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This study presents a design of an adaptive neuro-fuzzy controller for tractors’ tillage operations. Since the classical controllers allows plowing depth errors due to the variations of lands structure, the use of the combined neural networks and fuzzy logic methods decreases these errors. The proposed controller is based on Adaptive Neuro-Fuzzy Inference System (ANFIS), which permits the generation of fuzzy rules to cancel the nonlinearity and disturbances on the implement. The design and simulations of the system, which consist of a hitch-implement mechanism, an electro-hydraulic actuator, and a neuro-fuzzy controller, are conducted in SolidWorks and MATLAB software. The performance of the proposed controller is analyzed and is contrasted with a Proportional Integral Derivative (PID) controller. The obtained results show that the neuro-fuzzy controller adapts perfectly to the dynamics of the system with rejection of disturbances.

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The transit of reactive power through the electric transport lines due to the inductive loads, creates problems of instabilities on the electrical networks. Transport networks are increasingly vulnerable to instability of voltage due to industrialization and/or population growth. The managers of these networks are therefore seeking effective solutions to these problems. STATCOM is one of the devices of the family of shunt FACTS used for reactive energy compensation. It generally offers better features compared other FACTS devices and conventional reactive compensation devices. This work aims to apply the STATCOM controlled by the current control method by hysteresis bands for the maintenance of the voltage in an electric transport network. The transport network is modeled as a transport line in MATLAB/SIMULINK and its characteristics are compared to the system without STATCOM.