In this paper, a distributed diffusion unscented Kalman filtering algorithm based on covariance intersection strategy (DDUKF-CI) is proposed for target tracking with intermittent measurements. By virtue of the pseudo measurement matrix, the standard unscented Kalman filtering (UKF) with intermittent observations is transformed to the information form for the diffusion algorithm to fuse intermediate

This paper considers observer–predictor feedback for delay compensation in consensus control under undirected switching graphs. Each node involved in the network is described by a linear system with an actuator delay of uncertain length, and the connection graph is allowed to be unknown and switch arbitrarily. An observer is proposed to estimate the disagreement state using locally available information

Visual Simultaneous Localisation and Mapping (VSLAM) is a well-known problem in robotics with a large range of applications. This paper presents a novel approach to VSLAM by lifting the observer design to a novel Lie group VSLAMn(3) on which the system output is equivariant. The perspective gained from this analysis facilitates the design of a non-linear observer with almost semi-globally asymptotically

This paper introduces a framework for solving time-autonomous nonlinear infinite horizon optimal control problems, under the assumption that all minimizers satisfy Pontryagin’s necessary optimality conditions. In detail, we use methods from the field of symplectic geometry to analyze the eigenvalues of a Koopman operator that lifts Pontryagin’s differential equation into a suitably defined infinite

A new discrete reaching condition of quasi-sliding mode (QSM) and generalized discrete reaching law with different convergence rates are proposed in this paper. The superiority is that they can ensure the faster convergence rate and shorten the reaching phase of the sliding variable by adjusting a positive integer value. The relationship between the generalized discrete reaching law parameters and

This paper proposes a novel maneuvering technique for the complex-Laplacian-based formation control. We show how to modify the original weights that build the Laplacian such that a designed steady-state motion of the desired shape emerges from the local interactions among the agents. These collective motions can be exploited to solve problems such as the shaped consensus (the rendezvous with a particular

Asymptotic output stability (AOS) is an interesting property when addressing control applications in which not all state variables are requested to converge to the origin. AOS is often established by invoking classical tools such as Barbashin–Krasovskii–LaSalle’s invariance principle or Barbălat’s lemma. Nevertheless, none of these tools allow to predict whether the output convergence is uniform on

As a natural extension of the Kalman filter to systems subject to arbitrary unknown inputs, the Kitanidis filter has been designed by one-step minimization of the trace of the state estimation error covariance matrix. In this technical communiqué, it is shown that the Kitanidis filter is also optimal for the whole gain sequence in the sense of matrix positive definiteness, which notably implies that

We provide a set of counterexamples for the monotonicity of the Newton–Hewer method (Hewer, 1971) for solving the discrete-time algebraic Riccati equation in dynamic settings, drawing a contrast with the Riccati difference equation (Caines and Mayne, 1970).

In this paper, a recursive t-distribution noise model based maximum likelihood estimation algorithm for discrete-time dynamic state estimation is proposed. The proposed estimator is robust to outliers because the “thick tail” of the t-distribution reduces the effect of large errors in the likelihood function. A computationally efficient recursive algorithm is derived using the influence function. As

In this paper, a distributed set-membership estimator for linear full-coupled systems affected by bounded disturbances is presented. The estimator uses a multi-hop staircase decomposition, capturing the locally unobservable subspaces in a cascaded fashion with the information incoming from other agents involved in the network. Each agent has to find different sets for each subspace, that are mathematically

The paper focuses on a generic optimal control problem (OCP) deriving from the competition between two microbial populations in continuous cultures. The competition for nutrients is reduced to a two-dimensional dynamical nonlinear-system that can be derived from classical quota models. We investigate an OCP that achieves species separation over a fixed time-window, suitable for a large class of empirical

This paper studies edge-based event-triggered strategies for the average consensus problem in multi-agent systems. To this end, a distributed event-triggered algorithm is presented based on edge information rather than neighbor information, where positive minimum inter-event times are guaranteed between all communication links in the network. Moreover, the triggering mechanism is constructed in a fully

In this paper a constructive method to determine and compute probabilistic reachable and invariant sets for linear discrete-time systems, excited by a stochastic disturbance, is presented. The samples of the disturbance signal are not assumed to be uncorrelated, only bounds on the mean and the covariance matrices are supposed to be known. This allows to consider nonlinear stochastic systems approximations

In this paper, we present a projection-based interpolation framework for structure-preserving model order reduction of parametric bilinear dynamical systems. We introduce a general setting, covering a broad variety of different structures for parametric bilinear systems, and then provide conditions on projection spaces for the interpolation of structured subsystem transfer functions such that the system

