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A complex dynamical network (CDN) can be considered as the composition system with the nodes subsystem (NS) and the links subsystem (LS), and both subsystems are coupled with each other. In this paper, two vector differential equations (VDE) are used to describe the dynamical behaviours of NS and LS, respectively, in which the dynamical behaviour of NS is considered as the VDE with the second derivative term (SDT). This paper mainly focuses on the dynamics of LS, which is represented as VDE with the intuitive topologic feature of outgoing links, and investigates the design of the tracking controller for NS and the auxiliary tracking objectives (ATO) for LS. Firstly, the dynamical models of NS and LS in CDN are proposed, and the corresponding assumptions are given. Secondly, based on Lyapunov stability theory, the controller of NS and the ATO of LS are designed so that the state of NS can asymptotically track the given reference signal. Finally, the effectiveness of the proposed control strategy in this paper is verified by the numerical simulation example with N two-links robots. Abbreviations: ATO: auxiliary tracking objectives; CDN: complex dynamical network; LS: links subsystem; MDE: matrix differential equation; NS: nodes subsystem; SDT:second derivative term; VDE: vector differential equation; [ABSTRACT FROM AUTHOR]

This paper presents an end-user privacy and thermal comfort preserving approach for residential thermostatically controllable loads (TCLs) to provide demand response (DR) in grid services under uncertainties. Unlike the standard approach whereby a central utility-level control is used to control end-users loads, this paper splits the control effort between a central coordinating controller and local robust controllers. The Lagrangian relaxation (LR) method is applied by relaxing the power tracking constraint to obtain a hierarchical control framework with a local controller at each household level and a coordinating controller at the central utility level. Household-level local controllers are based on robust model predictive control (MPC) that relies on minimum household-specific information while accounting for thermal model parameter uncertainties and forecast errors associated with exogenous inputs. Considering inverter-type air conditioners as the TCL, the approach is validated using a practical signal corresponding to the Australian Energy Market Operator. The results demonstrate that accurate tracking of the load set-point signal can be achieved under a considerable range of uncertainties while preserving thermal comfort for end-users. Furthermore, the proposed DR scheme is computationally tractable and robust for real-world implementation. [ABSTRACT FROM AUTHOR]

This paper deals with a new design problem of adaptive gain robust model-following/tracking controllers for a class of systems with matched and unmatched uncertainties via piecewise Lyapunov functions. In the proposed design approach, compensation inputs for matched and mismatched uncertainties for the system are introduced and the proposed adaptive gain model-following/tracking robust controller can achieve that the tracking error decreases asymptotically to zero in spite of uncertainties. In this paper, on the basis of the concept of piecewise Lyapunov functions, we show linear matrix inequality-based sufficient conditions for the existence of the proposed controller. Finally, a numerical example is given to demonstrate the effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]

In this paper, for strict-feedback nonlinear systems with positive odd rational powers, the problem of adaptive fixed-time tracking control (FTTC) is considered. With the support of fixed-time theorem and adaptive backstepping method, this paper proposes a new globally adaptive FTTC strategy, which can overcome the singular problems caused by the derivation of virtual control signal. In addition, the proposed control scheme is a universal approach that can be applied to other types of nonlinear systems. Furthermore, the designed adaptive fixed-time tracking controller ensures the boundedness of all signals in the controlled system, and it guarantees the tracking error converges to a small neighbourhood near equilibrium in fixed-time. Finally, the simulation result further verifies the feasibility of the presented control scheme. [ABSTRACT FROM AUTHOR]

In this paper, some less conservative sufficient conditions for uniform exponential stability, local uniform exponential stability and uniform practical exponential stability of nonlinear time-varying systems on time scales are proposed. Compared with the traditional exponential stability results, the negative definiteness of the time derivatives of Lyapunov functions is weakened, that is, the time derivatives of related Lyapunov functions in this paper are allowed to be indefinite. The main tools used are some Gronwall's inequalities on time scales. Two examples are also included to verify the effectiveness of the results obtained. [ABSTRACT FROM AUTHOR]

