This paper has designed a variable structure controller based on the nominal compensation of neural networks. The neural network input is the desired trajectory, which eliminates the strict assumptions of the control inputs in conventional neural networks. It also ensures the asymptotic stability of the system closed-loop global exponentials to introduce model compensation and continuous variable structure control rate. By means of Lyapunov stability theory, it is analyzed and researched how to guarantee good transient performance of the control system comprehensively and thoroughly. The theoretic analysis and simulation results demonstrate the efficiency of the method proposed.
This paper focuses on the hardware development of an indoor ultrasound based robot localization system. The problems related to the ultrasound based distance measurements are presented and solutions are proposed related to Time of Flight measurements and measurement synchronization. An optimization based compensation method is introduced to attenuate the effect of the ambient temperature on the distance measurement precision. Experimental measurements were performed to analyze the applicability of the developed system and measurement methods.
This paper focuses on the hardware development of an indoor ultrasound based robot localization system. The problems related to the ultrasound time of flight measurements are presented and solutions are proposed related to the hardware applied for measurements and measurement synchronization. Experimental measurements were performed to analyze the applicability of the developed system and measurement methods.
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