Fuzzy Controller of Three-Inertia Resonance System designed by Differential Evolution

Ikeda, Hidehiro; Hanamoto, Tsuyoshi

doi:10.11142/jicems.2014.3.2.184

Cited by 5 publications

(6 citation statements)

References 10 publications

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“…To further improve the system performance in term of vibration suppression, multi inertia model, i.e., three and more inertia system, is considered [12]. In [13], a three-inertia system is controlled by using PI/PID control.…”

Section: Introductionmentioning

confidence: 99%

Vibration Suppression Control of Three Inertial Systems

Đức¹,

Linh²,

Thinh³

et al. 2020

JMechE

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This paper concerns with vibration suppression control for three inertia resonance system which can be used as the model for many moving mechanisms widely used in industry such as steel rolling mills, flexible arms, large-scale space structures, etc. Since the mechanical resonance which causes vibration is unavoidable, especially at high speed operation, vibration suppression plays a key role in improving the accuracy of the system. In this research, a linear quadratic regulator-based speed controller with an integrator that can effectively suppress the torsional vibration is applied to control the system. Instead of using conventional state observer that is sensitive to noise and model uncertainties, the extended state observer is used to overcome the disturbance and uncertainty problems. Moreover, this observer also gives us the load torque information that is used to improve the load response. Simulation results show the effectiveness of the proposed controller. In addition, the comparison to conventional PID controller also be done to verify the advantages of the proposed approach.

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Section: Introductionmentioning

confidence: 99%

Vibration Suppression Control of Three Inertial Systems

Đức¹,

Linh²,

Thinh³

et al. 2020

JMechE

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show abstract

“…The CDM is an algebraic approach designed to produce the characteristic polynomial directly in the parameter space. The design of the coefficient diagram of the control system is performed using a differential evolution (DE) procedure to obtain the optimal controller gains in a short time [11][12][13]. The second design method is a FRIT method, which is a PID controller design approach based on one-shot experimental data only and does not use the mathematical model of the object to be controlled [14][15][16].…”

Section: Introductionmentioning

confidence: 99%

PID Controller Design Methods for Multi-Mass Resonance System

Ikeda¹

2018

PID Control for Industrial Processes

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Motor drive systems are indispensable for applications in the industrial field. High-speed and high-accuracy control is required for motor drive systems. However, solutions to meet these requirements can cause mechanical resonance vibrations to occur in the system as a result of miniaturization and system weight reduction. It is therefore necessary to model these systems as multi-mass resonance systems with multiple masses and finite rigid shafts, gears, and loads. In addition, vibration suppression control should be applied to these systems. This chapter provides two off-line tuning methods for a digital proportional-integral-derivative (PID)-type controller for a two-mass resonance system to suppress its mechanical resonance vibrations. These methods include a coefficient diagram method and a fictitious reference iterative tuning method. The former method uses a nominal mathematical model of the object while the latter method uses only the initial experimental data without use of the mathematical model. In this chapter, the two methods are compared. A controller is proposed that consists of a modified integralproportional derivative (I-PD) speed controller and a proportional-integral (PI) current controller, and requires no information about the load side state variables. Finally, the effectiveness of the proposed method is confirmed through computer simulations and experimental results.

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“…A fuzzy control system using a fuzzy inference is the embodiment of non-mathematical control algorithm, which is constructed by experience and intuition. Several applications brought in the fuzzy control system to motor drive system [11][12][13][14].…”

Section: Introductionmentioning

confidence: 99%

“…Here, the proposed control system is new system that I improved to apply the control system which I already proposed for simulation model in Refs. [13,14] to experimental actual equipment.…”

Section: Introductionmentioning

confidence: 99%

“…The fuzzy controller has three scaling factors, and the PI current controller has two controller gains. In this chapter, a differential evolution algorithm (DE) is utilized the determination of these five controller parameters [13][14][15][16][17][18]. DE, which was proposed by Price and Storn, is one of the evolutionary optimization strategies.…”

Section: Introductionmentioning

confidence: 99%

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Vibration Suppression Controller of Multi-Mass Resonance System Using Fuzzy Controller

Ikeda¹

2017

Modern Fuzzy Control Systems and Its Applications

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Vibration suppression control of the mechanical system is a very important technology for realizing high precision, high speed response and energy saving. In general, the mechanical system is modeled with a multi-mass resonance system, and vibration suppression control is applied. This chapter presents a novel controller design method for the speed control system to suppress the resonance vibration of two-mass resonance system and three-mass resonance system. The target systems are constructed by a motor, finite rigid shafts, and loads. The control system consists of a speed fuzzy controller and a proportional-integral (PI) current controller to realize precise speed and torque response. In order to implement the experimental system, the system is treated as the digital control. This chapter also utilizes a differential evolution (DE) to determine five optimal controller parameters (three scaling factors of the fuzzy controller and two controller gains of PI current controller. Finally, this chapter verified the effectiveness to suppress the resonance vibrations and the robustness of the proposed method by the computer simulations and the experiments by using the test experimental setup.

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Fuzzy Controller of Three-Inertia Resonance System designed by Differential Evolution

Cited by 5 publications

References 10 publications

Vibration Suppression Control of Three Inertial Systems

Vibration Suppression Control of Three Inertial Systems

PID Controller Design Methods for Multi-Mass Resonance System

Vibration Suppression Controller of Multi-Mass Resonance System Using Fuzzy Controller

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