To solve the control problem of time-varying state-scale nonlinear systems whose initial state is not affected by settling time, fixed-time convergence algorithms are proposed for first-order systems and higher-order systems in this paper. First, a scalar model is used to illustrate how the time-varying feedback parameter can guarantee that the system achieves asymptotic stability while achieving finite-time convergence, and it is proved that the settling time obtained in this paper is only related to the prescribed boundary. This allows us to design the settling time with an appropriate parameter based on the prescribed boundary. To exhibit the effectiveness and extensibility of the proposed algorithm for first-order scalar systems, the results are subsequently extended to general higher-order systems based on the backstepping method. By introducing numerical simulation results, this paper verifies that the proposed algorithm will make the system achieve asymptotic stability and its output can converge to a given boundary, regardless of the system's initial states. [ABSTRACT FROM AUTHOR]

This paper studies the problem of scheduling control data transmissions from embedded processors to physical systems. For this problem, we propose novel state feedback and output feedback control architectures that are predicated on energy function-based and norm-free event-triggering conditions, where the embedded processor broadcasts a sampled data of its control signal value through a zero-order-hold operator to the physical system when the left side of the event-triggering condition equals to its right side. In this context, the energy function-based feature means that the right sides of the proposed event-triggering conditions involve an energy function as well as its time-derivative to make the selection of these right sides user-adjustable. Furthermore, the norm-free feature means that the left sides of the proposed event-triggering conditions do not depend on signal norms to allow for better control data transmission reduction. System-theoretical analyses of our event-triggered state feedback and output feedback control architectures are shown using the same energy functions and their time-derivatives used in the proposed event-triggering conditions, where illustrative numerical examples are also presented to demonstrate the efficacy of our contributions. To the best of our knowledge, the results given in this paper explore how event-triggering conditions are linked not only to energy functions but also to their time-derivatives for the first time. [ABSTRACT FROM AUTHOR]

This paper studies the $ {H_\infty } $ H ∞ filtering problem for a class of discrete-time semi-Markov switching repeated scalar nonlinear systems with an event-triggered scheme. Considering the limitation of bandwidth, the mode-dependent event-triggered mechanism is introduced to determine whether the currently sampled sensor data is transmitted to the filter, in which the parameters of the event generator depend on the system mode. By means of a constructed time-varying Lyapunov function, the two stages of the systems jump instant and mode residence are analysed, and a linear matrix inequality technique is used to ensure the mean-square stability and $ {H_\infty } $ H ∞ performance of the filter error system. Accordingly, the co-design method of the mode-dependent time-varying filter and the event-triggered mechanism is derived for semi-Markov switching systems. Finally, a numerical simulation is given to illustrate the effectiveness and feasibility of the method proposed in this paper. [ABSTRACT FROM AUTHOR]

In this paper, an optimisation problem for the monotone mean-variance (MMV) criterion is considered from the perspective of the insurance company. The MMV criterion is an amended version of the classical mean-variance (MV) criterion which guarantees the monotonicity of the utility function. With this criterion we study the optimal investment and reinsurance problem which is formulated as a zero-sum game between the insurance company and an imaginary player. We apply the dynamic programming principle to obtain the corresponding Hamilton–Jacobi–Bellman–Isaacs (HJBI) equation. As the main conclusion of this paper, by solving the HJBI equation explicitly, the closed forms of the optimal strategy and the value function are obtained. Moreover, the MMV efficient frontier is also provided. At the end of the paper, a numerical example is presented. [ABSTRACT FROM AUTHOR]

This paper considers modeling and state estimation of timed discrete-event systems (TDESs) with communication delays and losses. In the previous framework, the specified closed-loop system language may contain physically impossible strings, i.e. strings never occur in practice. To exclude these physically impossible strings, this paper presents a new modeling framework for supervisory control of networked TDESs. Specifically, we first analyse how to model and update the observation channel and the control channel under communication delays and losses. We then construct an automaton that explicitly describes the interaction process between the plant and the supervisor over the observation channel and the control channel so that the language of the closed-loop system can be specified. Compared with the existing work, the proposed framework can model the 'dynamics' of the closed-loop system more accurately. Under the proposed framework, we further estimate states of the closed-loop system under communication delays and losses. The state estimation is implemented on-the-fly and bases on only the information of observations and controls in history. As an application of the proposed modeling and state estimation approaches, we finally extend the existing approaches to find all the admissible and safe supervisors of networked TDESs. [ABSTRACT FROM AUTHOR]

