36 research outputs found
Synthesis of Hybrid Fuzzy Logic Law for Stable Control of Magnetic Levitation System
In this paper, we present a method to design a hybrid fuzzy logic controller (FLC) for a magnetic levitation system (MLS) based on the linear feedforward control method combined with FLC. MLS has many applications in industry, transportation, but the system is strongly nonlinear and unstable at equilibrium. The fast response linear control law ensures that the ball is kept at the desired point, but does not remain stable at that point in the presence of noise or deviation from the desired position. The controller that combines linear feedforward control and FLC is designed to ensure ball stability and increase the system's fast-response when deviating from equilibrium and improve control quality. Simulation results in the presence of noise show that the proposed control law has a fast and stable effect on external noise. The advantages of the proposed controller are shown through the comparison results with conventional PID and FLC control laws
Development of a Fuzzy Logic Model-Less Aircraft Controller
The Modeling and Control for Agile Aircraft Development (MCAAD) group at NASA Langley Research Center(LaRC) is developing techniques for Real-Time Global Modeling (RTGM) and Robust Learning Control (RLC) for NASA’s Transformational Tools and Technologies Project. This project seeks to develop a systematic approach to reduce the iterative nature of aircraft design by introducing a model-less control law and enabling inflight aerodynamic modeling and controller design. The development of the flight control system without prior knowledge of the aircraft aerodynamic model makes use of TakagiSugeno-Kang fuzzy logic inference systems for pitch and roll controllers and are tested in various simulations and wind tunnel platforms. These fuzzy logic controllers are not based on a mathematical model but rather on a rule base of generic flight control laws generated from the designer’s knowledge of aircraft flight mechanics. The controller architecture uses two channels to provide absolute and incremental controller commands as needed. The absolute channel is designed to reject disturbances and decrease rise time, while the incremental channel provides tracking and reduced steady state error. To provide controllers with acceptable performance without the need for tuning, a general method for selecting input and output scaling gains for the fuzzy inference systems is proposed. A performance and robustness comparison of similarly configured Type-1 and Interval Type-2 fuzzy logic controllers is made. The fuzzy logic controllers were implemented on an aircraft model in the NASA Langley 12-Foot low speed tunnel mounted on a free-to-pitch and free-to-roll rig. The development of the controller architectures and wind tunnel results are presented
FPGA fuzzy controller design for magnetic ball levitation
this paper presents a fuzzy controller design for nonlinear system using FPGA. A magnetic levitation system is considered as a case study and the fuzzy controller is designed to keep a magnetic object suspended in the air counteracting the weight of the object. Fuzzy controller will be implemented using FPGA chip. The design will use a high-level programming language HDL for implementing the fuzzy logic controller using the Xfuzzy tools to implement the fuzzy logic controller into HDL code. This paper, advocates a novel approach to implement the fuzzy logic controller for magnetic ball levitation system by using FPGA
Proportional-Integral-Derivative Gain-Scheduling Control of a Magnetic Levitation System
The paper presents a gain-scheduling control design procedure for classical Proportional-Integral-Derivative controllers (PID-GS-C) for positioning system. The method is applied to a Magnetic Levitation System with Two Electromagnets (MLS2EM) laboratory equipment, which allows several experimental verifications of the proposed solution. The nonlinear model of MLS2EM is linearized at seven operating points. A state feedback control structure is first designed to stabilize the process. PID control and PID-GS-C structures are next designed to ensure zero steady-state control error and bumpless switching between PID controllers for the linearized models. Real-time experimental results are presented for validation.
