22,700 research outputs found
COOPERATIVE AND CONSENSUS-BASED CONTROL FOR A TEAM OF MULTI-AGENT SYSTEMS
Cooperative control has attracted a noticeable interest in control systems
community due to its numerous applications in areas such as formation flying
of unmanned aerial vehicles, cooperative attitude control of spacecraft, rendezvous
of mobile robots, unmanned underwater vehicles, traffic control, data
network congestion control and routing. Generally, in any cooperative control
of multi-agent systems one can find a set of locally sensed information, a
communication network with limited bandwidth, a decision making algorithm,
and a distributed computational capability. The ultimate goal of cooperative
systems is to achieve consensus or synchronization throughout the team members
while meeting all communication and computational constraints. The
consensus problem involves convergence of outputs or states of all agents to
a common value and it is more challenging when the agents are subjected to
disturbances, measurement noise, model uncertainties or they are faulty.
This dissertation deals with the above mentioned challenges and has developed
methods to design distributed cooperative control and fault recovery
strategies in multi-agent systems. Towards this end, we first proposed a
transformation for Linear Time Invariant (LTI) multi-agent systems that facilitates
a systematic control design procedure and make it possible to use
powerful Lyapunov stability analysis tool to guarantee its consensus achievement.
Moreover, Lyapunov stability analysis techniques for switched systems
are investigated and a novel method is introduced which is well suited for designing
consensus algorithms for switching topology multi-agent systems. This
method also makes it possible to deal with disturbances with limited root mean
square (RMS) intensities. In order to decrease controller design complexity, a
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method is presented which uses algebraic connectivity of the communication
network to decouple augmented dynamics of the team into lower dimensional
parts, which allows one to design the consensus algorithm based on the solution
to an algebraic Riccati equation with the same order as that of agent.
Although our proposed decoupling method is a powerful approach to reduce
the complexity of the controller design, it is possible to apply classical pole
placement methods to the transformed dynamics of the team to develop and
obtain controller gains.
The effects of actuator faults in consensus achievement of multi-agent systems
is investigated. We proposed a framework to quantitatively study actuator
loss-of-effectiveness effects in multi-agent systems. A fault index is defined
based on information on fault severities of agents and communication network
topology, and sufficient conditions for consensus achievement of the team are
derived. It is shown that the stability of the cooperative controller is linked to
the fault index. An optimization problem is formulated to minimize the team
fault index that leads to improvements in the performance of the team. A numerical
optimization algorithm is used to obtain the solutions to the optimal
problem and based on the solutions a fault recovery strategy is proposed for
both actuator saturation and loss-of-effectiveness fault types.
Finally, to make our proposed methodology more suitable for real life scenarios,
the consensus achievement of a multi-agent team in presence of measurement
noise and model uncertainties is investigated. Towards this end, first
a team of LTI agents with measurement noise is considered and an observer
based consensus algorithm is proposed and shown that the team can achieve
H∞ output consensus in presence of both bounded RMS disturbance input and
measurement noise. In the next step a multi-agent team with both linear and
Lipschitz nonlinearity uncertainties is studied and a cooperative control algorithm
is developed. An observer based approach is also developed to tackle
consensus achievement problem in presence of both measurement noise and
model uncertainties
Multi-Agent Cooperation for Particle Accelerator Control
We present practical investigations in a real industrial controls environment
for justifying theoretical DAI (Distributed Artificial Intelligence) results,
and we discuss theoretical aspects of practical investigations for
accelerator control and operation. A generalized hypothesis is introduced,
based on a unified view of control, monitoring, diagnosis, maintenance and
repair tasks leading to a general method of cooperation for expert systems
by exchanging hypotheses. This has been tested for task and result sharing
cooperation scenarios. Generalized hypotheses also allow us to treat the
repetitive diagnosis-recovery cycle as task sharing cooperation. Problems
with such a loop or even recursive calls between the different agents are
discussed
Fault-tolerant formation driving mechanism designed for heterogeneous MAVs-UGVs groups
A fault-tolerant method for stabilization and navigation of 3D heterogeneous formations is proposed in this paper. The presented Model Predictive Control (MPC) based approach enables to deploy compact formations of closely cooperating autonomous aerial and ground robots in surveillance scenarios without the necessity of a precise external localization. Instead, the proposed method relies on a top-view visual relative localization provided by the micro aerial vehicles flying above the ground robots and on a simple yet stable visual based navigation using images from an onboard monocular camera. The MPC based schema together with a fault detection and recovery mechanism provide a robust solution applicable in complex environments with static and dynamic obstacles. The core of the proposed leader-follower based formation driving method consists in a representation of the entire 3D formation as a convex hull projected along a desired path that has to be followed by the group. Such an approach provides non-collision solution and respects requirements of the direct visibility between the team members. The uninterrupted visibility is crucial for the employed top-view localization and therefore for the stabilization of the group. The proposed formation driving method and the fault recovery mechanisms are verified by simulations and hardware experiments presented in the paper
Distributed L1-state-and-fault estimation for Multi-agent systems
In this paper, we propose a distributed state-and-fault estimation scheme for
multi-agent systems. The proposed estimator is based on an -norm
optimization problem, which is inspired by sparse signal recovery in the field
of compressive sampling. Two theoretical results are given to analyze the
correctness of the proposed approach. First, we provide a necessary and
sufficient condition such that state and fault signals are correctly estimated.
The result presents a fundamental limitation of the algorithm, which shows how
many faulty nodes are allowed to ensure a correct estimation. Second, we
provide a sufficient condition for the estimation error of fault signals when
numerical errors of solving the optimization problem are present. An
illustrative example is given to validate the effectiveness of the proposed
approach
A design for an intelligent monitor and controller for space station electrical power using parallel distributed problem solving
The emphasis is on defining a set of communicating processes for intelligent spacecraft secondary power distribution and control. The computer hardware and software implementation platform for this work is that of the ADEPTS project at the Johnson Space Center (JSC). The electrical power system design which was used as the basis for this research is that of Space Station Freedom, although the functionality of the processes defined here generalize to any permanent manned space power control application. First, the Space Station Electrical Power Subsystem (EPS) hardware to be monitored is described, followed by a set of scenarios describing typical monitor and control activity. Then, the parallel distributed problem solving approach to knowledge engineering is introduced. There follows a two-step presentation of the intelligent software design for secondary power control. The first step decomposes the problem of monitoring and control into three primary functions. Each of the primary functions is described in detail. Suggestions for refinements and embelishments in design specifications are given
Making intelligent systems team players: Case studies and design issues. Volume 1: Human-computer interaction design
Initial results are reported from a multi-year, interdisciplinary effort to provide guidance and assistance for designers of intelligent systems and their user interfaces. The objective is to achieve more effective human-computer interaction (HCI) for systems with real time fault management capabilities. Intelligent fault management systems within the NASA were evaluated for insight into the design of systems with complex HCI. Preliminary results include: (1) a description of real time fault management in aerospace domains; (2) recommendations and examples for improving intelligent systems design and user interface design; (3) identification of issues requiring further research; and (4) recommendations for a development methodology integrating HCI design into intelligent system design
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