This paper suggests a new dynamic sliding mode controller incorporating a disturbance observer for controlling integrating processes with time delay. Here, a new reaching law has been introduced to expedite the system response without evoking chattering. The convergence of this law is also studied. Additionally, the whole system stability is proved using the Lyapunov stability theory. This paper also proposes a new disturbance observer to improve the disturbance rejection and to help suppress chattering further. The suggested observer has only one parameter to be designed. Therefore, this observer can easily be implemented. Several simulation examples and a real-time application are considered to prove the superiority of the suggested controller over the reported controllers in the literature. [ABSTRACT FROM AUTHOR]

In this paper, we investigate various stabilisation problems of a hybrid system of elasticity, consisting of a thin tape, which moves axially between two sets of rollers. We present a control solution, which works simultaneously, for three variants of the tape model. In particular, we design boundary feedback control laws via Lyapunov's second method. The resulting closed-loop system for the general case is then analysed, where we prove the existence and uniqueness of solution using the semigroup theory of linear operators; furthermore, we prove the exponential decay of the solution via a frequency domain theorem. The stabilisation of the two other special cases is derived implicitly from the general case proofs presented in the paper. Finally, the paper is concluded by presenting computer simulations to support the theoretical results. [ABSTRACT FROM AUTHOR]

To improve the ride comfort of the vehicle and the high-efficiency control requirements of the suspension, this paper proposes a time-delay control strategy and the idea of using a linear motor as the actuator. This paper analyses the damping characteristics of the time-delay control strategy in the time domain and frequency domains. A linear equivalent excitation method is proposed to optimise the optimal time-delay control parameters under complex excitations. The stability of the system is analysed. The damping effect of time-delay control active suspension is verified by numerical simulation. An experimental hardware platform of a linear motor and active suspension was built further to verify the effectiveness of the time-delay control strategy. The experimental results show that the relative errors of root mean square values of experimental and simulation results are within 16% under each working condition. The experimental results verify the effectiveness of the simulation results. [ABSTRACT FROM AUTHOR]

This paper investigates the fixed-time consensus control for a class of multi-agent systems subject to unknown bounded disturbances under undirected topology. Firstly, the nonlinear controllers and the measurement errors are designed based on the hyperbolic tangent function to avoid the non-differential problem. Secondly, a distributed fixed-time control protocol is designed, which can realise the fixed-time convergence and improve the system convergence rate independent of the system's initial state. Thirdly, the dynamic event-triggered mechanism is proposed, such that the triggering frequency of events is reduced and communication energy consumption can be saved. The stability analysis is presented by employing the Lyapunov theory and the Zeno phenomenon is excluded. Finally, the simulation examples are presented to show the effectiveness and advantages of the proposed method in this paper. [ABSTRACT FROM AUTHOR]

This paper proposes Brenke-type polynomials for uncertainty approximation in adaptive control of cooperative electrically driven manipulators. The contribution of this paper is reducing the number of signals needed in the construction of the regressor vector for uncertainty approximation due to the simplicity of Brenke-type polynomials in comparison with other alternatives. It is verified that uniformly bounded stability of the tracking/approximation errors can be assured if the Brenke-type polynomials are utilised as regressors. Moreover, it has been assumed that velocity signals are not available for feedback. Different trajectories, including simple and highly complicated and fast paths, have been tested in simulation results. The results are also compared with four state-of-the-art powerful approximation methods to show the accuracy and efficiency of the proposed controller structure. [ABSTRACT FROM AUTHOR]

