An efficient ant colony system based on receding horizon control for the aircraft arrival sequencing and scheduling problem

The aircraft arrival sequencing and scheduling (ASS) problem is a salient problem in air traffic control (ATC), which proves to be nondeterministic polynomial (NP) hard. This paper formulates the ASS problem in the form of a permutation problem and proposes a new solution framework that makes the first attempt at using an ant colony system (ACS) algorithm based on the receding horizon control (RHC) to solve it. The resultant RHC-improved ACS algorithm for the ASS problem (termed the RHC-ACS-ASS algorithm) is robust, effective, and efficient, not only due to that the ACS algorithm has a strong global search ability and has been proven to be suitable for these kinds of NP-hard problems but also due to that the RHC technique can divide the problem with receding time windows to reduce the computational burden and enhance the solution's quality. The RHC-ACS-ASS algorithm is extensively tested on the cases from the literatures and the cases randomly generated. Comprehensive investigations are also made for the evaluation of the influences of ACS and RHC parameters on the performance of the algorithm. Moreover, the proposed algorithm is further enhanced by using a two-opt exchange heuristic local search. Experimental results verify that the proposed RHC-ACS-ASS algorithm generally outperforms ordinary ACS without using the RHC technique and genetic algorithms (GAs) in solving the ASS problems and offers high robustness, effectiveness, and efficienc

A pan-tilt camera Fuzzy vision controller on an unmanned aerial vehicle

is paper presents an implementation of two Fuzzy Logic controllers working in parallel for a pan-tilt camera platform on an UAV. This implementation uses a basic Lucas-Kanade tracker algorithm, which sends information about the error between the center of the object to track and the center of the image, to the Fuzzy controller. This information is enough for the controller, to follow the object moving a two axis servo-platform, besides the UAV vibrations and movements. The two Fuzzy controllers of each axis, work with a rules-base of 49 rules, two inputs and one output with a more significant sector defined to improve the behavior of those

Advanced inference in fuzzy systems by rule base compression

This paper describes a method for rule base compression of fuzzy systems. The method compresses a fuzzy system with an arbitrarily large number of rules into a smaller fuzzy system by removing the redundancy in the fuzzy rule base. As a result of this compression, the number of on-line operations during the fuzzy inference process is significantly reduced without compromising the solution. This rule base compression method outperforms significantly other known methods for fuzzy rule base reduction.Peer Reviewe

A High Performance Fuzzy Logic Architecture for UAV Decision Making

The majority of Unmanned Aerial Vehicles (UAVs) in operation today are not truly autonomous, but are instead reliant on a remote human pilot. A high degree of autonomy can provide many advantages in terms of cost, operational resources and safety. However, one of the challenges involved in achieving autonomy is that of replicating the reasoning and decision making capabilities of a human pilot. One candidate method for providing this decision making capability is fuzzy logic. In this role, the fuzzy system must satisfy real-time constraints, process large quantities of data and relate to large knowledge bases. Consequently, there is a need for a generic, high performance fuzzy computation platform for UAV applications. Based on Lees’ [1] original work, a high performance fuzzy processing architecture, implemented in Field Programmable Gate Arrays (FPGAs), has been developed and is shown to outclass the performance of existing fuzzy processors

See-and-avoid quadcopter using fuzzy control optimized by cross-entropy

In this work we present an optimized fuzzy visual servoing system for obstacle avoidance using an unmanned aerial vehicle. The cross-entropy theory is used to optimise the gains of our controllers. The optimization process was made using the ROS-Gazebo 3D simulation with purposeful extensions developed for our experiments. Visual servoing is achieved through an image processing front-end that uses the Camshift algorithm to detect and track objects in the scene. Experimental flight trials using a small quadrotor were performed to validate the parameters estimated from simulation. The integration of cross- entropy methods is a straightforward way to estimate optimal gains achieving excellent results when tested in real flights

Kesan penggunaan prosedur pembelajaran kawalan kendiri (self-regulated learning) terhadap pencapaian akademik, kemahiran meta kognitif dan motivasi pelajar politeknik : kajian kes

Pembelajaran Kawalan Kendiri (PKK) merupakan satu strategi pembelajaran efektif yang membantu pelajar untuk kompeten dan mempunyai autonomi dalam diri. Namun, prosedur yang betul bagi mengaplikasikan PKK masih memerlukan penambahbaikan disebabkan oleh pelajar cepat bosan belajar subjek teori. Pelajar juga didapati mengamalkan surface learning, mudah hilang fokus dalam kelas dan tidak cekap dalam mengawal kemahiran meta kognitif. Oleh itu, tujuan kajian ini dilaksanakan adalah untuk membangunkan satu prosedur PKK khusus untuk pelajar politeknik yang mengambil subjek Prinsip Pengurusan dan diuji keberkesanannya terhadap pencapaian akademik, kemahiran meta kognitif dan motivasi pelajar. Terdapat dua (2) fasa telah digunakan dalam kajian ini. Fasa pertama (1) ialah pembangunan prosedur PKK menggunakan analisis dokumen dan model Kemp. Analisis frekuensi telah digunakan dalam fasa ini. Terdapat tiga (3) hasil dapatan kajian daripada fasa pembangunan iaitu Prosedur PKK, Aktiviti Pengajaran dan Rancangan Pengajaran Harian (RPH). Fasa kedua (2) ialah pelaksanaan prosedur PKK menggunakan reka bentuk kuasi eksperimen iaitu ujian pra-pasca bagi kumpulan-kumpulan tidak seimbang. 43 orang pelajar Politeknik Sultan Haji Ahmad Shah (POLISAS) telah dipilih sebagai kumpulan rawatan manakala 38 orang pelajar Politeknik Merlimau (PMM) sebagai kumpulan kawalan. Analisis deskriptif skor min dan analisis inferensi MANCOVA telah digunakan dalam kajian ini bagi menguji perbezaan antara kumpulan kajian. Berdasarkan hasil analisis MANCOVA yang telah dijalankan, didapati wujud perbezaan yang signifikan secara statistik antara kumpulan rawatan dan kawalan bagi pencapaian akademik [F (1, 76) = 24.786, p = .000], kemahiran meta kognitif [F (1, 76) = 14.864, p = .000] dan motivasi [F (1, 76) = 65.148, p = .000]. Kesimpulannya, prosedur PKK terbukti berkesan dan boleh dijadikan panduan kepada pensyarah dalam mengaplikasikan PKK dengan lebih efektif dan berkesan

The adaptive control system of quadrocopter motion

In this paper we present a system for automatic control of a quadrocopter based on the adaptive control system. The task is to ensure the motion of the quadrocopter along the given route and to control the stabilization of the quadrocopter in the air in a horizontal or in a given angular position by sending control signals to the engines. The nonlinear model of a quadrocopter is expressed in the form of a linear non-stationary system