This paper presents the modeling of a robot's navigation using ultrasonic sensors under uncertainty. The robot tries to avoid obstacles by using the fuzzy logic controller to process the data coming from three ultrasonic sensors. To assess the performance of fuzzy logic optimized robot navigation controller with ultrasonic sensors, which measure the distance by calculating the time spent on the object and its return, the obstacles are placed in front of, left, and right of the robot.  Mamdani fuzzy reasoning system is used for the designed controller for its intuitive properties and fewer setting parameters which reduces the amount of time spent on the programming of the controller. 25 rules are considered to cover a robot’s possible interactions with obstacles. For an easy understanding of navigation architecture and rapid algorithm implementation, in this paper, a MATLAB simulation framework is developed. MATLAB/Simulink is one of the best simulation tools required to design the architecture and verify algorithms with real-time constraints. Resultant models of the fuzzy optimized controller demonstrate the superior performance of the fuzzy logic controller with high adaptability to the environment while maintaining a sufficient level of accuracy. The designed fuzzy controller can be used in microprocessor/microcontroller-based robots owing to easiness in implementation and coding.

The article is devoted to the approximation problems of functional dependencies during conversions performed in intelligent measurement devices. Non-linearities are essential parts of most control processes and systems. When using a nonlinear transmitter with a conversion function in measurement information systems used in various fields, it is necessary to perform nonlinear functional conversion operations on numbers in microprocessors/microcontrollers during direct and indirect measurements. For this purpose, various approximation methods are used. The purpose of the approximation is to describe nonlinear functions in a simpler, more convenient way for utilization and calculations, with an insignificantly small loss of accuracy. Existent methods for linearization, although some of them are effective, can be burdensome for implementation in microprocessor-based systems. Here, one of the proposed methods for the approximation of nonlinear functional dependencies by line segments is proposed. In this method, the range of the argument changes in the function is divided into line segments, and the parts of the coordinate system bisector, remaining within the line segments of the function, is swapped to perform approximation. Having involved few simple mathematical operations, the proposed method can be implemented efficiently in microprocessors/microcontrollers to perform approximations in measurement systems.