This paper deals with the robust state feedback stabilizability problem of linear time-invariant (LTI) systems in the presenceof polytopic uncertainty. The paper contributes two major results involving (i) necessary and sufficient conditions to simultaneouslycheck positivity and robust stability of an uncertain LTI system (ii) the development of a design algorithm to solve the mainstabilizability problem. This problem is not easy to deal with because it is not a convex problem. To cope with this issue, a designalgorithm is proposed that checks the design space of the stabilizer parameters, divides it into smaller subspaces, checks thefeasibility of the corner points of the design subspaces, removes the detected total infeasible design subspaces, and shrinks theremaining parts to solve the design problem, iteratively. The proposed algorithm is applied to the cancer chemotherapy applicationand the results demonstrate its efficacy to control the model considering the positivity condition. [ABSTRACT FROM AUTHOR]

The eigenstructure of imaginary axis eigenvalues of a Hamiltonian matrix is of importance in many fields of control systems, for example, in stability analysis of linear Hamiltonian systems, computation of the solutions of an algebraic Riccati equation (ARE), existence of a Lyapunov function for LTI systems, etc. The dynamical system consisting of all stationary trajectories for an optimal control problem – often called the Hamiltonian system – is known to admit, in its state space dynamical equation, a Hamiltonian matrix for the system matrix. In each of these cases, defectiveness of imaginary axis eigenvalues of a Hamiltonian matrix turns out to be of crucial importance. For example, defectiveness causes unboundedness of the oscillatory stationary trajectories in the Hamiltonian system. A characterisation of the ARE solutions in terms of Lagrangian invariant subspaces of the Hamiltonian matrix when the imaginary axis eigenvalues are defective has been addressed in the literature for the controllable case. This paper focuses on the general case of uncontrollable systems; we formulate conditions under which the imaginary axis eigenvalues of the Hamiltonian matrix are non-defective: this is central for solutions corresponding to imaginary axis eigenvalues to not become unbounded. We provide conditions on the so-called ϵ -characteristic of the non-defective imaginary axis eigenvalue: this helps in the characterisation of Lagrangian invariant subspaces. We formulate conditions under which a passivity-based Hamiltonian matrix is normal (i.e. it commutes with its transpose), and we link normality of such Hamiltonian matrices with all-pass behaviour. In summary, this paper formulates results that link defectiveness of imaginary axis eigenvalues of Hamiltonian matrix to solvabilities of Lyapunov and Algebraic Riccati equations, controllability/observability, ϵ -characteristic and sign-controllability. We consider examples in the area of bounded-real transfer functions and RLC circuits, both controllable and uncontrollable, to study applicability of the results of this paper. [ABSTRACT FROM AUTHOR]

In this paper, the problem of sampled-data adaptive tracking control for a class of switched nonlinear systems with prescribed performance is considered. In order to guarantee the system is stable and achieves the prescribed performance in sampled-data control, a coordinate transformation satisfying the prescribed performance is introduced. In addition, the neural networks (NNs) used to approximate the unknown nonlinear functions and the backstepping technique are applied to design the sampled-data controller and the adaptive laws. An upper bound on the sampling period is obtained to maintain the stability of the systems. It is confirmed that the designed sampled-data scheme ensures that all signals of the closed-loop system are semi-globally uniformly ultimately bounded (SGUUB) and the tracking error is limited to the prescribed performance function. The effectiveness of the designed control scheme is demonstrated by two simulation examples. [ABSTRACT FROM AUTHOR]

In this paper, we propose an event-triggered dual-mode predictive control strategy to deal with two-channel packet dropouts for discrete-time constrained nonlinear networked control systems. The main focus is on the construction of network compensation mechanisms and control algorithms. Firstly, two types of novel event generators are set, respectively, in sensor node and controller node to reduce resource consumption while preserving the desired system performance. In order to establish corresponding event-triggering conditions, two special states, successful transmitted states and reconstructed states, are introduced. Subsequently, a dual-mode control scheme, where the switch of modes depends on reconstructed states, is designed. The recursive feasibility of optimization problems is ensured by determining relationships between actual states and reconstructed states. By constructing actual control laws under two system modes, the stability property of closed-loop systems is guaranteed. Furthermore, effects of packet dropouts and disturbances on system performance are analyzed. At last, the efficiency of the proposed control strategy is illustrated by a cart-damper-spring simulation example. [ABSTRACT FROM AUTHOR]

