Comprehensive experimental study on the stabilization of active magnetic bearing system

Noshadi, Amin; Shi, Juan; Poolton, Sam; Lee, WeeSit; Kalam, Akhtar

doi:10.1109/aupec.2014.6966551

Cited by 7 publications

(5 citation statements)

References 19 publications

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“…A more advanced (and more expensive) option consists of using a DSP instead of a general-purpose MCU. This is reported in a number of works [12][13][14][15][16][17][18][19][20].…”

Section: Introduction 1pid Regulators In Contemporary Technologiesmentioning

confidence: 70%

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A Hardware Implementation of the PID Algorithm Using Floating-Point Arithmetic

Kulisz,

Jokiel

2024

Electronics

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The purpose of the paper is to propose a new implementation of the PID (proportional–integral–derivative) algorithm in digital hardware. The proposed structure is optimized for cost. It follows a serialized, rather than parallel, scheme. It uses only one arithmetic block, performing the multiply-and-add operation. The calculations are carried out in a sequentially cyclic manner. The proposed circuit operates on standard single-precision (32-bit) floating-point numbers. It implements an extended PID formula, containing a non-ideal derivative component, and weighting coefficients, which enable reducing the influence of setpoint changes in the proportional and derivative components. The circuit was implemented in a Cyclone V FPGA (Field-Programmable Gate Array) device from Intel, Santa Clara, CA, USA. The proper operation of the circuit was verified in a simulation. For the specific implementation, which is reported in the paper, the sampling period of 516 ns was obtained, which means that the proposed solution is comparable in terms of speed with other hardware implementations of the PID algorithm operating on single-precision floating-point numbers. However, the presented solution is much more efficient in terms of cost. It uses 1173 LUT (Look-up Table) blocks, 1026 registers, and 1 DSP (Digital Signal Processing) block, i.e., about 30% of logic resources required by comparable solutions.

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“…A more advanced (and more expensive) option consists of using a DSP instead of a general-purpose MCU. This is reported in a number of works [12][13][14][15][16][17][18][19][20].…”

Section: Introduction 1pid Regulators In Contemporary Technologiesmentioning

confidence: 70%

“…Nevertheless, some fast-controlled objects require sampling periods as short as tens of microseconds. In particular, it applies to the stabilization of magnetic bearings [11,16,17] and precise motion control [21]. In [21], a PID regulator is used to control the operation of insect-size robots.…”

Section: Introduction 1pid Regulators In Contemporary Technologiesmentioning

confidence: 99%

A Hardware Implementation of the PID Algorithm Using Floating-Point Arithmetic

Kulisz,

Jokiel

2024

Electronics

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“…Several forms of fuzzy controllers can be found in the literature [19][20][21][22][23][24][25]. It should be clear to the readers that the focus of this paper is on so-called direct action fuzzy controller.…”

Section: Pid-type Fuzzy Logic Controllersmentioning

confidence: 99%

Optimal PID-type fuzzy logic controller for a multi-input multi-output active magnetic bearing system

Noshadi

Shi

Lee

et al. 2015

Neural Comput & Applic

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The performance of the fuzzy controllers depends highly on the proper selection of some design parameters which is usually tuned iteratively via a trial and error process based primarily on engineering intuition. With the recent developments in the area of global optimization, it has been made possible to obtain the optimal values of the design parameters systematically. Nevertheless, it is well known that unless a priori knowledge is available about the optimization search-domain, most of the available time-domain objective functions may result in undesirable solutions. It is consequently important to provide guidelines on how these parameters affect the closedloop behavior. As a result, some alternative objective functions are presented for the time-domain optimization of the fuzzy controllers, and the design parameters of a PID-type fuzzy controller are tuned by using the proposed time-domain objective functions. Finally, the real-time application of the optimal PID-type fuzzy controller is investigated on the robust stabilization of a laboratory active magnetic bearing system. The experimental results show that the designed PID-type fuzzy controllers provide much superior performances than the linear on-board controllers while retaining lower profiles of control signals.

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“…Hence, the use of control techniques for the balance and control of the AMB system is crucial. A significant amount of research has been reported in the recent decades by Mushi et al (2011) and Noshadi et al (2014) to stabilize and regulate the AMB system.…”

Section: Introductionmentioning

confidence: 99%

Fuzzy logic control of five-DOF active magnetic bearing system based on sliding mode concept

Saha¹,

Amrr²,

Bhutto³

et al. 2022

Front. Control Eng.

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In rotor dynamics, the deviation of the shaft is a common phenomenon. The main reasons for the deviation are non-linear attractive forces, harmonic disturbances, system parameter variations, etc. Active magnetic bearings (AMBs) are used to support the rotor inside the air gap in rotating machines, thus avoiding wear and tear and possible breakdowns. This paper proposes a fuzzy sliding mode-inspired control (FSMIC) technique for the five-degrees-of-freedom (DOF) AMB system in the presence of system uncertainties and measurement noises. The fuzzy logic is used to estimate the auxiliary control input of the sliding mode control (SMC) to attenuate the chattering. The variable gains are designed with the help of superintended fuzzy logic to bring more flexibility to the controller performance. The stability analysis is presented with the help of the Lyapunov function candidate. The simulation studies for the AMB system under distinct types of control techniques, i.e., PID, SMC, and FSMIC, illustrate the effectiveness of the proposed control strategy.

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Comprehensive experimental study on the stabilization of active magnetic bearing system

Cited by 7 publications

References 19 publications

A Hardware Implementation of the PID Algorithm Using Floating-Point Arithmetic

A Hardware Implementation of the PID Algorithm Using Floating-Point Arithmetic

Optimal PID-type fuzzy logic controller for a multi-input multi-output active magnetic bearing system

Fuzzy logic control of five-DOF active magnetic bearing system based on sliding mode concept

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