Variable feedback gain control design based on particle swarm optimizer for automatic fighter tracking problems

The main focus of this paper is to develop an optimization method for the automatic fighter tracking (AFT) problem. The AFT problem is similar to a general evader–pursuer maneuvering automation problem between the dynamic systems of two highly interactive objects. This paper proposes a particle swarm optimizer-based variable feedback gain controller (PSO-based VFGC) for dealing with AFT problems. The PSO-based VFGC is designed to obtain the control value of a pursuer through an error-feedback gain controller. Once conditions of system closed-loop stability have been satisfied, the optimal feedback gains can be obtained through PSO, and the actual control values can be derived from the obtained values. Simulation results confirm the capabilities of the proposed method by comparing the results against two other methods in the field: the weight matrix value defined Ricatti equation, and the linear matrix inequality (LMI) based linear quadratic regulator (LQR). The performance of the proposed method is superior to that of its alternatives.

Graphical abstractFigure optionsDownload full-size imageDownload as PowerPoint slideHighlights► A PSO-based variable feedback gain controller (PSO-based VFGC) to deal with the automatic fighter tracking (AFT) problem. ► The PSO-based VFGC is designed to obtain the control value of a pursuer through an error-feedback gain controller. ► Once conditions of system closed-loop stability have been satisfied, the optimal feedback gains and control values can be obtained through PSO. ► The performance of the proposed method is superior to that of its alternatives.