This paper is concerned with the stability analysis of the stochastic strict-feedback nonlinear systems with time-varying delays on networks (SSNSTDN) via pinning control. Different from the previous literature, the new model we studied owns the non-strongly connected topology. The actual controllers are realised by back-stepping and designing virtual controllers. In particular, a novel method for constructing global Lyapunov functions is proposed,which exploits the Lyapunov function of each stochastic strict-feedback nonlinear systems with time-varying delays (SSNSTD) to construct the global Lyapunov function of SSNSTDN. Meanwhile, combining the Lyapunov method with graph theory, several sufficient conditions to guarantee the exponential stability in mean square of SSNSTDN are obtained in the form of coefficients-type criterion. Furthermore, we apply our main results to investigating the stabilisation of stochastic coupled oscillators with time-varying delays on networks and the effectiveness of proposed theories is illustrated by some numerical examples. [ABSTRACT FROM AUTHOR]

This paper discusses the problem of marking constraints in a class of partially controllable timed Petri nets. Specifically, these are Timed Event Graphs (TEGs) which include disturbed input transitions and which are subject to token capacity constraints in some paths. Using the Min-Plus algebra formalism, formal approaches are proposed to design causal control laws to guarantee compliance with marking constraints in TEGs. Sufficient conditions are defined to show the existence and synthesis of these controllers. The developed methodologies are illustrated in a case study of a disassembly system with a limited stock of components. [ABSTRACT FROM AUTHOR]

In this paper, an observer-based tracking control problem is considered for a polynomial system with parameter uncertainties and external disturbances. Noting that some states are difficult to measure in practice, a polynomial state observer is employed to obtain the unknown states. Then a robust observer-based tracking controller is designed to force the states of the polynomial uncertain system to follow the ones of the reference model and satisfy $ H_\infty $ H ∞ performance. By using a full-state-dependent homogeneous polynomial function, the solvability condition is derived for the observer-based tracking control strategy, which reduces conservatism. Sum of squares technique is utilised to calculate the corresponding observer and controller, effectively dealing with the calculation problem in polynomial systems. Simulation examples are given to illustrate the effectiveness of the presented control strategy. [ABSTRACT FROM AUTHOR]

The looped-functional approach has been extensively used for stability analysis of sampled-data systems. For this approach, this paper introduces two new functionals to minimise the conservatism of stability conditions. The first one is called a non-negative integral functional (NIF) that is added to the derivative of a common Lyapunov functional. The second one is a general looped-functional (GLF), whose values at sampling instants are traditionally not well-defined, and are defined here in terms of their limits. Leveraging further affine canonical Bessel-Legendre inequalities expressed by simplified polynomials, a polynomial-based NIF, a polynomial-based GLF, and a polynomial-based zero equality are tailored for obtaining hierarchical types of stability conditions in the form of linear matrix inequalities. Finally, numerical examples show that: (i) the proposed functionals lead to less conservatism when compared with several state-of-the-art methods; and, (ii) the resulting stability conditions exhibit a hierarchical characteristic in the sense that the higher level of hierarchy, the less conservatism of the criteria. [ABSTRACT FROM AUTHOR]

In this paper, the joint state and fault estimation problem for a class of discrete-time complex networks with time delays is investigated. The information on the dynamics of the fault is not required with an appropriate structure of the proposed fault estimator. Unbiased state and fault estimation can be obtained simultaneously at each node only with locally available information, thereby avoiding the requirement of a centre node which collects information from every node. Considering the effects of time delays and the interconnections between different nodes, an upper bound of the estimation error covariance is calculated, and the desired filter parameters are obtained in a recursive manner such that the trace of the bound is minimised. The existence conditions of the developed filter are provided explicitly as well. Finally, a simulation example is employed to demonstrate the state estimation and fault diagnosis performances of the given strategy. [ABSTRACT FROM AUTHOR]

