Tracking Control Via Linear Quadratic Gaussian and Guaranteed Cost Output Feedback Control to a DC Motor Reaction Wheel

2017 ◽  
Vol 10 (1) ◽  
pp. 49
Author(s):  
Erwin Susanto ◽  
I. Prasetya Dwi Wibawa ◽  
Heroe Wijanto
2013 ◽  
Vol 53 ◽  
pp. 233-240 ◽  
Author(s):  
M.Nizam Kamarudin ◽  
S.Md. Rozali ◽  
A.Rashid Husain

Author(s):  
Shusaku Nishikawa ◽  
◽  
Jun Yoneyama

This paper is concerned with the stability with guaranteed cost for a fuzzy system with immeasurable premise variables via output feedback. It is well known that Takagi-Sugeno fuzzy model describes a wide class of nonlinear systems especially when its premise variables include immeasurable functions. However, when it comes to output feedback control design of such a fuzzy system, a conventional Parallel Distributed Compensator (PDC) is not feasible because the PDC shares the same immeasurable premise variables as those of a fuzzy system. In this paper, we introduce an output feedback controller with the estimate of the premise variables of an original fuzzy system. We then formulate the stabilization problem with guaranteed cost for a fuzzy system with immeasurable premise variables. Our control design method is based on a set of strict LMI conditions. No tuning parameter is necessary a priori to solve them. The stability with guaranteed cost takes care of not only stabilization but also control performance. Our proposed method attempts to minimize the upper bound of the performance index, which results in the satisfactory trajectories of the system. Finally, numerical examples are given to illustrate our control design method.


2021 ◽  
Vol 21 (2) ◽  
pp. 79
Author(s):  
Supriyanto Praptodiyono ◽  
Hari Maghfiroh ◽  
Joko Slamet Saputro ◽  
Agus Ramelan

The electric motor is one of the technological developments which can support the production process. DC motor has some advantages compared to AC motor especially on the easier way to control its speed or position as well as its widely adjustable range. The main issue in the DC motor is controlling the angular speed with uncertainty and disturbance. The alternative solution of a control method with simple, easy to design, and implementable in a multi-input multi-output system is integral state feedback such as linear quadratic Gaussian (LQG). It is a combination between linear quadratic regulator and Kalman filter. One of the advantages of this method is the usage of fewer sensors compared with the original linear quadratic regulator method which uses sensors as many as the state in the system model. The design, simulation, and experimental study of the application of LQG as state feedback control in a DC-drive system have been done. Both performance and energy were analyzed and compared with conventional proportional integral derivative (PID). The gain of LQG was determined by trial whereas the PID gain is determined from MATLAB autotuning without fine-tuning. The load test and tracking test were carried out in the experiment. Both simulation and hardware tests showed the same result which LQG is superior in integral absolute error (IAE) by up to 74.37 % in loading test compared to PID. On the other side, LQG needs more energy, it consumes higher energy by 6.34 % in the load test.


2015 ◽  
Vol 9 (2) ◽  
pp. 232-239 ◽  
Author(s):  
Liu Xi ◽  
Liu Shuguang ◽  
Cai Ming ◽  
Sun Xiuxia ◽  
Xu Song

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