31 research outputs found

    Application of genetic algorithms to tuning fuzzy control systems

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    Real number genetic algorithms (GA) were applied for tuning fuzzy membership functions of three controller applications. The first application is our 'Fuzzy Pong' demonstration, a controller that controls a very responsive system. The performance of the automatically tuned membership functions exceeded that of manually tuned membership functions both when the algorithm started with randomly generated functions and with the best manually-tuned functions. The second GA tunes input membership functions to achieve a specified control surface. The third application is a practical one, a motor controller for a printed circuit manufacturing system. The GA alters the positions and overlaps of the membership functions to accomplish the tuning. The applications, the real number GA approach, the fitness function and population parameters, and the performance improvements achieved are discussed. Directions for further research in tuning input and output membership functions and in tuning fuzzy rules are described

    Validation and Verification of Aircraft Control Software for Control Improvement

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    Validation and Verification are important processes used to ensure software safety and reliability. The Cooper-Harper Aircraft Handling Qualities Rating is one of the techniques developed and used by NASA researchers to verify and validate control systems for aircrafts. Using the Validation and Verification result of controller software to improve controller\u27s performance will be one of the main objectives of this process. Real user feedback will be used to tune PI controller in order for it to perform better. The Cooper-Harper Aircraft Handling Qualities Rating can be used to justify the performance of the improved system

    Speed Roughness Control of an SI Engine Using Fuzzy Self Tuning Method

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    Implementasi Kontrol PID Pada Lengan Robot Untuk Mencari Sumber Gas Menggunakan STM32F4

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    Kebakaran adalah salah satu penyebab kematian pekerja pada perusahaan gas berbahaya. Salah satu penyebab kebakaran adalah kebocoran gas. Kebocoran gas berbahaya apabila diabaikan akan banyak menimbulkan bahaya. Lengan robot dengan sensor gas dapat digunakan untuk mendeteksi sumber kebocoran gas. Lengan robot dapat memposisikan sensor gas pada posisi terdekat dengan sumber gas yang dapat dijangkau. Dengan menggunakan sensor gas TGS2600 dengan target gas ethanol, maka lengan robot dapat menemukan sumber kebocoran gas. Implementasi kendali Proposional Derivative Integral (PID) pada lengan robot akan mengolah masukan dari sensor gas pada prosessor STM32F4 yang akan menghasilkan keluaran data untuk menggerakkan aktuator berupa servo secara otomatis. Pada tugas akhir ini, kendali PID digunakan untuk mengontrol gerakan lengan robot 3 DOF dengan sudut 0o-180o pada sumbu horizontal. Jarak jangkauan maksimal lengan robot dapat mendeteksi sumber gas dengan sensor TGS2600 adalah 15cm. Dibutuhkan sebuah kipas penghisap yang diletakkan pada ujung lengan robot di bagian sensor gas untuk membantu sensor mendeteksi dengan lebih fokus. Kendali pada lengan robot yang memiliki nilai error rata-rata rendah ketika mencari sumber gas pada sudut uji 90o adalah dengan menggunakan konstanta Kp=1, Kd=0,09, Ki=0.0001 dengan masing-masing nilai rata-rata error sebesar 4,401%,1,109%, dan 1,072%. ======================================================================================================= Fire accident is one of the mortal cause of workers in hazardous gas company. One cause of the fire accident was a gas leak. Gas leak is dangerous if neglected and will cause a lot of danger. Arm robot with gas sensors can be used to detect the source of the gas leak. The robotic arm can move the gas sensor to the closest position of the gas source. By using TGS2600 as the gas sensor and ethanol as the target, then the robot arm can locate the source of the gas leak. Implementation of control Proportional Integral Derivative (PID) on the robotic arm will process the input from the sensors using processor STM32F4 and generate data output to drive the servo actuators automatically. In this research, PID control is used to control the movement of the 3 DOF robot arm with 0o-180o angle on the horizontal axis. Maximum range of the robot arm's detection ability is 15 cm. a suction fan is placed at the end of the robot arm at the gas sensor to help detect sensor with more focus. robot arm's control has a low average error value when looking for the source of the gas at a test angle of 90o with constant Kp = 1, Kd = 0.09, Ki = 0.0001 and the respective average value of error of 4.401%, 1.109%, and 1.072%