This paper considers the problem of the instability issues of stochastic differential systems with impulsive effects. Definitions of instability including almost sure exponential instability, pth moment exponential instability and pth moment instability are given. By using the Lyapunov functions, the comparison theorem and the average impulsive interval condition, several instability criteria are established. Three examples are given to illustrate the effectiveness of the theoretical results. [ABSTRACT FROM AUTHOR]

We consider a class of forced continuous-time Lur'e systems obtained by applying nonlinear feedback to a higher-order linear differential equation which defines an input-output system in the sense of behavioural systems theory. This linear system directly relates the input and output signals and does not involve any internal, latent or state variables. A stability theory subsuming results of circle criterion type is developed, including criteria for input-to-output stability and strong integral input-to-output stability, concepts which are very much reminiscent of input-to-state stability and strong integral input-to-state stability, respectively. The methods used in the paper combine ideas from the behavioural approach to systems and control, absolute stability theory and input-to-state stability theory. [ABSTRACT FROM AUTHOR]

This paper proposes a novel control methodology to achieve fixed-time stabilisation for a class of three-order nonlinear systems based on fast nonsingular terminal sliding mode control. In this research, based on the combination of integral fast nonsingular terminal sliding mode (IFNTSM) surface and fixed-time control theory, a novel backstepping fast nonsingular terminal sliding mode (FNTSM) controller is being studied. The interests of this method are that the presented controller can not only maintain the characteristics of integral fast nonsingular terminal sliding mode control (IFNTSMC) but also has the advantages of fixed time convergence and fast transient response. Piecewise function is introduced to solve the singularity problem caused by negative exponential term. Our control strategy achieves the stabilisation performance within finite convergent time being independent of initial condition. The control scheme is applied to the gyros system with chaotic state and suppress its chaotic phenomenon. The theoretical results are supported by simulation results. [ABSTRACT FROM AUTHOR]

This paper introduces a feedforward control method for physical systems that can be described with linear parameter-varying (LPV) models. The proposed feedforward controller structure is consequently derived from a generic LPV representation and is shown to be identifiable directly from noisy measurement data. The identified structure is advantageous for feedforward control, as using a simple least squares algorithm allows to parameterise basis functions representing the required input trajectory to follow a given output trajectory. Also, with the proposed regularisation, the input trajectory remains bounded even when the physical system exhibits non-minimum phase behaviour. Additionally, the proposed controller structure does not possess states but only considers the inputs and outputs signals and their derivatives, leading to a unique physical interpretation of each controller's parameter. Multiple feedforward controllers identified at various operating points can therefore be directly merged to create a parameter-varying controller. A nonlinear and locally non-minimum phase system is considered in this study, i.e. an engine air path, to evaluate the performances of the proposed feedforward strategy. The controller parameters are first identified from noisy measurement data, and then the proposed feedforward controller is implemented with a feedback controller to track the exhaust pressure and $ \mathrm {NO}_{\mathrm {x}} $ NO x concentration. Using a detailed physical simulation of the engine air path, the proposed feedforward strategy showed encouraging output tracking performances compared to state-of-the-art control methods. The presented feedforward method is shown to be straightforward to identify and calibrate while guaranteeing a contained computational complexity and being applicable to many physical systems thanks to its modularity. [ABSTRACT FROM AUTHOR]

The focus of this paper is the design of open-loop control profiles for linear differentially flat systems whose model parameters are uncertain and are represented probabilistically. To account for the time-invariant model parameter uncertainties, polynomial chaos is used to derive a surrogate model which permits easy evaluation of the mean and variance of the uncertain states. A chance constrained optimisation problem is posed to minimise the terminal error of the stochastic states for a prescribed risk of not satisfying the terminal state bounds. To permit posing a convex optimisation problem, the cost function which is the residual energy is approximated by a hypercube circumscribing the hypersphere which bounds the terminal residual error. This relaxation permits posing a convex optimisation problem to arrive at the robust control profile. The proposed technique is illustrated on two examples including the benchmark spring-mass-dashpot system undergoing a rest-to-rest maneuver and a UAV undergoing a translation in a prescribed time. Parametric studies are conducted where the impact of varying the order of the polynomial chaos expansion and the degree of the parameterised control profiles are used to conclude that a 2–3 degree polynomial chaos expansion is sufficient to capture the time evolution of the mean and variance of the states which are required for the chance constrained optimisation problems. As expected, the design results in improved performance as the number of free variables used to parameterise the control profiles increases. [ABSTRACT FROM AUTHOR]

