Control Engineering

Keviczky, László; Bars, Ruth; Hetthéssy, Jenő; Bányász, Csilla

doi:10.1007/978-981-10-8297-9

Cited by 32 publications

(19 citation statements)

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“…Depending on the type and order of the control object as well as the relationship between its time responses, the controller was set according to the standard criteria and methods [27]. The criterion selection is based on understanding the control purpose and is not formalized in itself.…”

Section: Methodsmentioning

confidence: 99%

The Fuzzy Logic in the Problems of Test Control of a Bypass Turbojet Engine Gas Generator

et al. 2022

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Continuous improvement in the operational characteristics of gas turbine equipment and a significant reduction in the time of its creation have led to the development and application of new technologies for conducting research tests of a gas generator—the basic section of a bypass turbojet engine. Carrying out such tests requires the reproduction of the thermo gas dynamic parameters of the working fluid at the gas generator inlet to ensure maximum similarity to the processes occurring in the engine being designed. Obtaining a working fluid with the required thermo gas dynamic parameters such as temperature, pressure, and air flow rate is carried out on the basis of a test complex. The test complex, as a control object, is a non-linear, non-stationary, multi-variable system, where each controlled variable substantially depends on other control actions. The article presents the main aspects of the behavior of the object under consideration, which are the basis for the development of an automated test system and, in particular, the principles of forming control algorithms based on the theory of fuzzy logic. The graphs of the state and control of the main elements of the test complex are presented. Special attention is given to the analysis of the proposed control algorithms.

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Section: Methodsmentioning

confidence: 99%

The Fuzzy Logic in the Problems of Test Control of a Bypass Turbojet Engine Gas Generator

et al. 2022

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“…We adopt the transfer function model in the control theory to calculate the noise rejection ratio of the active magnetic-field stabilization system [46,47]. The transfer function theoretically models a linear-time-invariant (LTI) system's output for each possible input [48] and provides a direct way to quantitatively analyze the system's characteristics, such as the stability and the frequency response.…”

Section: Methodsmentioning

confidence: 99%

Active Magnetic-Field Stabilization with Atomic Magnetometer

Zhang

Ding

Yang

et al. 2020

Sensors

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A magnetically-quiet environment is important for detecting faint magnetic-field signals or nonmagnetic spin-dependent interactions. Passive magnetic shielding using layers of large magnetic-permeability materials is widely used to reduce the magnetic-field noise. The magnetic-field noise can also be actively monitored with magnetometers and then compensated, acting as a complementary method to the passive shielding. We present here a general model to quantitatively depict and optimize the performance of active magnetic-field stabilization and experimentally verify our model using optically-pumped atomic magnetometers. We experimentally demonstrate a magnetic-field noise rejection ratio of larger than ∼800 at low frequencies and an environment with a magnetic-field noise floor of ∼40 fT/Hz1/2 in unshielded Earth’s field. The proposed model provides a general guidance on analyzing and improving the performance of active magnetic-field stabilization with magnetometers. This work offers the possibility of sensitive detections of magnetic-field signals in a variety of unshielded natural environments.

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“…The Bass-Gura equation and the Ackermann formula are well known in the literature to design the gain vector k T [2][3][4][5][6].…”

Section: Pole Placement Controlmentioning

confidence: 99%

“…The studied plant is a popular example commonly found in control system textbooks and research literature [1][2][3][4][5][6][7][8]. The dynamics of the system are nonlinear as presented in the paper based on the above mentioned literature, but controller design is based on the linearized system.…”

Section: Introductionmentioning

confidence: 99%

State Space Based Linear Controller Design for the Inverted Pendulum

Kuczmann

2019

Acta Tech Jaur

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In a previous survey paper the detailed PID controller design to stabilize the inclination angle as well as the horizontal movement of an inverted pendulum system has been presented. In this paper the linear controller design based on the state space representation is shown step by step. Pendulum model is based on EulerLagrange modeling, and the nonlinear state space model is linearized in the unstable upward position, finally pole placement by Ackermann formula and Bass–Gura equation, moreover linear quadratic optimal control are presented. The pendulum has been inserted into a virtual reality laboratory, which is suitable to use in model based control teaching.

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Control Engineering

Cited by 32 publications

References 0 publications

The Fuzzy Logic in the Problems of Test Control of a Bypass Turbojet Engine Gas Generator

The Fuzzy Logic in the Problems of Test Control of a Bypass Turbojet Engine Gas Generator

Active Magnetic-Field Stabilization with Atomic Magnetometer

State Space Based Linear Controller Design for the Inverted Pendulum

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