5,133 research outputs found

    Meta-heuristic algorithms in car engine design: a literature survey

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    Meta-heuristic algorithms are often inspired by natural phenomena, including the evolution of species in Darwinian natural selection theory, ant behaviors in biology, flock behaviors of some birds, and annealing in metallurgy. Due to their great potential in solving difficult optimization problems, meta-heuristic algorithms have found their way into automobile engine design. There are different optimization problems arising in different areas of car engine management including calibration, control system, fault diagnosis, and modeling. In this paper we review the state-of-the-art applications of different meta-heuristic algorithms in engine management systems. The review covers a wide range of research, including the application of meta-heuristic algorithms in engine calibration, optimizing engine control systems, engine fault diagnosis, and optimizing different parts of engines and modeling. The meta-heuristic algorithms reviewed in this paper include evolutionary algorithms, evolution strategy, evolutionary programming, genetic programming, differential evolution, estimation of distribution algorithm, ant colony optimization, particle swarm optimization, memetic algorithms, and artificial immune system

    VHDL-AMS based genetic optimization of a fuzzy logic controller for automotive active suspension systems

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    This paper presents a new type of fuzzy logic controller (FLC) membership functions for automotive active suspension systems. The shapes of the membership functions are irregular and optimized using a genetic algorithm (GA). In this optimization technique, VHDL-AMS is used not only for the modeling and simulation of the fuzzy logic controller and its underlying active suspension system but also for the implementation of a parallel GA. Simulation results show that the proposed FLC has superior performance to that of existing FLCs that use triangular or trapezoidal membership functions

    A genetic algorithm for the design of a fuzzy controller for active queue management

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    Active queue management (AQM) policies are those policies of router queue management that allow for the detection of network congestion, the notification of such occurrences to the hosts on the network borders, and the adoption of a suitable control policy. This paper proposes the adoption of a fuzzy proportional integral (FPI) controller as an active queue manager for Internet routers. The analytical design of the proposed FPI controller is carried out in analogy with a proportional integral (PI) controller, which recently has been proposed for AQM. A genetic algorithm is proposed for tuning of the FPI controller parameters with respect to optimal disturbance rejection. In the paper the FPI controller design metodology is described and the results of the comparison with random early detection (RED), tail drop, and PI controller are presented

    DIFFERENTIAL EVOLUTION FOR OPTIMIZATION OF PID GAIN IN ELECTRICAL DISCHARGE MACHINING CONTROL SYSTEM

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    ABSTRACT PID controller of servo control system maintains the gap between Electrode and workpiece in Electrical Dis- charge Machining (EDM). Capability of the controller is significant since machining process is a stochastic phenomenon and physical behaviour of the discharge is unpredictable. Therefore, a Proportional Integral Derivative (PID) controller using Differential Evolution (DE) algorithm is designed and applied to an EDM servo actuator system in order to find suitable gain parameters. Simulation results verify the capabilities and effectiveness of the DE algorithm to search the best configuration of PID gain to maintain the electrode position. Keywords: servo control system; electrical discharge machining; proportional integral derivative; con- troller tuning; differential evolution

    Analisis dan penilaian prestasi lengah lepas tangan menggunakan protokol pencetusan sesi (SIP) bagi sistem terintegrasi UMTS-WLAN

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    Teknologi rangkaian tanpa vvayar 4G merupakan penggabungan beberapa teknologi rangkaian capaian yang berbeza seperti rangkaian Universal Mobile Telecommunication System (UMTS) dan Rangkaian Kawasan Setempat Tanpa Wayar (WLAN). Rangkaian 4G menyokong mobiliti tanpa kelim {seamless) dalam menjanjikan perhubungan dan perkhidmatan yang terbaik kepada pelanggan. Protokol Pencetusan Sesi (SIP) yang berada pada lapisan aplikasi telah diramalkan sebagai calon terbaik bagi menguruskan mobiliti di dalam rangkaian 4G. Rangkaian 4G yang menawarkan aplikasi multimedia dalam perkhidmatannya mesti mempunyai lengah lepas tangan yang rendah bagi mencapai objektif penubuhannya. Tujuan utama disertasi ini adalah untuk menilai lengah lepas tangan bagi sistem terintegrasi UMTSWLAN yang menggunakan SIP sebagai protokol pengisyaratan. Model simulasi menggunakan MATLAB dibangunkan untuk menilai prestasi lengah lepas tangan tersebut. Model simulasi menggambarkan pergerakan hos mobil ke rangkaian UMTS dan WLAN. Lengah lepas tangan yang berlaku diukur berdasarkan model analitik. Prestasi lengah lepas tangan dinilai berdasarkan perubahan kadar ralat kerangka (FER), kadar ketibaan sesi SIP dan halaju hos mobil (MIT) semasa MH bergerak ke rangkaian UMTS dan WLAN. Keputusan simulasi menunjukkan bahawa lengah lepas tangan meningkat dengan penambahan FER dan kadar ketibaan sesi SIP. Halaju kebolehgerakan pengguna memberi kesan terhadap nilai lengah lepas tangan. Keputusan juga menunjukkan lengah lepas tangan minimum yang berlaku sewaktu MH bergerak ke rangkaian UMTS adalah 1.9565 saat dengan lebar jalur saluran 128kbps dan ke rangkaian WLAN adalah sekitar 0.8651 saat dengan lebar jalur saluran 11 Mbps. Berdasarkan nilai ini, lengah lepas tangan semasa MH bergerak ke rangkaian UMTS atau WLAN adalah tidak boleh diterima untuk penjurusan multimedia. Di dalam kajian ini didapati capaian tanpa wayar GPRS menyumbang lengah terbesar daripada keseluruhan lengah lepas tangan ke rangkaian UMTS