Hybrid unmanned aerial vehicles (UAVs) provide an interesting combination of the vertical takeoff and landing (VTOL) capabilities of rotary-wing (RW) and of the efficient forward flight of fixed-wing (FW) vehicles. The employed controllers must be able to handle the highly nonlinear dynamics and changing control authorities resulting from this combination, especially during the transition between the

This paper studies the asymptotic behavior of switched linear systems, beyond classical stability. We focus on systems having a low-dimensional asymptotic behavior, that is, systems whose trajectories converge to a common time-varying low-dimensional subspace. We introduce the concept of path-complete p-dominance for switched linear systems, which generalizes the approach of quadratic Lyapunov theory

This paper presents a subspace-based frequency identification method with passivity enforcement via Linear-Matrix Inequalities to achieve a globally optimal and passive solution. These inequalities are formulated and solved as a convex optimization problem using a state-of-the-art numerical solver. We also apply a weighting methodology to the LMI formulation to enhance the approximation between the

In this paper, nonsmooth aggregative games are investigated, where the nondifferentiable cost function of every player depends on its own decision as well as the aggregate of the decisions of all players. Moreover, in the problem, the local constraints of players are general and heterogeneous convex sets, and the decisions of players are coupled by linear constraints. For purpose of distributed seeking

This paper is concerned with the target tracking problem for a class of wireless localization systems with unknown but bounded noises. Since the energy supply of wireless sensor nodes is rather scarce, a component-based event-triggered mechanism is utilized to reduce the signal transmission frequency by discarding the unnecessary information transmissions. The objective of the addressed problem is

In this paper we address the edge-agreement problem with preserved connectivity for networks of first and second-order systems under proximity constraints and interconnected over a class of directed graphs. We provide a strict Lyapunov function that leads to establishing uniform asymptotic stability of the consensus manifold with guaranteed connectivity preservation. Furthermore, robustness of the

The note considers optimal and model predictive controls for linear systems with strictly convex quadratic stage and terminal cost functions, and under closed polyhedral stage constraints, finitely many open spherical exclusion stage constraints, and closed polyhedral terminal constraints. The computational complexity of exact nonconvex optimal and model predictive controls is alleviated through the

This paper is concerned with the linear–quadratic optimal control problem for networked systems simultaneously with input delay and Markovian packet losses under hold-input compensation strategy, which is different from the literature. Necessary and sufficient conditions for the solvability of optimal control problem over a finite horizon are given by coupled difference Riccati-type equations. Moreover

This paper considers the global finite-time attitude synchronization and coordinated tracking problems of multiple rigid bodies without angular velocity measurements. First, for the attitude synchronization problem, by combining the hybrid technique and homogeneous theory, a new velocity-free attitude synchronization algorithm is constructed to prevent the unwinding problem and achieve finite-time

This paper studies exponential stability and stabilization of linear time-varying systems without assuming that the coefficient matrix is bounded, which is generally necessary in the existing literature. First, by introducing the notions of uniformly exponentially stable and uniformly exponentially expanding functions, some Lyapunov differential inequalities based characterizations for exponential

Extended state observer (ESO) is a class of high-gain observers and a powerful tool for output feedback control of uncertain nonlinear systems. In this paper, we propose a new ESO design technique which is based on cascading a series of first-order ESOs. Benefited from the cascade design, saturations can be inserted into the observer internal variables to limit the maximal implemented gain. The convergence

In this paper, a general theoretical framework is established for the robust fusion filtering problem of discrete time-varying stochastic multisensor systems under energy harvesting constraints. The energy harvesting technology is utilized to provide the needed energy for persistently maintaining the operation of the multisensor systems. The energy level at the energy harvester is characterized by

System identification for multibody mechanical systems such as robots and vehicles is typically formulated as a parameter optimization problem, in which the model parameters are chosen to minimize the difference between measured and predicted trajectories of the system. The problem is made difficult by the large number of parameters of different scales and physical units, and also noisy and incomplete

The isoline tracking of this work is concerned with the control design for a sensing vehicle to track a desired isoline of an unknown scalar field. To this end, we propose a simple proportional integral (PI)-like controller for a Dubins vehicle in the GPS-denied environment. Inspired by the sliding mode control method, our key idea lies in the design of an error term in the standard PI controller.

