonsepkan taman teknologi ini adalah selari dengan ketetapan syariat Islam. Pendekatan kajian ini menggunakan kaedah temubual, permerhatian dan kajian perpustakaan. Hasil dari analisis kajian, terdapat tiga aspek yang perlu diambilkira semasa merekabentuk tanah perkuburan berkonsepkan taman teknologi iaitu tujuan mengkebumikan jenazah, tujuan menziarahi kubur dan bentuk binaan di atas tapak perkuburan. Dapatan daripada kajian ini akan menjadikan rekabentuk Tanah Perkuburan berkonsepkan Taman Teknologi menepati syariat Islam, diterima serta dimanafaatkan oleh seluruh masyarakat Islam di Malaysia

System Identification of multi-rotor UAVs using echo state networks

Controller design for aircraft with unusual configurations presents unique challenges, particularly in extracting valid mathematical models of the MRUAVs behaviour. System Identification is a collection of techniques for extracting an accurate mathematical model of a dynamic system from experimental input-output data. This can entail parameter identification only (known as grey-box modelling) or more generally full parameter/structural identification of the nonlinear mapping (known as black-box). In this paper we propose a new method for black-box identification of the non-linear dynamic model of a small MRUAV using Echo State Networks (ESN), a novel approach to train Recurrent Neural Networks (RNN)

System identification and model-based flight control system design for an agile maneuvring quadrotor platform

In this paper, we provide a system identification, model stitching and model-based flight control system design methodology for an agile maneuvering quadrotor micro aerial vehicle (MAV) technology demonstrator platform. The proposed MAV is designed to perform agile maneuvers in hover/low-speed and fast forward flight conditions in which significant changes in system dynamics are observed. As such, these significant changes result in considerable loss of performance and precision using classical hover or forward flight model based controller designs. To capture the changing dynamics, we consider an approach which is adapted from the full-scale manned aircraft and rotorcraft domain. Specifically, linear mathematical models of the MAV in hover and forward flight are obtained by using the frequency-domain system identification method and they are validated in time-domain. These point models are stitched with the trim data and quasi-nonlinear mathematical model is generated for simulation purposes. Identified linear models are used in a multi objective optimization based flight control system design approach in which several handling quality specifications are used to optimize the controller parameters. Lateral reposition and longitudinal depart/abort mission task elements from ADS-33E-PRF are scaled-down by using kinematic scaling to evaluate the proposed flight control systems. Position hold, trajectory tracking and aggressiveness analysis are performed, Monte-Carlo simulations and actual flight test results are compared. The results show that the proposed methodology provides high precision and predictable maneuvering control capability over an extensive speed envelope in comparison to classical control techniques. Our current work focuses on i) extension of the flight envelope of the mathematical model and ii) improvement of agile maneuvering capability of the MAV

Real-time embedded system of super twisting-based integral sliding mode control for quadcopter UAV

This paper presents the development of set-point weighting-based integral super-twisting sliding mode control (SISTASMC) with full-order state observers to overcome the control challenges encountered with nonlinear and underactuated systems. Quadcopter UAV form is a good example of underactuated systems, and this is selected in this research for validating the developed control. A comparative assessment through experimental validation is conducted between SISTASMC and Set-point weighting-based Integral Sliding Mode Control to demonstrate the performance of both controllers. Based on predetermined performance criteria, the results obtained demonstrate good performance of SISTASMC in dealing with uncertainty

Hybrid active force control for fixed based rotorcraft

Disturbances are considered major challenges faced in the deployment of rotorcraft unmanned aerial vehicle (UAV) systems. Among different types of rotorcraft systems, the twin-rotor helicopter and quadrotor models are considered the most versatile flying machines nowadays due to their range of applications in the civilian and military sectors. However, these systems are multivariate and highly non-linear, making them difficult to be accurately controlled. Their performance could be further compromised when they are operated in the presence of disturbances or uncertainties. This dissertation presents an innovative hybrid control scheme for rotorcraft systems to improve disturbance rejection capability while maintaining system stability, based on a technique called active force control (AFC) via simulation and experimental works. A detailed dynamic model of each aerial system was derived based on the Euler–Lagrange and Newton-Euler methods, taking into account various assumptions and conditions. As a result of the derived models, a proportional-integral-derivative (PID) controller was designed to achieve the required altitude and attitude motions. Due to the PID's inability to reject applied disturbances, the AFC strategy was incorporated with the designed PID controller, to be known as the PID-AFC scheme. To estimate control parameters automatically, a number of artificial intelligence algorithms were employed in this study, namely the iterative learning algorithm and fuzzy logic. Intelligent rules of these AI algorithms were designed and embedded into the AFC loop, identified as intelligent active force control (IAFC)-based methods. This involved, PID-iterative learning active force control (PID-ILAFC) and PID-fuzzy logic active force control (PID-FLAFC) schemes. To test the performance and robustness of these proposed hybrid control systems, several disturbance models were introduced, namely the sinusoidal wave, pulsating, and Dryden wind gust model disturbances. Integral square error was selected as the index performance to compare between the proposed control schemes. In this study, the effectiveness of the PID-ILAFC strategy in connection with the body jerk performance was investigated in the presence of applied disturbance. In terms of experimental work, hardware-in-the-loop (HIL) experimental tests were conducted for a fixed-base rotorcraft UAV system to investigate how effective are the proposed hybrid PID-ILAFC schemes in disturbance rejection. Simulated results, in time domains, reveal the efficacy of the proposed hybrid IAFC-based control methods in the cancellation of different applied disturbances, while preserving the stability of the rotorcraft system, as compared to the conventional PID controller. In most of the cases, the simulated results show a reduction of more than 55% in settling time. In terms of body jerk performance, it was improved by around 65%, for twin-rotor helicopter system, and by a 45%, for quadrotor system. To achieve the best possible performance, results recommend using the full output signal produced by the AFC strategy according to the sensitivity analysis. The HIL experimental tests results demonstrate that the PID-ILAFC method can improve the disturbance rejection capability when compared to other control systems and show good agreement with the simulated counterpart. However, the selection of the appropriate learning parameters and initial conditions is viewed as a crucial step toward this improved performance