    Doubly-fed induction generator used in wind energy

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    Wound-rotor induction generator has numerous advantages in wind power generation over other generators. One scheme for wound-rotor induction generator is realized when a converter cascade is used between the slip-ring terminals and the utility grid to control the rotor power. This configuration is called the doubly-fed induction generator (DFIG). In this work, a novel induction machine model is developed. This model includes the saturation in the main and leakage flux paths. It shows that the model which considers the saturation effects gives more realistic results. A new technique, which was developed for synchronous machines, was applied to experimentally measure the stator and rotor leakage inductance saturation characteristics on the induction machine. A vector control scheme is developed to control the rotor side voltage-source converter. Vector control allows decoupled or independent control of both active and reactive power of DFIG. These techniques are based on the theory of controlling the B- and q- axes components of voltage or current in different reference frames. In this work, the stator flux oriented rotor current control, with decoupled control of active and reactive power, is adopted. This scheme allows the independent control of the generated active and reactive power as well as the rotor speed to track the maximum wind power point. Conventionally, the controller type used in vector controllers is of the PI type with a fixed proportional and integral gain. In this work, different intelligent schemes by which the controller can change its behavior are proposed. The first scheme is an adaptive gain scheduler which utilizes different characteristics to generate the variation in the proportional and the integral gains. The second scheme is a fuzzy logic gain scheduler and the third is a neuro-fuzzy controller. The transient responses using the above mentioned schemes are compared analytically and experimentally. It has been found that although the fuzzy logic and neuro-fuzzy schemes are more complicated and have many parameters; this complication provides a higher degree of freedom in tuning the controller which is evident in giving much better system performance. Finally, the simulation results were experimentally verified by building the experimental setup and implementing the developed control schemes

    Proceedings of the Third International Workshop on Neural Networks and Fuzzy Logic, volume 2

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    Papers presented at the Neural Networks and Fuzzy Logic Workshop sponsored by the National Aeronautics and Space Administration and cosponsored by the University of Houston, Clear Lake, held 1-3 Jun. 1992 at the Lyndon B. Johnson Space Center in Houston, Texas are included. During the three days approximately 50 papers were presented. Technical topics addressed included adaptive systems; learning algorithms; network architectures; vision; robotics; neurobiological connections; speech recognition and synthesis; fuzzy set theory and application, control and dynamics processing; space applications; fuzzy logic and neural network computers; approximate reasoning; and multiobject decision making

    Cognitive Vehicle Platooning in the Era of Automated Electric Transportation

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    Vehicle platooning is an important innovation in the automotive industry that aims at improving safety, mileage, efficiency, and the time needed to travel. This research focuses on the various aspects of vehicle platooning, one of the important aspects being analysis of different control strategies that lead to a stable and robust platoon. Safety of passengers being a very important consideration, the control design should be such that the controller remains robust under uncertain environments. As a part of the Department of Energy (DOE) project, this research also tries to show a demonstration of vehicle platooning using robots. In an automated highway scenario, a vehicle platoon can be thought of as a string of vehicles, following one another as a platoon. Being equipped by wireless communication capabilities, these vehicles communicate with one another to maintain their formation as a platoon, hence are cognitive. Autonomous capable vehicles in tightly spaced, computer-controlled platoons will lead to savings in energy due to reduced aerodynamic forces, as well as increased passenger comfort since there will be no sudden accelerations or decelerations. Impacts in the occurrence of collisions, if any, will be very low. The greatest benefit obtained is, however, an increase in highway capacity, along with reduction in traffic congestion, pollution, and energy consumption. Another aspect of this project is the automated electric transportation (AET). This aims at providing energy directly to vehicles from electric highways, thus reducing their energy consumption and CO2 emission. By eliminating the use of overhead wires, infrastructure can be upgraded by electrifying highways and providing energy on demand and in real time to moving vehicles via a wireless energy transfer phenomenon known as wireless inductive coupling. The work done in this research will help to gain an insight into vehicle platooning and the control system related to maintaining the vehicles in this formation
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