A multilayer control architecture for unmanned aerial vehicles

In the past several years there has been a lot of interest in the design of efficient autonomous intelligent controllers for unmanned aerial vehicles (UAV). This is a very challenging problem since future UAVs will be expected to complete autonomously a wide variety of complex missions, and achieve performance comparable to that of the manned vehicles. In this paper we describe and discuss the issues arising in autonomous intelligent control of UAVs. It is shown that the related problems can be effectively addressed within a framework of a four-layer hierarchical control architecture. The layers integrate the following autonomous functions: (1) fault-tolerant redundancy management; (2) trajectory generation; (3) path planning; and (4) decision making. The resulting multilayer control architecture is described in detail.

[1]  Kumpati S. Narendra,et al.  Adaptive control using multiple models , 1997, IEEE Trans. Autom. Control..

[2]  John Lygeros,et al.  Multiagent hybrid system design using game theory and optimal control , 1996, Proceedings of 35th IEEE Conference on Decision and Control.

[3]  John Lygeros,et al.  Hierarchical Hybrid Control: A Case Study , 1994, Hybrid Systems.

[4]  Sai-Ming Li,et al.  Semi-globally stable formation flight control design in three dimensions , 2001, Proceedings of the 40th IEEE Conference on Decision and Control (Cat. No.01CH37228).

[5]  Raman K. Mehra,et al.  A Hybrid Fault-Tolerant Scheme for Flight Control Applications* , 2001 .

[6]  R. Murray,et al.  Trajectory Planning of Differentially Flat Systems with Dynamics and Inequalities , 2000 .

[7]  Robert F. Stengel,et al.  Robust Nonlinear Control of a Hypersonic Aircraft , 1999 .

[8]  Irene M. Gregory,et al.  A New Approach to Aircraft Robust Performance Analysis , 1996 .

[9]  Kevin A. Wise,et al.  DIRECT ADAPTIVE RECONFIGURABLE FLIGHT CONTROL FOR A TAILLESS ADVANCED FIGHTER AIRCRAFT , 1999 .

[10]  R. K. Shyamasundar,et al.  Introduction to algorithms , 1996 .

[11]  Sunil K. Agrawal,et al.  Trajectory Planning of Differentially Flat Systems with Dynamics and Inequalities , 2000 .

[12]  Sai-Ming Li,et al.  Initial study of autonomous trajectory generation for unmanned aerial vehicles , 2001, Proceedings of the 40th IEEE Conference on Decision and Control (Cat. No.01CH37228).

[13]  O. Yakimenko Direct Method for Rapid Prototyping of Near-Optimal Aircraft Trajectories , 2000 .

[14]  Panos J. Antsaklis,et al.  Hybrid Systems II , 1994, Lecture Notes in Computer Science.

[15]  John L. Junkins,et al.  Inverse dynamics approach for real-time determination of feasible aircraft reference trajectories , 1999 .

[16]  Petros A. Ioannou,et al.  Accommodation of failures in the F-16 aircraft using adaptive control , 1991, IEEE Control Systems.

[17]  Seungjae Lee,et al.  Direct adaptive reconfigurable control of a tailless fighter aircraft , 1998 .

[18]  Jovan D. Boskovic,et al.  Intelligent Adaptive Control of a Tailless Advanced Fighter Aircraft Under Wing Damage , 2000 .

[19]  Jean-Claude Latombe,et al.  Robot motion planning , 1970, The Kluwer international series in engineering and computer science.

[20]  Sai-Ming Li,et al.  Evaluation of the properties of a multiple-model reconfigurable flight controller on a 6 DOF simulation , 2000 .

[21]  John Lygeros,et al.  A Game-Theoretic Approach to Hybrid System Design , 1996, Hybrid Systems.

[22]  Emilio Frazzoli,et al.  Real-Time Motion Planning for Agile Autonomous Vehicles , 2000 .

[23]  Jovan D. Boskovic,et al.  Stable multiple model adaptive flight control for accommodation of a large class of control effector failures , 1999, Proceedings of the 1999 American Control Conference (Cat. No. 99CH36251).

[24]  Meir Pachter,et al.  System identification for adaptive and reconfigurable control , 1995 .

[25]  Marc Bodson,et al.  Multivariable adaptive algorithms for reconfigurable flight control , 1997, IEEE Trans. Control. Syst. Technol..