169 research outputs found
Reconfigurable cooperative control of networked lagrangian systems under actuator saturation constraints
In this paper, a reconfigurable control strategy is proposed for state synchronization and tracking control of
networked (electro-) mechanical Euler-Lagrange (EL) systems that are subject to input saturation constraints that
may arise due to actuator faults or failures. The reconfigurable controller consists of three main parts. The first part, known as the nominal controller, is a distributed controller that is employed to guarantee global stability of the multiagent networked EL system provided that certain mild connectivity conditions are satisfied in absence or presence of actuator saturation constraints. The second part, known as the reconfigured controller, is a constrained nonlinear smooth distributed controller that has a different structure and gains from the nominal controller. This controller can preserve the overall control objectives in presence of actuator faults and actuator saturation constraints. The third part is a switching strategy between the nominal and the reconfigured controllers. Global stability as well as asymptotic
convergence of the synchronization and the tracking errors to origin for switchings under certain conditions between
the nominal and the reconfigured controllers with non-vanishing dwell-times for a fixed network topology are shown to be guaranteed. Simulation results are reported to demonstrate and validate the merits of the proposed controllers
Comprehensive review on controller for leader-follower robotic system
985-1007This paper presents a comprehensive review of the leader-follower robotics system. The aim of this paper is to find and elaborate on the current trends in the swarm robotic system, leader-follower, and multi-agent system. Another part of this review will focus on finding the trend of controller utilized by previous researchers in the leader-follower system. The controller that is commonly applied by the researchers is mostly adaptive and non-linear controllers. The paper also explores the subject of study or system used during the research which normally employs multi-robot, multi-agent, space flying, reconfigurable system, multi-legs system or unmanned system. Another aspect of this paper concentrates on the topology employed by the researchers when they conducted simulation or experimental studies
Event-triggered Synchronization of Multi-agent Systems with Partial Input Saturation
This paper is concerned with the distributed event/self-triggered synchronization problem for general linear multi-agent systems with partial input saturation. Both the event-based and self-triggered laws are designed using the local sampled, possibly saturated, state, which ensures the bounded synchronization of the multi-agent systems, and exclusion of the Zeno-behavior. The continuous communication between agents is avoided under these triggering protocols. Different from the existing related works, we show the fully distributed design for multi-agent systems, where the synchronization criteria, the designed input laws, and the proposed triggering protocols do not depend on any global information of the communication topology. In addition, the computation load of multi-agent systems is reduced significantly
A Survey on Aerial Swarm Robotics
The use of aerial swarms to solve real-world problems has been increasing steadily, accompanied by falling prices and improving performance of communication, sensing, and processing hardware. The commoditization of hardware has reduced unit costs, thereby lowering the barriers to entry to the field of aerial swarm robotics. A key enabling technology for swarms is the family of algorithms that allow the individual members of the swarm to communicate and allocate tasks amongst themselves, plan their trajectories, and coordinate their flight in such a way that the overall objectives of the swarm are achieved efficiently. These algorithms, often organized in a hierarchical fashion, endow the swarm with autonomy at every level, and the role of a human operator can be reduced, in principle, to interactions at a higher level without direct intervention. This technology depends on the clever and innovative application of theoretical tools from control and estimation. This paper reviews the state of the art of these theoretical tools, specifically focusing on how they have been developed for, and applied to, aerial swarms. Aerial swarms differ from swarms of ground-based vehicles in two respects: they operate in a three-dimensional space and the dynamics of individual vehicles adds an extra layer of complexity. We review dynamic modeling and conditions for stability and controllability that are essential in order to achieve cooperative flight and distributed sensing. The main sections of this paper focus on major results covering trajectory generation, task allocation, adversarial control, distributed sensing, monitoring, and mapping. Wherever possible, we indicate how the physics and subsystem technologies of aerial robots are brought to bear on these individual areas
Cooperative Control Reconfiguration in Networked Multi-Agent Systems
Development of a network of autonomous cooperating vehicles has attracted significant
attention during the past few years due to its broad range of applications in areas
such as autonomous underwater vehicles for exploring deep sea oceans, satellite formations
for space missions, and mobile robots in industrial sites where human involvement
is impossible or restricted, to name a few. Motivated by the stringent specifications
and requirements for depth, speed, position or attitude of the team and the possibility
of having unexpected actuators and sensors faults in missions for these vehicles have
led to the proposed research in this thesis on cooperative fault-tolerant control design of
autonomous networked vehicles.
First, a multi-agent system under a fixed and undirected network topology and subject
to actuator faults is studied. A reconfigurable control law is proposed and the so-called
distributed Hamilton-Jacobi-Bellman equations for the faulty agents are derived. Then,
the reconfigured controller gains are designed by solving these equations subject to the
faulty agent dynamics as well as the network structural constraints to ensure that the
agents can reach a consensus even in presence of a fault while simultaneously the team
performance index is minimized.
Next, a multi-agent network subject to simultaneous as well as subsequent actuator
faults and under directed fixed topology and subject to bounded energy disturbances is considered. An H∞ performance fault recovery control strategy is proposed that guarantees:
the state consensus errors remain bounded, the output of the faulty system behaves
exactly the same as that of the healthy system, and the specified H∞ performance bound
is guaranteed to be minimized. Towards this end, the reconfigured control law gains
are selected first by employing a geometric control approach where a set of controllers
guarantees that the output of the faulty agent imitates that of the healthy agent and the
consensus achievement objectives are satisfied. Then, the remaining degrees of freedom
in the selection of the control law gains are used to minimize the bound on a specified
H∞ performance index.
Then, control reconfiguration problem in a team subject to directed switching topology
networks as well as actuator faults and their severity estimation uncertainties is considered.
The consensus achievement of the faulty network is transformed into two stability
problems, in which one can be solved offline while the other should be solved online
and by utilizing information that each agent has received from the fault detection and
identification module. Using quadratic and convex hull Lyapunov functions the control
gains are designed and selected such that the team consensus achievement is guaranteed
while the upper bound of the team cost performance index is minimized.
Finally, a team of non-identical agents subject to actuator faults is considered. A
distributed output feedback control strategy is proposed which guarantees that agents
outputs’ follow the outputs of the exo-system and the agents states remains stable even
when agents are subject to different actuator faults
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