Name
Abstract | ||
|---|---|---|
We present in this paper our preliminary results on the problem of learning-based adaptive trajectory tracking control for electromagnetic actuators. First, we develop a nominal nonlinear backstepping controller that stabilizes the tracking errors asymptotically and globally. Second, we robustify the nominal controller using a model-free learning technique, namely, multiparameter extremum seeking, to estimate the uncertain model parameters. In this sense we are proposing to solve an adaptive control problem with model-free learning-based algorithms. We show the performance of the proposed controller on a numerical example. |
Year | Venue | Keywords |
|---|---|---|
2013 | Control Conference | adaptive control,asymptotic stability,control nonlinearities,electromagnetic actuators,learning systems,nonlinear control systems,optimal control,trajectory control,asymptotic racking error stability,learning-based adaptive trajectory tracking control,model-free learning technique,model-free learning-based algorithms,multiparameter extremum seeking,nonlinear backstepping controller,nonlinear learning-based adaptive control,electromagnetics,trajectory,actuators,uncertainty,backstepping,robustness |
Field | DocType | Citations |
Control theory,Optimal control,Nonlinear system,Control theory,Control engineering,Backstepping controller,Exponential stability,Adaptive control,Mathematics,Trajectory,Actuator | Conference | 0 |
PageRank | References | Authors |
0.34 | 0 | 2 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Benosman, M. | 1 | 0 | 0.34 |
| Gökhan M. Atinç | 2 | 7 | 1.22 |