Cooperative planning for coupled multi-agent systems under timed temporal specifications

This paper studies the synthesis of controllers for cyber-physical systems (CPSs) that are required to carry out complex tasks that are time-sensitive, in the presence of an adversary. The task is specified as a formula in metric interval temporal logic (MITL). The adversary is assumed to have the ability to tamper with the control input to the CPS and also manipulate timing information perceived by the CPS. In order to model the interaction between the CPS and the adversary, and also the effect of these two classes of attacks, we define an entity called a durational stochastic game (DSG). DSGs probabilistically capture transitions between states in the environment, and also the time taken for these transitions. With the policy of the defender represented as a finite state controller (FSC), we present a value-iteration based algorithm that computes an FSC that maximizes the probability of satisfying the MITL specification under the two classes of attacks. A numerical case-study on a signalized traffic network is presented to illustrate our results.

It is well known that (timed) ω-regular properties such as 'p holds at every even position' and 'p occurs at least three times within the next 10 time units' cannot be expressed in Metric Interval Temporal Logic (MITL) and Event Clock Logic (ECL). A standard remedy to this deficiency is to extend these with modalities defined in terms of automata. In this paper, we show that the logics EMITL0, ∞ (adding non-deterministic finite automata modalities into the fragment of MITL with only lower- and upper-bound constraints) and EECL (adding automata modalities into ECL) are already as expressive as EMITL (full MITL with automata modalities). In particular, the satisfiability and model-checking problems for EMITL0, ∞ and EECL are PSPACE-complete, whereas the same problems for EMITL are EXPSPACE-complete. We also provide a simple translation from EMITL0, ∞ to diagonal-free timed automata, which enables practical satisfiability and model checking based on off-the-shelf tools.

In this paper the problem of cooperative task planning of multi-agent systems when timed constraints are imposed to the system is investigated. We consider timed constraints given by Metric Interval Temporal Logic (MITL). We propose a method for automatic control synthesis in a two-stage systematic procedure. With this method we guarantee that all the agents satisfy their own individual task specifications as well as that the team satisfies a team global task specification.

We present a verification framework exploiting τ-simulations as a way to preserve local linear properties checked on the components of real-time systems. Therefore, we consider a component-based modeling of real-time systems. Their properties are expressed in a timed logic, MITL (Metric Interval Temporal Logic).For component-based models, traditional verification techniques are generally applied to the complete composed model, even if some properties only concern some components of the system, if not only one. We show that it is possible to check such local linear properties (safety as well as liveness) on the components they concern, and then to ensure their preservation using τ-simulation relations. We show the interest of the method by applying it on two real-time systems examples and by comparing the results with traditional verification techniques.

We describe Breach, a Matlab/C++ toolbox providing a coherent set of simulation-based techniques aimed at the analysis of deterministic models of hybrid dynamical systems. The primary feature of Breach is to facilitate the computation and the property investigation of large sets of trajectories. It relies on an efficient numerical solver of ordinary differential equations that can also provide information about sensitivity with respect to parameters variation. The latter is used to perform approximate reachability analysis and parameter synthesis. A major novel feature is the robust monitoring of metric interval temporal logic (MITL) formulas. The application domain of Breach ranges from embedded systems design to the analysis of complex non-linear models from systems biology.

In this paper, a simplified reinforcement learning (RL) of identifier-actor-critic architecture is proposed to solve the formation problem of multiagent state-delay system. The dynamics of multi-agent systems includes the uncertainties and state delay, which is more practical in applications. In the multiagent system formation control, the system uncertainties are counteracted through the fuzzy logic system; the state delay is offset by applying a Lyapunov-Krasovskii functional. The updating laws of RL are derived from a simple equation, which is equivalent to the gradient of the HJB equation. Finally, a simulation example is given to demonstrate the satisfactory performance of the proposed method.

Failures are unavoidable in many circumstances. For example, an agent may fail at some point to perform a task in a dynamic environment. Robust systems typically have mechanisms to handle such failures. Temporal logic is a widely used representation language for reasoning about the behaviour of systems, although dealing with failures is not part of the language. In this paper, it is investigated how interval temporal logic can be extended with an operator describing failure. This logic has a close relationship to exception handling mechanisms in programming languages, which provides an elegant mechanism for modelling and handling failures. The approach is motivated from the context of specification of systems that have to operate in highly dynamic environments. A case study of the formal modelling and verification of the treatment of diabetes mellitus type 2 illustrates the practical usefulness of the approach.

During requirement specification process of software development activities, many existing systems or business process requirements have been captured using natural language or specialized tools such as UML. However, the capturing of informal requirements into formalized properties has not been taken into attention by software developers due to time and budget constraints. It is critical for the informally captured requirements to be formally specified in order to perform system verification. Formal verification checks whether a system model meets the formal specifications while validation checks whether the developed system fulfills its intended purpose. Therefore, in this paper, we present our studies of formal verification of multi agent system using model checking approach. We have utilized model checking tool in order to execute the formal verification procedures based on a particular basic theory to verify certain kind of properties of requirement specifications. We show an example of how model checking tool could support the verification of Universiti Teknologi Malaysia (UTM) multi agent online application system and conclude that the propose model checking approach will benefit multi agent system.

This paper addresses the challenging problem of decentralized adaptive control for a class of coupled hidden leader-follower multi-agent systems, in which each agent is described by a nonlinearly parameterized uncertain model in discrete time and can interact with its neighbors via its available information on its neighbors. One of the agents is a leader, who knows the desired reference trajectory, while other agents have no access to the desired reference signal or are unaware of existence of the leader. In order to tackle unknown internal parameters and unknown high-frequency gains, a projection-type parameter estimation algorithm is proposed. Based on the certainty equivalence principle and neighborhood history information, the decentralized adaptive control is designed, under which, the boundedness of identification error is guaranteed with the help of the Lyapunov theory. Under some conditions, the multi-agent system eventually achieves strong synchronization in the presence of strong couplings. Finally, a simulation example is given to support the results of the proposed scheme.