    VHDL-AMS based genetic optimisation of fuzzy logic controllers

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    Purpose – This paper presents a VHDL-AMS based genetic optimisation methodology for fuzzy logic controllers (FLCs) used in complex automotive systems and modelled in mixed physical domains. A case study applying this novel method to an active suspension system has been investigated to obtain a new type of fuzzy logic membership function with irregular shapes optimised for best performance. Design/methodology/approach – The geometrical shapes of the fuzzy logic membership functions are irregular and optimised using a genetic algorithm (GA). In this optimisation technique, VHDL-AMS is used not only for the modelling and simulation of the FLC and its underlying active suspension system but also for the implementation of a parallel GA directly in the system testbench. Findings – Simulation results show that the proposed FLC has superior performance in all test cases to that of existing FLCs that use regular-shape, triangular or trapezoidal membership functions. Research limitations – The test of the FLC has only been done in the simulation stage, no physical prototype has been made. Originality/value – This paper proposes a novel way of improving the FLC’s performance and a new application area for VHDL-AMS

    Multi-objective evolutionary–fuzzy augmented flight control for an F16 aircraft

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    In this article, the multi-objective design of a fuzzy logic augmented flight controller for a high performance fighter jet (the Lockheed-Martin F16) is described. A fuzzy logic controller is designed and its membership functions tuned by genetic algorithms in order to design a roll, pitch, and yaw flight controller with enhanced manoeuverability which still retains safety critical operation when combined with a standard inner-loop stabilizing controller. The controller is assessed in terms of pilot effort and thus reduction of pilot fatigue. The controller is incorporated into a six degree of freedom motion base real-time flight simulator, and flight tested by a qualified pilot instructor

    Design an intelligent controller for full vehicle nonlinear active suspension systems

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    The main objective of designed the controller for a vehicle suspension system is to reduce the discomfort sensed by passengers which arises from road roughness and to increase the ride handling associated with the pitching and rolling movements. This necessitates a very fast and accurate controller to meet as much control objectives, as possible. Therefore, this paper deals with an artificial intelligence Neuro-Fuzzy (NF) technique to design a robust controller to meet the control objectives. The advantage of this controller is that it can handle the nonlinearities faster than other conventional controllers. The approach of the proposed controller is to minimize the vibrations on each corner of vehicle by supplying control forces to suspension system when travelling on rough road. The other purpose for using the NF controller for vehicle model is to reduce the body inclinations that are made during intensive manoeuvres including braking and cornering. A full vehicle nonlinear active suspension system is introduced and tested. The robustness of the proposed controller is being assessed by comparing with an optimal Fractional Order (FOPID) controller. The results show that the intelligent NF controller has improved the dynamic response measured by decreasing the cost function

    Intelligent systems in manufacturing: current developments and future prospects

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    Global competition and rapidly changing customer requirements are demanding increasing changes in manufacturing environments. Enterprises are required to constantly redesign their products and continuously reconfigure their manufacturing systems. Traditional approaches to manufacturing systems do not fully satisfy this new situation. Many authors have proposed that artificial intelligence will bring the flexibility and efficiency needed by manufacturing systems. This paper is a review of artificial intelligence techniques used in manufacturing systems. The paper first defines the components of a simplified intelligent manufacturing systems (IMS), the different Artificial Intelligence (AI) techniques to be considered and then shows how these AI techniques are used for the components of IMS
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