Time varying formation control problem for a group of quadrotor unmanned aerial vehicles (UAVs) under Markovian switching topologies is investigated through a modified dynamic event-triggered control protocol. The formation shape is specified by a time varying vector, which prescribes the relative positions and bearings among the whole agents. Instead of the general stochastic topology, the graph is governed by a set of Markov chains to the edges, which can recover the traditional Markovian switching topologies in line with the practical communication network. The stability proof for the state space origin of the overall closed-loop system is derived from the singular perturbation method and Lyapunov stability theory. An event-triggered formation control protocol in terms of a dynamically varying threshold parameter is delicately carried out, while acquiring satisfactory resource efficiency, and Zeno behavior of triggering time sequences is excluded. Finally, simulations on six quadrotor UAVs are given to verify the effectiveness of the theoretical results.
Finite time control problem is investigated for a class of underactuated systems with uncertainties and external disturbances. For the sake of expanding control region furthest within a bound input, finite time extended state observer (FTESO) and a novel adaptive terminal sliding mode (ATSM) controller are applied to improve the stability performance of system. Compared to the general extended state observer (ESO), FTESO makes use of fractional powers to reduce the estimation errors to zero in finite time. The coordinate transformation is made for more degrees of design freedom. Rigorous analysis of finite time convergence results has been performed through Lyapunov theory and sufficient conditions are provided for the observer/controller-design. Finally, simulation results on the Rotating Inverted Pendulum are given to demonstrate the effectiveness of the proposed controller and observer.
This paper presents a distributed consensus algorithm that employs event-triggered communication for multiple underactuated systems under Markovian switching topologies. Instead of the general stochastic topology, the graph of the entire system is governed by a set of Markov chains to the edges, which can recover the general Markovian switching topologies in line with the practical communication network. By utilizing integral sliding mode control strategy, rigorous analysis of the asymptotic convergence results has been performed through graph theory and Lyapunov stability theory. An event-triggered communication law is provided for each agent and Zeno behavior of triggering time sequences is excluded. It will yield to the very first application of the multiple underactuated systems, in which the system states could be enforced to track the leader. Finally, the illustrative simulations on six underactuated two-link manipulators are given to demonstrate the effectiveness of theoretical results.
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