In this article, we deal with the active diagnosis problem in labeled Petri nets by developing a supervisor for a plant such that the closed-loop system is diagnosable. Since control actions may introduce deadlocks even if an original plant is deadlock-free, we first generalize the classical notion of diagnosability in labeled Petri nets to the nets that may contain potential deadlocks. To avoid enumerating

This article addresses the problem of average consensus in a multi-agent system when the desired consensus quantity is a time varying signal. Although this problem has been addressed in existing literature by linear schemes, only bounded steady-state errors have been achieved. Other approaches have used first order sliding modes to achieve zero steady-state error, but suffer from the chattering effect

Cyber–physical systems usually have complex dynamics and are required to fulfill complex tasks. In recent years, formal methods from Computer Science have been used by control theorists for both describing the required tasks and ensuring that they are fulfilled by the systems. The crucial drawback of formal methods is that a complete model of the system often needs to be available. The main goal of

This paper investigates positivity and asymptotic stability for a class of timescale-type differential–difference equation with time-varying delay. When the delay is bounded, a necessary and sufficient condition is obtained based on timescale theory and comparison principle. While for the case of unbounded delay, a sufficient criterion is acquired. Further, for the corresponding continuous-time system

In this paper, the distributed state and fault estimation problem is discussed for a class of nonlinear time-varying systems with probabilistic quantizations and dynamic event-triggered mechanisms. To reduce resource consumption, a dynamic event-triggered strategy is exploited to schedule the data communication among sensor nodes. In addition, the measurement signals are quantized and then transmitted

This paper analyzes the robust feedback stability of a single-input-single-output stable linear time-invariant (LTI) system against three different classes of nonlinear systems using the Zames–Falb multipliers. The contribution is threefold. Firstly, we identify a class of uncertain systems over which the robust feedback stability is equivalent to the existence of an appropriate Zames–Falb multiplier

In this paper, we consider a multi-agent resilient consensus problem, where some of the nodes may behave maliciously. The approach is to equip all nodes with a scheme to detect neighboring nodes when they behave in an abnormal fashion. To this end, the nodes exchange not only their own states but also information regarding their neighbor nodes. Such two-hop communication has long been studied in fault-tolerant

A new data-driven tuning method of a linearly parametrized controller is proposed for stable multi-input multi-output plants. A criterion that evaluates the difference between responses of the reference model and those of the feedback system is employed for tracking control. Because the criterion is nonconvex with respect to controller parameters, its second order Taylor expansion, which is convex

The paper deals with the distributed minimum sharing problem: a set of decision-makers compute the minimum of some local quantities of interest in a distributed and decentralized way by exchanging information through a communication network. We propose an adjustable approximate solution which enjoys several properties of crucial importance in applications. In particular, the proposed solution has good

This paper develops an online algorithm to solve a time-varying optimization problem with an objective that comprises a known time-varying cost and an unknown function. This problem structure arises in a number of engineering systems and cyber–physical systems where the known function captures time-varying engineering costs, and the unknown function models user’s satisfaction; in this context, the

The P-difference between two sets A and B is the set of all points, C, such that the sum of B to any of the points in C is contained in A. Such a set difference plays an important role in robust model predictive control and set-theoretic control. In this paper, we show that an inner approximation of the P-difference between two sets described by collections of polynomial inequalities can be computed

The ϵ-dependent Lyapunov method is an effective technique to analyze both standard and nonstandard singularly perturbed systems, and the constructed ϵ-dependent Lyapunov function has an impact on the conservatism of the obtained results. This paper proposes a novel ϵ-dependent Lyapunov function, which includes three classes of common ϵ-dependent Lyapunov functions in the existing literature and can

This paper studies the identification of discrete-time nonlinear parameterized control systems in given experiments. A necessary and sufficient condition of the closed-loop identifiability is established for the stable experiments and an algorithm is proposed to estimate the parameter. The estimates are shown to be strongly consistent with the convergence rate explicitly computed under some simple

This article studies two problems related to observability and efficient constrained sensor placement in linear time-invariant discrete-time systems with partial state observations: (i) We impose the condition that both the set of outputs and the state that each output can measure are pre-specified. We establish that for any fixed k>2, the problem of placing the minimum number of sensors/outputs required

This paper deals with formal controller synthesis for discrete-time dynamical systems. We consider a specification provided under the form of a discrete-time hybrid automaton with external inputs, which can represent, for instance, instructions or informations received from a human user or from another system. The hybrid automaton describes the intended behavior of the system and we first consider

We tackle the problem of trajectory planning in an environment comprised of a set of obstacles with uncertain time-varying locations. The uncertainties are modeled using widely accepted Gaussian distributions, resulting in a chance-constrained program. Contrary to previous approaches however, we do not assume perfect knowledge of the moments of the distribution, and instead estimate them through finite

