In the presence of plant uncertainties, utilizing an appropriate controller for a smooth output tracking and elimination of high-frequency disturbances, especially in accurate systems is very important. In this paper, a controller is proposed based on the robust and optimal theory to achieve a combination of such characteristics in the face of model parameter variations and unknown disturbances. The proposed controller has been simulated on a three-axis gyro-stabilized MIMO platform and comparison results with a NLPID controller simulation are provided.

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The reliability of an intelligent self tuning controller called the brain emotional learning based intelligent controller (BELBIC) to attitude control of a nonlinear launch vehicle (LV) simulation with hardware-in-the loop simulation (HILS) is studied. To set up the HIL system of the LV a six-degree of freedom simulation of the LV and a hydraulic actuator, which was used for the pitch channel thrust vector control (TVC) actuator of the LV, is performed. The results of the BELBIC controller with a fuzzy controller (FC) and a PID controller in this HILS of the LV to control the pitch channel of the LV have been compared.

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