This Is AuburnElectronic Theses and Dissertations

Design and Implementation of Digital Controllers for Buck and Boost Converters Using Linear and Nonlinear Control Methods




Guo, Liping

Type of Degree



Electrical and Computer Engineering


Issues in the design and implementation of digital controllers for a buck converter and a boost converter using linear and nonlinear control methods were investigated in this dissertation. The small signal models of the buck and boost converters, obtained using standard state space averaging techniques, were utilized in the dissertation. Analog PID and PI controllers were designed for generic buck and boost converters using standard frequency response techniques. The controllers were then transformed into digital controllers. The small signal models of the converters change with the variations of the operating point. Since the linear controllers were designed based on the small signal models, they were not able to respond effectively to changes in operating point. To achieve a stable and fast response, nonlinear control methods were applied to the buck and boost converters. Since fuzzy controllers don’t require a precise mathematical model, they are well suited to nonlinear, time-variant systems. Fuzzy controllers were designed for the buck and boost converters. Two structures of fuzzy controllers are investigated in this dissertation. Only one structure was applied to the buck converter, and both structures were applied to the boost converter to obtain satisfactory response. The second nonlinear control method investigated in this dissertation was sliding mode fuzzy controller. The sliding mode fuzzy controller combined the advantages of both fuzzy controllers and sliding mode controllers. Sliding mode fuzzy controllers are designed for the boost converter. The digital controllers designed using linear and nonlinear control methods were implemented on a TI DSP. Experimental results for the buck and boost converters were presented and compared. Experimental results verify that nonlinear controllers have superior performance over linear controllers under the change of operating points.