This paper focuses on finite-time adaptive practical tracking control for a class of high-order nonlinear systems with full-state constraints and input saturation. The state constraints are handled by applying nonlinear transformed functions (NTFs) and the input saturation is estimated by an auxiliary hyperbolic tangent function. On the basis of adding a power integrator technique and adaptive control method, an adaptive state feedback controller is designed for the closed-loop system. With the aid of finite-time stability theory, the tracking error converges to a bounded neighbourhood of the origin in a finite time, and all the signals in the closed-loop system are bounded. At last, a simulation example and a practical example are presented to show the effectiveness of the proposed control procedure. [ABSTRACT FROM AUTHOR]

This paper designs a novel coordinated control scheme to improve the control performance of voltage source converters (VSC) based multi-terminal high voltage direct current (MTDC) transmission network by merging the benefits of adaptive drooping and voltage margin controllers. In this proposed scheme, the droop coefficient is used to manage the DC voltage and maintain power sharing by shifting the control modes of the rectifiers and inverters in the presence of considerable power disturbances. The droop coefficient is planned based on the stability limit of DC voltage. The performance of the designed control scheme is compared to that of existing coordinated control and voltage margin droop control approaches. A ±400 kV five-terminal VSC-MTDC network is developed in PSCAD to verify the planned control method. The simulation results indicate that the proposed control scheme can achieve good performance for controlling the DC voltage and maintaining active power in the MTDC system. [ABSTRACT FROM AUTHOR]

This paper investigates the secure optimal tracking control problem for cyber-physical systems, in which the controller-actuator channel is jammed by denial-of-service attacks. Without leveraging model knowledge, learning-based tracking control algorithms are proposed by utilizing the measured input-output data. The impact of malicious attacks on tracking performance is discussed. More specifically, an augmented system consisted of the system model and the reference model is derived. Then the states of the augmented system are rewritten by utilizing the input, output, and reference trajectory, following which both the Bellman equation and algebraic Riccati equation are given. The conditions of existence and uniqueness of the solution to the algebraic Riccati equation are derived. Furthermore, both policy iteration and value iteration learning-based tracking control algorithms are provided for cyber-physical systems against denial-of-service attacks, and the convergence of the algorithms is also proved. Finally, a DC motor system and a numerical example are given to illustrate the effectiveness of the proposed control algorithms. [ABSTRACT FROM AUTHOR]

In this paper we present and provide a proof for a set of non-recursive formulae arising in the computation of the largest output-nulling and the smallest input-containing subspaces which have been used in a variety of contexts in the framework of the geometric approach. These expressions have been used in the literature both in the strictly proper and in the non-strictly proper case, but, to the best of our knowledge, a proof is still missing. These formulae are established here in the general possibly non-strictly proper case. Some ancillary side results of independent interest are also proposed. [ABSTRACT FROM AUTHOR]

In this paper, the quantisation synchronisation control problem of bilateral teleoperation systems with communication delays is investigated. The inaccurate modelling problem including the system uncertainties and the unknown disturbances are compensated by using the radial basis function networks (RBFN). By introducing the hysteretic quantiser, the control signals are quantised to a set of discrete values to ease the accuracy requirement for actual physical systems and the requirement for communication rate. The position synchronisation of joint variables between the master and slave manipulators is achieved by using the designed control signals and adaptive parameters. Simulation results verify that the synchronisation tracking errors gradually converge to a small neighbourhood around zero. [ABSTRACT FROM AUTHOR]

In this paper, we have analysed the influence of viscoelastic and frictional damping on the decay rate of solutions for a Kirchhoff-type viscoelastic wave equation with a distributed delay acting on nonlinear internal damping. Taking the relaxation function of a fairly large class and using the method of energy in which we introduce an adapted Lyapunov functional and by exploiting certain properties of convex functions, under certain assumptions on the constants of system, we obtain the optimal decay rate of energy in the sense that it is compatible with the decay rate of the relaxation function. [ABSTRACT FROM AUTHOR]

