Development of a novel linear magnetic actuator with trajectory control based on an online tuning fuzzy PID controller

Dinh, Truong Quang; Thanh, Trương Quốc; Ahn, Kyoung Kwan

doi:10.1007/s12541-012-0184-2

Cited by 16 publications

(4 citation statements)

References 20 publications

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“…Fig. 2 Lunar regolith sampling head [1] lid, [2] transducer horn, [3] the shell of the sampling motor, [4]coupling, [5] fixed spoon, [8] rotating sampling spoon.…”

Section: Mechanical Design Of the Flexible Lunar Regolith Samplermentioning

confidence: 99%

“…But the dynamical modeling of the sampler-regolith system is difficult to obtain and time varies when the sampler is in different depth in the lunar regolith. So far as we know, the existing controlling methods of vibration are mostly achieving the reduction of vibration [5][6][7][8]. Besides that, the micro-vibrating is about dozens kHz [9,10]which is far from that of the flexible sampler whose resonant frequency is about several to dozens of Hertz.…”

Section: Introductionmentioning

confidence: 99%

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Vibration Frequency Fuzzy Adaptive Control of the Flexible Lunar Regolith Sampler Based on the Dynamic Pediction by Uing the RBFNN

Lü

Zeng²,

Song³

et al. 2012

AMM

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The drilling efficiency can be improved effectively by controlling the lunar regolith sampler always in the resonance state. But the dynamical modeling of the sampler-regolith system is difficult to obtain and time varies when the sampler is in different depth in the lunar regolith. For the nonlinear time-varying system of the dynamic modeling of the sampler in drilling, we present a method of the vibration frequency fuzzy adaptive control based on the dynamic prediction by using the RBFNN. The Radial Basis Function (RBF) neural network with a FIR filter in series is used to predict the resonant frequency dynamically and decrease the overshoot. And the fuzzy adaptive control is used to calculate the sweeping frequency bandwidth with the input of the amplitude and variation. The simulation results have verified the effectiveness of the control strategy. The experimental results show that the control algorithm can improve the drilling depth, drilling efficiency and the discarding efficiency effectively.

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“…Fig. 2 Lunar regolith sampling head [1] lid, [2] transducer horn, [3] the shell of the sampling motor, [4]coupling, [5] fixed spoon, [8] rotating sampling spoon.…”

Section: Mechanical Design Of the Flexible Lunar Regolith Samplermentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Vibration Frequency Fuzzy Adaptive Control of the Flexible Lunar Regolith Sampler Based on the Dynamic Pediction by Uing the RBFNN

Lü

Zeng²,

Song³

et al. 2012

AMM

View full text Add to dashboard Cite

show abstract

“…Such methods provide optimal results and can be implemented because they do not contain a lot of mathematical equations. PID Control is a linear control for linear systems such as magnetic actuator [11], Position Control [12], Trajectory Control [13], Brushless DC motors [14], and Brushed DC Motor [15] so that the PID controller has been widely used by some researchers for example by Ziegler Nichols [16], as a motor controllers since PID has a simple structure with a method of determining a common PID parameter, thus it has the ability in suppressing an interference well. However, it results in a large percentage of overshoot and the control signaling used tends to be large, which may cause saturation in the actuator.…”

Section: Introductionmentioning

confidence: 99%

Hover Position of Quadrotor Based on PD-like Fuzzy Linear Programming

Iswanto

Wahyunggoro

Cahyadi

2016

IJECE

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The purpose of this paper is to present the altitude control algorithm for quadrotor to be able to fly at a particular altitude. Several previous researchers have conducted studies on quadrotor altitude by using PID control but there are problems in the overshoot and oscillation. To optimize the control, tunning on PID algorithm must be first conducted to determine proportional and derivative constants. Hence, the paper presents altitude control modification by using PID-like fuzzy without tuning. The PID algorithm is a control algorithm for linear systems. While, system to be controlled is a non-linear, so that linearization is needed by using equilibrium. The proposed algorithm is a modification of the PID algorithm used as an altitude control which enables quadrotor to be stable when hovering. The algorithm used is not PID algorithm with tuning using fuzzy, but this is a single input single output (SISO) control PID-like fuzzy linear programming. The result of the research shows that quadrotor can hover in a rapid raise time, steady state and settling time without performing overshoot and oscillation.

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Section: Introductionmentioning

confidence: 99%

Hover Position of Quadrotor Based on PD-like Fuzzy Linear Programming

Iswanto

Wahyunggoro

Cahyadi

2016

IJECE

View full text Add to dashboard Cite

<p>The purpose of this paper is to present the altitude control algorithm for quadrotor to be able to fly at a particular altitude. Several previous researchers have conducted studies on quadrotor altitude by using PID control but there are problems in the overshoot and oscillation. To optimize the control, tunning on PID algorithm must be first conducted to determine proportional and derivative constants. Hence, the paper presents altitude control modification by using PID-like fuzzy without tuning. The PID algorithm is a control algorithm for linear systems. While, system to be controlled is a non-linear, so that linearization is needed by using equilibrium. The proposed algorithm is a modification of the PID algorithm used as an altitude control which enables quadrotor to be stable when hovering. The algorithm used is not PID algorithm with tuning using fuzzy, but this is a single input single output (SISO) control PID-like fuzzy linear programming. The result of the research shows that quadrotor can hover in a rapid raise time, steady state and settling time without performing overshoot and oscillation.</p>

show abstract

Development of a novel linear magnetic actuator with trajectory control based on an online tuning fuzzy PID controller

Cited by 16 publications

References 20 publications

Vibration Frequency Fuzzy Adaptive Control of the Flexible Lunar Regolith Sampler Based on the Dynamic Pediction by Uing the RBFNN

Vibration Frequency Fuzzy Adaptive Control of the Flexible Lunar Regolith Sampler Based on the Dynamic Pediction by Uing the RBFNN

Hover Position of Quadrotor Based on PD-like Fuzzy Linear Programming

Hover Position of Quadrotor Based on PD-like Fuzzy Linear Programming

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