Application of fictitious reference iterative tuning to vibration suppression controller for 2-inertia resonance system

Ikeda, Hidehiro; Ajishi, Hideki; Hanamoto, Tsuyoshi

doi:10.1109/iecon.2015.7392366

Cited by 5 publications

(6 citation statements)

References 11 publications

(11 reference statements)

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“…Similarly, several shafts and gears are approximated as a single torsional shaft. The typical two-mass model is depicted schematically in Figure 1 below [14][15][16][17].…”

Section: Description Of Two-mass Resonance Modelmentioning

confidence: 99%

“…The coefficient a i can then be calculated using τ and the stability indices γ i as shown in Eq. (15).…”

Section: Modified-ipd Speed Controller and Pi Current Controllermentioning

confidence: 99%

“…In this section, an off-line tuning method for the vibration suppression-type speed and current controller gains for the two-mass system is proposed based on the FRIT method; this method uses only single-shot experimental input-output data and does not use either the model parameters or the state equation of the two-mass resonance model. While most FRIT designs only use one state variable, this method uses specific multiple state variables to design the controller gains when using the FRIT method [6,7,[14][15][16]. Figure 14 shows a typical control system, in which G is the transfer function of the object to be controlled, r is the reference signal, r represents the controller gains, C(r) represents the controller, u is the control input parameter, and y is the output parameter.…”

Section: Controller Design Using Fictitious Reference Iterative Tuninmentioning

confidence: 99%

“…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]. The effectiveness of the two proposed design methods is confirmed using a combination of computer simulations and experiments.…”

Section: Introductionmentioning

confidence: 99%

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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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“…Similarly, several shafts and gears are approximated as a single torsional shaft. The typical two-mass model is depicted schematically in Figure 1 below [14][15][16][17].…”

Section: Description Of Two-mass Resonance Modelmentioning

confidence: 99%

“…The coefficient a i can then be calculated using τ and the stability indices γ i as shown in Eq. (15).…”

Section: Modified-ipd Speed Controller and Pi Current Controllermentioning

confidence: 99%

Section: Controller Design Using Fictitious Reference Iterative Tuninmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

PID Controller Design Methods for Multi-Mass Resonance System

Ikeda¹

2018

PID Control for Industrial Processes

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“…Refs. [9,10] previously proposed a controller gain tuning method for a vibration suppression-type speed controller using fictitious reference iterative tuning (FRIT) for single-input multi-variable control objects without knowledge of the system state equations and the parameters.…”

Section: Introductionmentioning

confidence: 99%

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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Data-Driven Design of Predictive Functional Control Based Feed-Forward Disturbance Rejection Controller

Ashida,

Obika

2024

IFAC-PapersOnLine

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Application of fictitious reference iterative tuning to vibration suppression controller for 2-inertia resonance system

Cited by 5 publications

References 11 publications

PID Controller Design Methods for Multi-Mass Resonance System

PID Controller Design Methods for Multi-Mass Resonance System

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

Data-Driven Design of Predictive Functional Control Based Feed-Forward Disturbance Rejection Controller

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