In this paper, a method to synthesize controllers using finite time convergence control barrier functions guided by linear temporal logic specifications for continuous time multi-agent dynamical systems is proposed. Finite time convergence to a desired set in the state space is guaranteed under the existence of a suitable finite time convergence control barrier function. In addition, these barrier functions also guarantee forward invariance once the system converges to the desired set. This allows us to formulate a theoretical framework which synthesizes controllers for the multi-agent system. These properties also enable us to solve the reachability problem in continuous time by formulating a theorem on the composition of multiple finite time convergence control barrier functions. This approach is more flexible than existing methods and also allows for a greater set of feasible control laws. Linear temporal logic is used to specify complex task specifications that need to be satisfied by the multi-agent system. With this solution methodology, a control law is synthesized that satisfies the given temporal logic task specification. Robotic experiments are provided which were performed on the Robotarium multi-robot testbed at Georgia Tech.

This paper proposes a rule language for defining social expectations based on a metric interval temporal logic with past and future modalities and a current-time binding operator. An algorithm for run-time monitoring compliance of rules in this language based on formula progression is also presented.

SummaryIn this paper, a bipartite consensus problem is considered for a high‐order multiagent system with cooperative‐competitive interactions and unknown time‐varying disturbances. A signed graph is used to describe the interaction network associated with the multiagent system. The unknown disturbances are expressed by linearly parameterized models, and distributed adaptive laws are designed to estimate the unknown parameters in the models. For the case that there is no exogenous reference system, a fully distributed adaptive control law is proposed to ensure that all the agents reach a bipartite consensus. For the other case that there exists an exogenous reference system, another fully distributed adaptive control law is also developed to ensure that all the agents achieve bipartite consensus on the state of the exogenous system. The stability of the closed‐loop multiagent systems with the 2 proposed adaptive control laws are analyzed under an assumption that the interaction network is structurally balanced. Moreover, the convergence of the parameter estimation errors is guaranteed with a persistent excitation condition. Finally, simulation examples are provided to demonstrate the effectiveness of the proposed adaptive bipartite consensus control laws for the concerned multiagent system.

This paper investigates the consensus problem for discrete linear multi-agent systems (MASs) in the case of Markovian packet dropouts. The agent subsystems are connected by lossy channels, which can be described by Markov process. The relationship of agent dynamics, communication network, and packet losses rate is studied, and based on which the MASs can achieve consensus by a designed distributed controller. Specifically, based on the stability of a transformed system state function under the identical packet looses, we first derive the sufficient condition of consensus for discrete-time MASs, and meanwhile design the control gain. Then, we also discuss the sufficient condition of consensus for the MASs under nonidentical packet losses. At last, the availability of the proposed results is illustrated through simulation examples.

Self-organisation is increasingly being regarded as an effective approach to tackle modern systems complexity. The self-organisation approach allows the development of systems exhibiting complex dynamics and adapting to environmental perturbations without requiring a complete knowledge of the future surrounding conditions. However, the development of self-organising systems (SOS) is driven by different principles with respect to traditional software engineering. For instance, engineers typically design systems combining smaller elements where the composition rules depend on the reference paradigm, but typically produce predictable results. Conversely, SOS display non-linear dynamics, which can hardly be captured by deterministic models, and, although robust with respect to external perturbations, are quite sensitive to changes on inner working parameters. In this thesis, we describe methodological aspects concerning the early-design stage of SOS built relying on the Multiagent paradigm: in particular, we refer to the A&A metamodel, where MAS are composed by agents and artefacts, i.e. environmental resources. Then, we describe an architectural pattern that has been extracted from a recurrent solution in designing self-organising systems: this pattern is based on a MAS environment formed by artefacts, modelling non-proactive resources, and environmental agents acting on artefacts so as to enable self-organising mechanisms. In this context, we propose a scientific approach for the early design stage of the engineering of self-organising systems: the process is an iterative one and each cycle is articulated in four stages, modelling, simulation, formal verification, and tuning. During the modelling phase we mainly rely on the existence of a self-organising strategy observed in Nature and, hopefully encoded as a design pattern. Simulations of an abstract system model are used to drive design choices until the required quality properties are obtained, thus providing guarantees that the subsequent design steps would lead to a correct implementation. However, system analysis exclusively based on simulation results does not provide sound guarantees for the engineering of complex systems: to this purpose, we envision the application of formal verification techniques, specifically model checking, in order to exactly characterise the system behaviours. During the tuning stage parameters are tweaked in order to meet the target global dynamics and feasibility constraints. In order to evaluate the methodology, we analysed several systems: in this thesis, we only describe three of them, i.e. the most representative ones for each of the three years of PhD course. We analyse each case study using the presented method, and describe the exploited formal tools and techniques.

This note addresses the adaptive consensus problem of first-order and second-order linearly parameterized multi-agent systems with unknown identical control directions. First, we propose a new Nussbaum-type function based on which a key lemma is established. The lemma plays an important role in analyzing the consensus of the closed-loop multi-agent systems. Second, the Nussbaum-type function is used to design adaptive control laws for first-order and second-order linearly parameterized multi-agent systems so that each agent seeks for the unknown control direction adaptively and cooperatively. Then, under the assumption that the interconnection topology is undirected and connected, it is proved that the first-order and second-order multi-agent systems can achieve consensus by choosing proper design parameters. Two simulation examples are given to illustrate the effectiveness of the proposed control laws.