Control of a DC motor : comparing classical and adaptive techniques /

Abstract

The intent of this project is to compare and contrast the advantages and disadvantages of using adaptive techniques as opposed to classical ones in the control of a DC motor. To that end Root Locus and the adaptive techniques of self-tuning regulation, one-step ahead adaptive control, and model-reference adaptive control are presented. The controllers are designed based on a model that is commonly used for a DC motor. To investigate the effect of a non-ideal model on the controlled system, several variations are considered. The effect of model mismatch is investigated by making the order ofthe plant and the type ofthe plant higher than the assumed model for controller design. Furthermore, the effect of load on the motor as well as the presence of additive noise is considered. The Root-Locus designed controller does not meet the criteria in most non-ideal situations. The self-tuning regulator meets the design criteria in all the non-ideal cases, but has a high control effort before the parameter estimates converge, after which the control effort is more reasonable. The weighted modelreference adaptive system best meets the design criteria with the least control effort in all the non-ideal cases if the model used to design the controller has been overparameterized. This thesis concludes with a summary ofthe project results and ideas for future research topics.

The intent of this project is to compare and contrast the advantages and disadvantages of using adaptive techniques as opposed to classical ones in the control of a DC motor. To that end Root Locus and the adaptive techniques of self-tuning regulation, one-step ahead adaptive control, and model-reference adaptive control are presented. The controllers are designed based on a model that is commonly used for a DC motor. To investigate the effect of a non-ideal model on the controlled system, several variations are considered. The effect of model mismatch is investigated by making the order ofthe plant and the type ofthe plant higher than the assumed model for controller design. Furthermore, the effect of load on the motor as well as the presence of additive noise is considered. The Root-Locus designed controller does not meet the criteria in most non-ideal situations. The self-tuning regulator meets the design criteria in all the non-ideal cases, but has a high control effort before the parameter estimates converge, after which the control effort is more reasonable. The weighted modelreference adaptive system best meets the design criteria with the least control effort in all the non-ideal cases if the model used to design the controller has been overparameterized. This thesis concludes with a summary ofthe project results and ideas for future research topics.