APLIKASI ADAPTIVE FIR INVERSE LINEAR CONTROLLER PADA SISTEM MAGNETIC LEVITATION

Telah diaplikasikan pendekatan inverse linear kontroller pada sistem track detection magnetic levitation. Sistem magnetic levitation menggunakan gaya elekromagnetik yang dapat menghilangkan gaya friksi. Masalah utama yang sering terjadi adalah adanya sifat non linear maglev dan tingkat ketidakstabilan yang tinggi. Pada eksperimen ini diterapkan inverse linear kontroller dengan pendekatan Non Linear Mean Square (NLMS) untuk mencapai sistem maglev yang stabil pada operating point tertentu. Untuk menstabilkan proses digunakan PID controller pada sistem maglev . Kestabilan sistem ditingkatkan kembali oleh adaptive FIR inverse linear controller yang diparalelisasi dengan PID controler . Delay pada sistem direduksi dengan menambah adaptive inverse NLMS pada sistem. Eksperimen menunjukan sistem track detection yang stabil pada operasi kerja maksimum ± 2.6 Volt

NLMS Based Adaptive Control of Stable Plants

In this paper we propose a new stable adaptive controller for stable plants, which may be non-minimum phase. The controller is composed of adaptive finite impulse response (FIR) filter in the feedback loop. This adaptive FIR filter is designed online as an L-delay approximate inverse system of the given stable plant. The solution of Diophantine equation is not involved in the design procedure. Hence the numerical problems associated with the solution of Diophantine equation are avoided. Computer simulation results and real time experimental results are included in the paper to demonstrate the effectiveness of the proposed method

Model predictive control of magnetic levitation system

In this work, we suggest a technique of controller design that applied to systems based on nonlinear. We inform the sufficient conditions for the stability of closed loop system. The asymptotic stability of equilibrium and the nonlinear controller can be applied to improvement the stability of Magnetic Levitation system(MagLev). The MagLev nonlinear nodel can be obtained by state equation based on Lagrange function and Model Predictive Control has been used for MagLev system

Inverse model based adaptive control of magnetic levitation system

This paper presents, an adaptive finite impulse response (FIR) filter based controller used for the tracking of a ferric ball under the influence of magnetic force. The adaptive filter is designed online as approximate inverse system. To stabilize the open-loop unstable and highly nonlinear magnetic levitation system, PID controller is designed using polynomial approach. To improve the stability, an adaptive FIR filter is added along side the PID controller while the use of the proposed controller has improved tracking. Since adaptive FIR filters are inherently stable so the controller remains stable. Experimental results are included to highlight the excellent position tracking performance

Fractional - order system modeling and its applications

In order to control or operate any system in a closed-loop, it is important to know its behavior in the form of mathematical models. In the last two decades, a fractional-order model has received more attention in system identification instead of classical integer-order model transfer function. Literature shows recently that some techniques on fractional calculus and fractional-order models have been presenting valuable contributions to real-world processes and achieved better results. Such new developments have impelled research into extensions of the classical identification techniques to advanced fields of science and engineering. This article surveys the recent methods in the field and other related challenges to implement the fractional-order derivatives and miss-matching with conventional science. The comprehensive discussion on available literature would help the readers to grasp the concept of fractional-order modeling and can facilitate future investigations. One can anticipate manifesting recent advances in fractional-order modeling in this paper and unlocking more opportunities for research

IMECE2002-NCA-33051 ACTIVE CONTROL OF GEAR NOISE USING MAGNETIC BEARINGS FOR ACTUATION

ABSTRACT This paper investigates experimentally the active control of gear noise and vibration using magnetic bearing actuators in a feedforward active control scheme. The dynamic forces caused by gear meshing can produce large noise and vibration signatures that can cause annoyance and also fatigue mechanical components. In this work active magnetic bearings were used as actuators to introduce control forces very close to the source of the disturbance i.e. directly onto the rotating shaft. The proximity of the actuators to the source ensures that substantial control can be achieved using a small number of actuators. A four-square gear rig was constructed in order to test the control methodology experimentally. A proximity sensor placed near the gear teeth was used as a reference sensor and used to drive the two magnetic bearing actuators through a time domain filtered X-LMS control system to minimize the outputs from both vibration and pressure error sensors. At one microphone over 20 dB of reduction in acoustic levels was achieved at the gear mesh frequency and an overall reduction of 6 dB was demonstrated at four microphones. It is also shown that gear mesh noise and sideband frequencies can be simultaneously controlled

Application of Multichannel Active Vibration Control in a Multistage Gear Transmission System

Gears are the most important parts of rotating machinery and power transmission devices. When gears are engaged in meshing transmission, vibration will occur due to factors such as gear machining errors, meshing rigidity, and meshing impact. The traditional FxLMS algorithm, as a common active vibration algorithm, has been widely studied and applied in gear transmission system active vibration control in recent years. However, it is difficult to achieve good performance in convergence speed and convergence precision at the same time. This paper proposes a variable-step-size multichannel FxLMS algorithm based on the sampling function, which accelerates the convergence speed in the initial stage of iteration, improves the convergence accuracy in the steady-state adaptive stage, and makes the modified algorithm more robust. Simulations verify the effectiveness of the algorithm. An experimental platform for active vibration control of the secondary gear transmission system is built. A piezoelectric actuator is installed on an additional gear shaft to form an active structure and equipped with a signal acquisition system and a control system; the proposed variable-step-size multichannel FxLMS algorithm is experimentally verified. The experimental results show that the proposed multichannel variable-step-size FxLMS algorithm has more accurate convergence accuracy than the traditional FxLMS algorithm, and the convergence accuracy can be increased up to 123%