A recent significant progress has been made in development of intelligent mobile robots that is capable of autonomous navigation using an edge-computing system. This could sense changes in its environment to control its mechanical behavior towards accomplishing preprogrammed motions. Several algorithms were used in developing the robot's control software. These include the moving average filter, the extended Kalman filter, and the covariance algorithm. Using these algorithms, the robot could learn from its sensors to estimate and control its position, velocity, and the proximity of obstacles along its path, while autonomously navigating to a predetermined location on the earth's surface. Results show that our algorithmic approach to developing software systems for autonomous robots using edge-computing devices is viable, cost-efficient, and robust. Hence, our work is a proof of concept for the further development of edge-based intelligence and autonomous robots.

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The heat exchanger is a device that helps to circulate calculated amount of heat in a system. It can be applied in order to reduce the number of heat sources while maintaining a precise level of heat. Heat exchanger is expected to be part of the solution to CO2 emission and climate issues since its application reduces the sources of heat and cost of production such as in electrical power plant. Due to the critical need for the solution to the enormous emission of CO2 and the need to reduce cost of running power plants, the study and improvement of the heat exchanger has become very important.  The heat exchanger suffers from disturbances due to its harsh environment. In order to maintain desired performance the heat exchanger requires an adequate control measure. Many types of controllers have been designed, however from the review it was observed that most of the controllers produced marginal stability which will not maintain good performance of the system in the presence of significant disturbance. The major objectives of this work are to reduce the tracking error for performance improvement, to reduce the peak sensitivity for better disturbance rejection and to improve the stability margins for stability robustness. In this work, an optimal robust control was developed for the heat exchanger using H2 synthesis technique. From the results, the controlled system trajectory tracking error and overshoot were reduced to zero and the peak sensitivity to disturbance was reduced to 0.189 dB. Gain and phase margins satisfied the robust stability characteristics; gain margin was greater than 20 dB and phase margin was greater 60 dB. This means that the designed optimal controller will guarantee robust performance and stability of the system even in the presence of large disturbance.

The flexible joint robot is gaining more popularity in research and development because of its light weight and numerous applications. The major problems of the flexible joint robotic manipulator are poor tracking performance and instability. This work aims at improving the tracking performance and stability of the flexible joint robot based on the tracking error, damping time, overshoot and stability margins of the flexible joint model. To achieve this, a mixed synthesis method was applied. The mixed sensitivity synthesis is a robust control technique which uses adjustable weights to design a robust controller model which improves the performance and stability of a plant through loop shaping. From the results, the flexible joint model recorded damping time of infinity which is very high, gain margin of 22.8dB and very low phase margin of 3.21e-12deg. This means that the flexible joint model suffers from poor performance and it is unstable. The mixed synthesis controlled flexible joint model recorded low damping time of 0.993seconds, overshoot of 0%, tracking error of 0.0214dB, gain margin of 24.9dB and phase margin of 86.9degrees. This means that the mixed sensitivity synthesis controlled FJR achieved improved tracking performance and robust stability. The mixed synthesis control technique maintained negligible changes in damping time, tracking error and stability margins when the joint flexibility coefficient of the joint was varied to verify the robustness of the system. The work concludes that the flexible joint tracking performance and stability improvement was achieved using mixed sensitivity synthesis.

Design and implementation of a fuzzy logic controller for power plant temperature monitoring and control used fuzzy lite software to simulate using triangular method and compared with bell shape membership function. Fuzzy logic technology was deployed; the motor temperature and RPM being used as crisp inputs to the fuzzy logic controller with appropriate membership function definitions. The fuzzy logic was designed and simulated using the Fuzzy Lite and Proteus software. It was implemented as firmware written in C++ programming language being executed on the PIC16F877A microcontroller. The results gotten from the simulations and implementation were in concordance as variations in motor temperature influenced motor speed. Triangular method used in this work was compared with Bell shape method used in previous work to ascertain its contribution to knowledge and also discovered that triangular method is more precise in its result.