Linear Quadratic Optimal Feedback Research Articles

Mean-square practical stability for uncertain stochastic system with additive noise controlled by optimal feedback

Stability concepts addressed in the framework of Lyapunov are not suitable to analyze the stability of stochastic systems with additive noise since it has no equilibrium. The mean-square practical stability is introduced to study the stability of uncertain stochastic systems with additive noise controlled by linear-quadratic optimal feedback. By using Lyapunov functional methods and the comparison principle, criteria on mean-square practical stability of stochastic systems with partially known uncertainties and norm-bounded parameter uncertainties are deduced, respectively. Some numerical examples and simulations are given to illustrate the validity of the theoretical analysis.

Active Pitch Control in Larger Scale Fixed Speed Horizontal Axis Wind Turbine Systems Part I: Linear Controller Design

This paper reviews and addresses the principles of linear controller design of the fixed speed wind turbine system in above rated wind speed, using pitch angle control of the blades and applying modern control theory. First, the non-linear equations of the system are built in under some reasonable suppositions. Then, the non-linear equations are linearised at set operating point and digital simulation results are shown in this paper. Finally, a linear quadratic optimal feedback controller is designed and the dynamics of the closed circle system are simulated with digital calculation. The advantages and disadvantages of the assumptions and design method are also discussed. Because of the inherent characteristics of the linear system control theory, the performance of the linear controller is not sufficient for operating wind turbines, as is discussed.

A gradient flow approach for computing jump linear quadratic optimal feedback gains

A class of linear systems subject to sudden jumps in parameter values is considered. To solve this class of stochastic control problem, we try to find the best feedback control law depending both on the measurable output as well as the mode of the system. A gradient flow based algorithm is derived for this problem. It is shown that an optimal solution can be successfully computed by finding the limiting solution of an ordinary differential equation which is given in terms of the gradient flow associated with the cost function. Several important properties are obtained. A numerical example is solved.

Sensitivity reducing observers for optimal feedback control

This paper considers the problem of designing an observer for use in a linear quadratic optimal feedback control scheme so as to minimize the effects of small departures in the plant parameters from their nominal values.