Under terminal constraints, the set of states such that a model-predictive control strategy is feasible, and thus stable, is equivalent to the viable-reachable set of the controlled system. We prove that viscosity and storage function approaches to viability theory are equivalent to each other. Based on these results we propose inner and outer bounds of the feasible set by storage functions, which

Many state estimation and control algorithms require knowledge of how probability distributions propagate through dynamical systems. However, despite hybrid dynamical systems becoming increasingly important in many fields, there has been little work on utilizing the knowledge of how probability distributions map through hybrid transitions. Here, we make use of a propagation law that employs the saltation

Load side participation can provide valuable support to the power network in case of urgencies. On many occasions, loads are naturally represented by on and off states. However, the use of on–off loads for frequency control can lead to chattering and undesirable limit cycle behavior, which are issues that need to be resolved for such loads to be used for network support This paper considers the problem

The problem of trajectory tracking of nonholonomic wheeled mobile robots has been extensively studied in the last decades. Nevertheless, most of the control laws proposed in the literature assume full state measurements. Based on the flatness property of the robot’s kinematic model, we proposed a dynamic feedback linearization controller in combination with attitude and velocity observers. The proposed

This paper aims at the distributed computation for semi-definite programming (SDP) problems over multi-agent networks. Two SDP problems, including a non-sparse case and a sparse case, are transformed into distributed optimization problems, respectively, by fully exploiting their structures and introducing consensus constraints. Inspired by primal–dual and consensus methods, we propose two distributed

The increased penetration of plug-in electric vehicles asks for efficient algorithms to be adopted in parking lots equipped with charging units. In this paper, the peak power minimization problem for a plug-in charging station is addressed. A chance constraint approach is adopted in order to minimize the daily peak power, allowing for a tolerance on the charging service customer satisfaction expressing

The paper addresses large-scale, convex optimization problems that need to be solved in a distributed way by agents communicating according to a random time-varying graph. Specifically, the goal of the network is to minimize the sum of local costs, while satisfying local and coupling constraints. Agents communicate according to a time-varying model in which edges of an underlying connected graph are

In this paper, we propose a compositional approach to construct opacity-preserving finite abstractions (a.k.a symbolic models) for networks of discrete-time nonlinear control systems. Particularly, we introduce new notions of simulation functions that characterize the distance between control systems while preserving opacity properties across them. Instead of treating large-scale systems in a monolithic

Constant power loads (CPLs) in power systems have a destabilizing effect that gives rise to significant oscillations or to network collapse, motivating the development of new methods to analyse their effect in AC and DC power systems. A sine qua non condition for this analysis is the availability of a suitable mathematical model for the CPL. In the case of DC systems power is simply the product of

H2 static and dynamic output-feedback control problems are investigated for linear time-invariant uncertain systems. The goal is to minimize the averaged H2 performance in the presence of nonlinear dependence on time-invariant probabilistic parametric uncertainties. By applying the polynomial chaos theory, the control synthesis problem is solved using a high-dimensional expanded system which characterizes

In this paper, we consider the frequency synchronization problem in a network of lossless, connected, and network-reduced power system. Frequency synchronization is an important problem in power systems as frequency deviation can lead to degraded power quality, tripping of generators, etc. We present a load-estimator-based consensus algorithm in a network of fourth-order generator models that achieves

Connected and automated vehicles (CAVs) provide the most intriguing opportunity to improve energy efficiency, traffic flow, and safety. In earlier work, we addressed the constrained optimal coordination problem of CAVs at different traffic scenarios using Hamiltonian analysis. In this paper, we investigate the properties of the unconstrained problem and provide conditions under which different combination

This paper is concerned with the event-triggered output regulation problem for a class of linear networked switched systems (NSSs). A mode-dependent alternate event-triggered mechanism (AETM) is integrated into the NSSs with transmission delays and packet losses for the first time based on continuous detection and periodic sampling, and a joint-designed switching signal with the triggering information

Exact discrete-time models of nonlinear systems are difficult or impossible to obtain, and hence approximate models may be employed for control design. Most existing results provide conditions under which the stability of the approximate model in closed-loop carries over to the stability of the (unknown) exact model but only in a practical sense, i.e. the trajectories of the closed-loop system are

This work presents DMPC (Data-and Model-Driven Predictive Control) to solve control problems in which some of the constraints or parts of the objective function are known, while others are entirely unknown to the controller. It is assumed that there is an exogenous “black box” system, e.g. a machine learning technique, that predicts the value of the unknown functions for a given trajectory. DMPC (1)