Cooperative Adaptive Control for Systems with Second-Order Nonlinear Dynamics
In Chap. 8, we designed cooperative adaptive controllers for multi-agent systems having first-order nonlinear dynamics. In this chapter, we study adaptive control for cooperative multi-agent systems having second-order nonidentical nonlinear dynamics. The study of second-order and higher-order consensus is required to implement synchronization in most real-world applications such as formation control and coordination among unmanned aerial vehicles (UAVs), where both position and velocity must be controlled. Note that Lagrangian motion dynamics and robotic systems can be written in the form of second-order systems. Moreover, second-order integrator consensus design (as opposed to first-order integrator node dynamics) involves more details about the interaction between the system dynamics and control design problem and the graph structure as reflected in the Laplacian matrix. As such, second-order consensus is interesting because there one must confront more directly the interface between control systems and communication graph structure.
- 4.Ge SS, Hang CC, Zhang T (1998) Stable Adaptive Neural Network Control. Springer, BerlinGoogle Scholar
- 6.Khalil HK (2002) Nonlinear Systems, 3rd edn. Prentice Hall, Upper Saddle River, NJGoogle Scholar
- 9.Lewis FL, Jagannathan S, Yesildirek A (1999) Neural Network Control of Robot Manipulators and Nonlinear Systems. Taylor and Francis, LondonGoogle Scholar
- 10.Qu Z (2009) Cooperative Control of Dynamical Systems: Applications to Autonomous Vehicles. Springer-Verlag, New YorkGoogle Scholar
- 11.Stone MH (1948) The generalized weierstrass approximation theorem. Math Mag 21(4/5):167–184/237–254Google Scholar