Excitation Trajectory Optimization with Power Constraints for Parameter Estimation

This paper addresses trajectory optimization for the excitation of systems with uncertain parameters, subject to input power constraints. Since the input required to follow a given trajectory depends on the system parameters which are to be estimated, this task is non-trivial. Therefore, we present worst-case and chance constraints to limit the short-time average power demand and optimize the excitation trajectory for energy-based parameter estimation. The effectiveness of our approach is verified through extensive simulation experiments. The results demonstrate that the optimized trajectories can be followed without violating power constraints and yield better parameter estimates compared to randomly selected trajectories, both under low and high power limits.