Enhancement of tracking performance in electro-optical system based on servo control algorithm

2017 ◽  
Author(s):  
SungSu Kim ◽  
DaeYoon Jung ◽  
HyoungKyu Seo ◽  
WooJin Choi
Keyword(s):  
Optical System ◽  
Control Algorithm ◽  
Servo Control ◽  
Tracking Performance

Barrier Lyapunov function-based robot control with an augmented neural network approximator

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Zuguo Zhang ◽  
Qingcong Wu ◽  
Xiong Li ◽  
Conghui Liang
Keyword(s):  
Neural Network ◽  
Lyapunov Function ◽  
Control Algorithm ◽  
Tracking Performance ◽  
Content Type ◽  
Barrier Lyapunov Function ◽  
Output Error ◽  
Control Scheme ◽  
Stringent Constraint ◽  
Continuous Dynamic

Purpose Considering the complexity of dynamic and friction modeling, this paper aims to develop an adaptive trajectory tracking control scheme for robot manipulators in a universal unmodeled method, avoiding complicated modeling processes. Design/methodology/approach An augmented neural network (NN) constituted of radial basis function neural networks (RBFNNs) and additional sigmoid-jump activation function (SJF) neurons is introduced to approximate complicated dynamics of the system: the RBFNNs estimate the continuous dynamic term and SJF neurons handle the discontinuous friction torques. Moreover, the control algorithm is designed based on Barrier Lyapunov Function (BLF) to constrain output error. Findings Lyapunov stability analysis demonstrates the exponential stability of the closed-loop system and guarantees the tracking errors within predefined boundaries. The introduction of SJFs alleviates the limitation of RBFNNs on discontinuous function approximation. Owing to the fast learning speed of RBFNNs and jump response of SJFs, this modified NN approximator can reconstruct the system model accurately at a low compute cost, and thereby better tracking performance can be obtained. Experiments conducted on a manipulator verify the improvement and superiority of the proposed scheme in tracking performance and uncertainty compensation compared to a standard NN control scheme. Originality/value An enhanced NN approximator constituted of RBFNN and additional SJF neurons is presented which can compensate the continuous dynamic and discontinuous friction simultaneously. This control algorithm has potential usages in high-performance robots with unknown dynamic and variable friction. Furthermore, it is the first time to combine the augmented NN approximator with BLF. After more exact model compensation, a smaller tracking error is realized and a more stringent constraint of output error can be implemented. The proposed control scheme is applicable to some constraint occasion like an exoskeleton and surgical robot.

Numerical Simulation of a Prediction Control Algorithm for Close-Loop Adaptive Optical System

2011 ◽  
Vol 31 (1) ◽  
pp. 0101003
Author(s):  
颜召军 Yan Zhaojun ◽  
李新阳 Li Xinyang ◽  
饶长辉 Rao Changhui
Keyword(s):  
Numerical Simulation ◽  
Optical System ◽  
Control Algorithm ◽  
Adaptive Optical System ◽  
Prediction Control

Reserve-driven flow control for extracorporeal life support: proof of principle

Perfusion ◽  
2010 ◽  
Vol 25 (1) ◽  
pp. 25-29 ◽  
Author(s):  
AP Simons ◽  
KD Reesink ◽  
MD Lancé ◽  
T. van der Nagel ◽  
FH van der Veen ◽  
...  
Keyword(s):  
Control Strategy ◽  
Control Algorithm ◽  
Continuous Monitoring ◽  
Life Support ◽  
Extracorporeal Life Support ◽  
Servo Control ◽  
Low Flow ◽  
Circulatory Support ◽  
Control Schemes ◽  
Proof Of Principle

Extracorporeal life support systems lack volume-buffering capacity. Therefore, any decrease in venous intravascular volume available for drainage may result in acutely reduced support flow. We recently developed a method to quantify drainable volume and now conceived a reserve-driven pump control strategy, which is different from existing pressure or flow servo control schemes. Here, we give an outline of the algorithm and present animal experimental data showing proof of principle. With an acute reduction in circulatory volume (10-15%), pump flow immediately dropped from 4.1 to 1.9 l/min. Our pump control algorithm was able to restore bypass flow to 3.2 l/min (about 80% of the original level) and, thereby, reduced the duration of the low-flow condition. This demonstrates that a reserve-driven pump control strategy, based on the continuous monitoring of drainable volume, may maintain extracorporeal circulatory support flow, despite serious changes in filling conditions.

A Novel Two-Degrees-of-Freedom Voice Coil Motor and its PID Controllers for Linear and Rotary Motions

2013 ◽  
Vol 303-306 ◽  
pp. 1635-1640
Author(s):  
Xi Qing Jia ◽  
Shou Bin Liu
Keyword(s):  
Pid Control ◽  
High Speed ◽  
Control Algorithm ◽  
Degrees Of Freedom ◽  
Voice Coil Motor ◽  
Settling Time ◽  
Servo Control ◽  
Pid Controllers ◽  
Two Degrees Of Freedom ◽  
Actual Environment

A two-degrees-of-freedom voice coil motor and its control system are proposed for linear and rotary motions with high speed. This VCM consists of two individual motion parts driven by two separated DSP embedded controllers. For servo control of the VCM, an improved PID control algorithm is adopted. The performance of the control algorithm is evaluated under actual environment. When the targets of position and angle are set at 5mm and 15°, the time response shows 48ms and 70.4ms settling time with 5μm and 3’ steady state error without overshoot. Settling time is reduced to 36% as compared to that of original PID controller.

Prediction Control Algorithm for Close-loop Adaptive Optical System

2013 ◽  
Vol 46 (5) ◽  
pp. 276-284
Author(s):  
YAN Zhao-jun ◽  
LI Xin-yang ◽  
RAO Chang-hui
Keyword(s):  
Optical System ◽  
Control Algorithm ◽  
Adaptive Optical System ◽  
Prediction Control
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