FPGA BASED ADAPTIVE NEURO FUZZY INFERENCE CONTROLLER FOR FULL VEHICLE NONLINEAR ACTIVE SUSPENSION SYSTEMS

A Field Programmable Gate Array (FPGA) is proposed to build an Adaptive Neuro Fuzzy Inference System (ANFIS) for controlling a full vehicle nonlinear active suspension system. A Very High speed integratedcircuit Hardware Description Language (VHDL) has been used to implement the proposed controller. Anoptimal Fraction Order PID(FOPID) controller is designed for a full vehicle nonlinear activesuspension system. Evolutionary Algorithm (EA) has been applied to modify the five parameters of theFOPID controller (i.e. proportional constant Kp, integral constant Ki, derivative constant Kd, integralorder and derivative order μ). The data obtained from the FOPID controller are used as a reference todesign the ANFIS model as a controller for the controlled system. A hybrid approach is introduced to trainthe ANFIS. A Matlab Program has been used to design and simulate the proposed controller. The ANFIScontrol parameters obtained from the Matlab program are used to write the VHDL codes. Hardwareimplementation of the FPGA is dependent on the configuration file obtained from the VHDL program. Theexperimental results have proved the efficiency and robustness of the hardware implementation for theproposed controller. It provides a novel technique to be used to design NF controller for full vehiclenonlinear active suspension systems with hydraulic actuators