Theses & Dissertations

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https://hdl.handle.net/20.500.14170/206

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Browsing Theses & Dissertations by Subject "Adaptive Neuro-Controller (ANC)"
  • Publication
    Adaptive neuro-controller design for nano-satellite attitude control
    ( 2012)
    Norhayati Mohd Nazid
    The motivation of this research is to bring the technology of spacecraft control into university education and to bring the possibility of developing our own satellite that will put us of equal standard with other developed nations. The purpose of this research is to develop the control scheme for three axes stabilization of nano-satellite system namely Innovative Satellite (InnoSAT). An adaptive neuro-controller (ANC) is applied as a controller in many application such as in robotics, power system, industries and etc. There are many successfully applications of ANC in controlling the satellite attitude control have been proposed. In this regards, four types of ANCs using two different control scheme and using two different algorithm for nano-satellite attitude control have been introduced in this research. These are ANC based on Model Reference Adaptive Control (MRAC) scheme trained by Back-Propagation (BP) algorithm, ANC based on MRAC scheme trained by Recursive Least Square (RLS) algorithm, ANC based on Internal Model Adaptive Control (IMAC) scheme trained by BP algorithm and ANC based on IMAC scheme trained by RLS algorithm. These two different control schemes are used by the ANC to adjust the output response of InnoSAT to follow the desired target. In this research, BP and RLS algorithms were used as an adjustment mechanism to update the parameters of the ANC. A multilayer perceptron (MLP) network with one hidden layer has the capability to approximate any continuous function up to certain accuracy. It is a very powerful technique in the discipline of control systems, especially when the controlled systems have large uncertainties and strong non- linearities. MLP network is used for ANC in this research. The design of ANC is initially started with design of ANC based on MRAC scheme using BP algorithm. Then, the ANC based on MRAC using RLS algorithm is designed and the performance for both ANCs based on MRAC were compared in term of convergence speed and possible divergence for certain conditions. The design is continued by designing the ANC based on IMAC scheme using BP algorithm and the last part of designing is designed the ANC based on IMAC scheme using RLS algorithm. The performance for both ANC based on IMAC scheme are also compared in term of convergence speed and possible divergence for certain conditions. The simulation results for all ANCs indicated that ANC using RLS algorithm have faster convergence speed compared to the ones trained by BP algorithm. The best ANC based on MRAC and ANC based on IMAC are compared with a conventional proportional, integral and derivative (PID) controller. Simulations have been carried out and for several reference inputs namely unit step, square wave and Y-Thompson. The simulation results are presented and the output responses show that the ANC based on MRAC performance is acceptable even in the case of the InnoSAT is subjected to varying gain, measurement noise, time delay and disturbance. Then, the ANC based on MRAC scheme is simulated with two axes cross coupling system and the simulation results show that the InnoSAT system is stable. The final simulation is tested the ANC with real time attitude reference which is Y-Thompson input reference. The results showed that the ANC based on MRAC scheme can stabilized the InnoSAT system even the system is subjected with varying gain, measurement noise, time delay and disturbance.
  • Publication
    Development of an adaptive neurocontroller and satellite simulator for nano-satellite attitude control system
    ( 2013)
    Siti Maryam Sharun
    Malaysia, a developing country is striding towards venturing the field involving outerspace research. Since 2000, Malaysia has succesfully developed and lauched a few satellites. Therefore, the motivation of this project is to introduce a control technology for satellite implementation riaxial control scheme, for stabilizing system of nano-satellite which is an Innovative veloping a satelit simulator in order ceptron (MLP) controller. All the controllers have used Model Reference Adaptive Control (MRAC) as a control scheme. This modified control scheme was chosen due to its ability in adapting the controller behavior in respond to the changes in the dynamic process and the characteristic of disturbance. Weighted Recursive Least-Square (WRLS) algorithm was used as the adjustment mechanism for updating the parameter of ANC based on HMLP network, ANC based on MLP network and APBB controller. The performances of the four controllers were compared in terms of convergence speed when certain conditions are applied. Simulation was done by using a few reference inputs which consist of step, square wave and Y-Thompsoninput. The simulation results show that ANC based on HMLP is the best controller as compared to the others. The step continues by developing the satellite simulator by using Hardware-in-the-loop simulation (HILS) techniques. The simulator is divided into two parts, software simulator and hardware simulator that will be functioning side by side. The controller algorithm for ANC based on HMLP is uploaded into Microcontroller Rabbit (RCM4100) as the hardware simulator. The software simulator on the other hand was implemented in the PC which represents the dynamic model of InnoSAT. The result shows that the ANC based on HMLP is able to stabilize the InnoSAT system in the real environment even though the system is exposed to varying gain, measurement noise and disturbances. The main contribution of this research is to provide an intelligent control scheme and a hardware-in-loop simulator for satellite attitude control. Satellite simulator that has been developed is expected to produce a concept for testing and analyzing attitude control algorithm in real time environment by having low risk and low cost as well.