Best tracking performance for integrator and dead time plant

The optimal tracking performance for integrator and dead time plant in the case where plant uncertainty and control energy constraints are to be considered jointly is inrestigated. Firstly, an average cost function of the tracking error and the plant input energy over a class of stochastic model errors are defined. Then, we obtain an internal model controller design method that minimizes the average performance and further studies optimal tracking performance for integrator and dead time plant in the simultaneous presence of plant uncertainty and control energy constraint. The results can be used to evaluate optimal tracking performance and control energy in practical designs.

Best Tracking Performance under Plant Uncertainty and Control Energy Constraint

This paper has investigated best tracking performance for linear feedback control systems in the case that plant uncertainty and control effort need to be considered simultaneously. Firstly, an average integral square criterion of the tracking error and the plant input energy over a class of additive model errors is defined. Then, utilizing spectral factorization to minimize the performance index, we obtain an optimal controller design method, and furthermore study optimal tracking performance under plant uncertainty and control energy constraint. The results can be used to evaluate optimal average tracking performance and control energy in designing practical control systems.

Optimal robust control for linear feedback systems in the presence of plant uncertainty

This paper has investigated how the optimization methods can be used to deal with plant uncertainty in linear feedback control design. Firstly, we define a weighted sensitivity error function based on robust redesign. Then, by modifying the nominal controller to minimize the variance of the actual system performanee from the desired performance over the whole frequency range, we obtain an optimal robust design method for a class of stochastic model errors. Moreover, the result can be used to give a good prediction to the achievable average tracking performance and control energy for practical system designs. The validity of obtained results can be illustrated by the simulation research.

Autopilot Control Synthesis for Path Tracking Maneuvers of Underwater Vehicles

This paper is concerned with the robust control synthesis of autonomous underwater vehicle （AUV） for general path following maneuvers. First, we present maneuvering kinematics and vehicle dynamics in a unified framework. Based on H∞ loop-shaping procedure, the 2-DOF autopilot controller has been presented to enhance stability and path tracking. By use of model reduction, the high-order control system is reduced to one with reasonable order, and further the scaled low-order controller has been analyzed in both the frequency and the time domains. Finally, it is shown that the autopilot control system provides robust performance and stability against prescribed levels of uncertainty.

Best performance analysis for stochastic perturbation systems with spectral factorization

We investigate the best performance for linear feedback control systems in the case that plant uncertainty is to be considered. First, we define an average integral square criterion of tracking error over a class of stochastic model errors. By utilizing spectral factorization to minimize the performance index, we derive an optimal controller design method and further study best performance in the presence of stochastic perturbation. The results can be used to evaluate optimal performance in practical control system designs.