Immune-system inspired approach for decentralized multi-agent control

This paper contains the first steps towards the development of a fully decentralized system framework. The novel approach that has been taken is derived from the inherent properties of the immune system. An assessment of the proposed control architecture has been performed by comparison with a more typical approach under a search and suppress kind of mission for an unmanned fleet

Fast non-monotone submodular maximisation subject to a matroid constraint

In this work we present the first practical . 1 e −ǫ . -approximation algorithm to maximise a general non-negative submodular function subject to a matroid constraint. Our algorithm is based on combining the decreasing-threshold procedure of Badanidiyuru and Vondrak (SODA 2014) with a smoother version of the measured continuous greedy algorithm of Feldman et al. (FOCS 2011). This enables us to obtain an algorithm that requires O( nr2 ǫ4 . ¯ d+ ¯ d ¯ d .2 log2 ( n ǫ )) value oracle calls, where n is the cardinality of the ground set, r is the matroid rank, and ¯ d, ¯ d ∈R+ are the absolute values of the minimum and maximum marginal values that the function f can take i.e.: − ¯ d ≤fS(i) ≤ ¯ d, for all i ∈E and S ⊆E, where E is the ground set. The additional value oracle calls with respect to the work of Badanidiyuru and Vondrak come from the greater spread in the sampling of the multilinear extension that the possibility of negative marginal values introduce

Integrated reconfigurable control and guidance based on evaluation of degraded performance

The present paper is focused on analysing an integrated reconfigurable control and guidance approach for recovering a small fixed-wing UAV from different actuator faults, which cover locked in place (stuck) and loss of effectiveness. The model of the UAV Aerosonde is used to develop a reconfigurable control system based on the control allocation technique for a variety of faults, such as locked-in-place control surfaces. It is shown through simulation that the developed technique is successful to recover the aircraft from various faults but cannot guarantee success on the planned mission. For mission scenarios where performance degradation is such that the prescribed trajectory cannot be achieved, a reconfigurable guidance system is developed, which is capable of adapting parameters such as the minimum turning radius and the look-ahead distance for obstacle avoidance, to allow the vehicle to dynamically generate a path which guides the aircraft around the no-fly zones taking into account the post-fault reduced performance. Path following is performed by means of a non-linear lateral guidance law and a collision avoidance algorithm is implemented as well. Finally, the integration of control reconfiguration and guidance adaptation is carried out to maximise probabilities of post-failure success in the mission. A methodology is developed, using an error based control allocation parameter, as a measure of performance degradation, which links both reconfiguration and guidance systems. The developed method, although approximate, is proven to be an efficient way of allocating the required degree of reconfiguration in guidance commands when an accurate prediction of the actual performance is not available

Trajectory optimization for target localisation with bearing-only measurement

This paper considers the problem of twodimensional (2D) constrained trajectory optimisation of a pointmass aerial robot for constant-manoeuvring target localisation using bearing-only measurement. A performance metric that can be utilised in trajectory optimisation to maximise target observability is proposed first based on geometric conditions. One-step optimal manoeuvre that maximises the observability criterion is then derived analytically for moving targets. The heading angle constraint is also incorporated in the proposed optimal manoeuvre derivation to support practical application. Numerical simulations with some comparisons are presented to validate the analytical findings

Evolutionary game theory based multi-objective optimization for control allocation of over-actuated system

This research presents multi-objective optimization for control allocation problem based on the Evolutionary Game Theory to solve distribution of redundant control input on the over actuated system in real-time. Optimizing the conflicting objectives, an evolutionary game theory based approach with replicator dynamics is used to find the optimal weighting using the weighted sum method. The main idea of this method is that the best strategy or dominant solution can be selected as a solution that survives among other non-dominant solutions. The Evolutionary Game Theory considers strategies as a player and investigates how these strategies can survive using replicator dynamics with payoff matrix. The numerical simulation results show the optimal weightings selected by Evolutionary Game and how the payoff has been changed in replicator dynamics

Local information-based control for probabilistic swarm distribution guidance

This paper proposes a closed-loop decentralised framework for swarm distribution guidance, which disperses homogeneous agents over bins to achieve a desired density distribution by using feedback gains from the current swarm status. The key difference from existing works is that the proposed framework utilises only local information, not global information ,to generate the feedback gains for stochastic policies. Dependency on local information entails various advantages including reduced inter-agent communication, a shorter timescale for obtaining new information, asynchronous implementation, and deployability without a priori mission knowledge. Our theoretical analysis shows that, even utilising only local information, the proposed framework guarantees convergence of the agents to the desired status, while maintaining the advantages of existing closed-loop approaches. Also, the analysis explicitly provides the design requirements to achieve all the advantages of the proposed framework. We provide implementation examples and report the results of empirical tests. The test results confirm the effectiveness of the proposed framework and also validate the robustness enhancement in a scenario of partial disconnection of the communication network

Generalized formulation of linear nonquadratic weighted optimal error shaping guidance laws

This study presents a novel extension to the theory of optimal guidance laws represented by the nontraditional class of performance indices: nonquadratic-type signal Lp" role="presentation">Lp norm for the input weighted by an arbitrary positive function. Various missile guidance problems are generally formulated into a scalar terminal control problem based on the understanding of the predictor–corrector nature. Then, a new approach to derive the optimal feedback law, minimizing the nonquadratic performance index, is proposed by using the Hölderian inequality. The proposed extension allows a more general family of formulations for the design of closed-form feedback solutions to various guidance problems to be treated in a unified framework. The equivalence between the proposed approach and other design methodologies is investigated. In general, the type of input norm mainly determines the variability of input during the engagement while trading off against the rate of error convergence. The analytic solution derived in this study is verified by comparison with the solution from numerical optimization, and the effect of the exponent p" role="presentation">p in the performance index on the trajectory and command is demonstrated by numerical simulations

Model identification adaptive control - implementation case studies for a high manoeuvrability aircraft

With the proliferation of modular Unmanned Aerial Vehicles (UAVs) cheap and scalable control methods are needed to ensure operability. Using adaptive control it seems that these requirements could be met. In this paper applicability of parameter adaptation and control methods are demonstrated within the model identification adaptive control framework, implementing several methods and evaluating their performance. As a plant a non-linear simulation model of an F-16 aircraft is used