scholarly journals Self-tuning Speed Controller with Load Parameters Observer for Servo Drives

Author(s):  
Anastasia Kotelnikova ◽  
Alexey Dmitriev ◽  
Yuriy Vagapov ◽  
Maxim Lashkevich ◽  
Nikolay Kuraev ◽  
...  
2014 ◽  
Vol 20 (6) ◽  
Author(s):  
J. Kriauciunas ◽  
R. Rinkeviciene ◽  
A. Baskys

2018 ◽  
Vol 80 (2) ◽  
Author(s):  
Satishrao Pothorajoo ◽  
Hamdan Daniyal

Brushless Direct Current (BLDC) motors have gained popularity in recent years due to their high-power density. Many type of speed controller techniques have been developed and Proportional Integral Derivative (PID) controller has been the most widely used. However, PID’s performance deteriorates during nonlinear loads conditions. Over the past five years, controllers have been developed to overcome this limitations in BLDC speed control, however the solutions are focusing on forward motoring only. In this paper, a speed controller for BLDC with seamless speed reversal using Modified Fuzzy Gain Scheduling is proposed. The proposed controller regulates the speed using Fuzzy Gain Scheduling 49 base rules. The controller was tested for six test cases and compared to PID and Self-Tuning Fuzzy PID controller. It is found out the proposed controller yields lowest steady state error, ess of 0.025 % during step-changing speed test case. Overall, Modified Fuzzy Gain Scheduling BLDC speed controller outperforms the other two similar controllers in variable speed conditions. The controller has potential to be used as bidirectional drive in highly dynamic load conditions.


2015 ◽  
Vol 815 ◽  
pp. 408-412
Author(s):  
M.N. Azuwir ◽  
Mohd Sazli Saad ◽  
Mohd Zakimi Zakaria

This paper investigates the performance of a real-time self-tuning speed controller designed to track and regulate at various engine speeds. The controller was tested with an automotive engine fuelled with petroleum diesel and and palm oil biodiesel (Palm Methyl Esters) within speed range of 1800 rpm to 2400 rpm. A self-tuning control algorithm based on pole assignment method together with on-line model parameters estimation strategy based on the recursive least squares method are adopted. The ability of the controller to track, regulate at various engine speed and also to reject disturbances applied for both type of fuel are compared and presented. The results confirmed that the controller performed very satisfactorily.


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