Robust Integral State Feedback Using Coefficient Diagram in Magnetic Levitation System
Magnetic Levitation System or Maglev system is a modern and future technology that has many advantages and applications. Its characteristic is highly nonlinear, fast dynamics, and unstable, so it is challenging to make a suitable controller. The model of the Maglev system is in nonlinear state-space representation, and then feedback linearization is implemented to obtain the linear model system. Then, the integral state feedback control that tuned by the coefficient diagram method is implemented. The robustness of the controller is determined using the coefficient diagram method. The result of the standard coefficient diagram parameter will be compared with the robustness parameter. The open-loop test simulation showed that the maglev system has a nonlinear characteristic. Among all of the uncertainties, the uncertainty of resistance provides the highest nonlinearity, even by the small value of uncertainty. The examination of the mass, inductance, and resistance uncertainties showed that the robustness parameter is able to handle them and to provide a robust controller
Uma Estratégia de Controle Multi-Modelo LQG/LTR Aplicada a um Sistema Não Linear de Levitação Magnética.
Este trabalho apresenta o desenvolvimento de uma nova estratégia de controle multi-modelo para aplicações em plantas não lineares. Realiza-se a união da metodologia clássica, com o desenvolvimento de controladores LQG/LTR em tempo discreto, junto à metodologia inteligente, através da lógica Fuzzy, de forma a obter como resultado um controlador hÃbrido que consiga driblar o problema da não linearidade existente em sistemas dinâmicos. Neste contexto, este trabalho apresenta uma estratégia de expandir a planta de processo por integradores backward Euler e, a partir da dinâmica da planta em malha aberta expandida, desenvolver e ajustar controladores multi-modelos LQG/LTR em tempo discreto e realizar a união destes via lógica Fuzzy para obter um controlador não linear global que atue na planta não linear de um sistema de levitação magnética. O objetivo do controlador não linear global proposto é ser capaz de rejeitar distúrbios, bem como manter o rastreamento do sistema para diferentes pontos de operação, usando a solução de controle multi-modelo LQG/LTR em tempo discreto unido a lógica Fuzzy. Para validação e comprovação da nova parametrização desenvolvida, foram realizadas simulações e ensaios práticos em um aparelho de levitação magnética da empresa canadense Quanser
Sistem Kontrol Tungku Api Otomatis Untuk Proses Pasteurisasi Susu Berbasis Logika Fuzzy Sugeno
Salah satu faktor berkurangnya gizi pada susu adalah kesalahan dalam proses pengolahannya, produk susu biasanya akan melalui proses pasteurisasi guna membunuh bakteri didalamnya dan menambah waktu simpan susu. Namun proses pasteurisasi yang salah justru akan mengakibatkan berkurangnya gizi yang terkandung didalam susu dan tak jarang akan membuat susu justru menjadi rusak. Sistem kontrol tungku api otomatis dirancang untuk menangani masalah yang ada dimana dengan menggunakan mekanikal servo, sistem akan secara otomatis mengatur bukaan katup tungku api untuk menjaga suhu pada set-point yang diinginkan, sehingga suhu akan terjaga dan protein pada susu tidak rusak karena suhu pada proses pemasakan yang terlalu tinggi. Berdasarkan hasil pengujian, bahwa sistem tanpa fuzzy membutuhkan waktu selama 1 jam untuk dapat mencapai set-point, sedangkan sistem dengan fuzzy hanya membutuhkan waktu 30 menit saja untuk mencapai set-point
Tracking Control of High Order Input Reference Using Integrals State Feedback and Coefficient Diagram Method Tuning
The purpose of the research is tracking control to follow the input reference signal such as step, ramp, parabolic, and high order reference stably. The challenge is rising when high order input references, such as parabolic or polynomial, are used in the advanced system. Like in satellite and missile launcher systems, the triple integrator systems have to follow parabolic or polynomial trajectory with high stability required. The research proposed an integrals state feedback controller to combine simple state feedback control with cascade-layered integral control. The order of the input reference defines the structure and number of integrals used. Along with Coefficient Diagram Method in its tuning process, the proposed controller is guaranteed to have good stability and zero steady-state error. Simulation results and mathematical proofs of stability and zero steady-state error are provided on the paper. The proposed method can follow various input references such as the ramp, parabolic, polynomial, and higher-order reference based on the simulation and mathematical proofs. The stability using the pole location also shown the negative poles that give a stable system