In this paper, we mainly concern the fixed-time consensus control problem for nonlinear leader-following multi-agent systems(MASs). An edge-based adaptive control protocol is presented with part of parameters updated by relative information of system state. Compared with the common node-based adaptive protocols, the proposed edge-based adaptive control protocol assigning different time-varying weights to different communication edges is more accurate. By selecting special Lyapunov functions and theoretical analysis, the obtained conclusions indicate that both sufficient conditions and the settling time of the fixed-time consensus are independent of the system's global information such as the spectrum of Laplacian matrix, which implies that the given protocol is fully distributed. Finally, numerical simulation is illustrated to support the correctness of the main theoretical results. [ABSTRACT FROM AUTHOR]

This paper aims at adaptive event-triggered output-feedback stabilisation in the presence of intractable non-parametric uncertainties. Typically, double-side (i.e. sensor-to-controller and controller-to-actuator) event-triggered communication is pursued for efficient resource utilisation, unlike in related works only reducing single-side communication. This renders more constrained information transmitted via network, challenging the co-design of the compensation and event-triggering mechanisms. By incorporating a switching-varying mechanism, a distinctive adaptive event-triggered output-feedback scheme is established based on a switching filter reconstructing the unmeasurable states. Crucially, a convergence-preserving event-triggering mechanism is proposed with the adaptiveness for uncertainty compensation, by suitably exploiting the switching-varying gain. As such, a desired event-triggered output-feedback control is designed with linearity (with respect to the system output and the filter states) rendered for the controller signal. Just owing to the linearity, the controller signal is subtly kept from entering the event-triggering mechanism, so as to match the double-side event-triggered architecture. Furthermore, it is achieved that the system and filter states converge to zero while a positive minimum inter-execution time is ensured. [ABSTRACT FROM AUTHOR]

The Gilpin-Ayala (GA) ecosystem is one of the most important biological mathematical models. The exploration of various kinetics behaviours of GA-ecological model has attracted the attention of many mathematicians. This paper focuses on a nonlinear periodic GA-predation ecosystem with infinite distributed lags on time scales. In the sense of time scale, our model unifies the difference model and differential model of GA-predation ecosystem. We first discuss a class of auxiliary functions with only two real roots. By using these auxiliary functions, coincidence degree and some inequality techniques, we next obtain some existence conditions of periodic solution. Furthermore, we explore the global asymptotic stability of periodic solution on account of Lyapunov stability theory. An example and its simulation are provided to inspect the correctness and availability of our main results at last. [ABSTRACT FROM AUTHOR]

We investigate the robustness, disturbance attenuation and performance capabilities of a Proportional-Integral-Retarded (PIR) controller when controlling a class of uncertain second-order systems with input disturbances. The purpose of this paper is to provide insight into the trade-offs between these conflicting requirements. This is accomplished by introducing simple delay-dependent stability conditions, expressed in linear matrix inequality form, which are used to establish the trade-offs in PIR control. In light of the obtained stability conditions, we show that improving performance comes at the cost of reduced robustness and disturbance attenuation. To our knowledge, this problem has not been addressed before and these new results provide valuable insights and systematic guidelines for designing these controllers with trade-offs in mind, thereby completing our current understanding of the tuning mechanisms in PIR control. Inspired by the application field of fuel-cell systems, experiments are carried out on a proof-of-concept switching converter prototype to demonstrate the relevance of the obtained results. [ABSTRACT FROM AUTHOR]

This paper presents a learning- and scenario-based model predictive control (MPC) design approach for systems modelled in the linear parameter-varying (LPV) framework. Using input-output data collected from the system, a state-space LPV model with uncertainty quantification is first learned through the variational Bayesian inference Neural Network (BNN) approach. The learned probabilistic model is assumed to contain the true dynamics of the system with a high probability and is used to generate scenarios that ensure safety for a scenario-based MPC. Moreover, to guarantee stability and enhance the performance of the closed-loop system, a parameter-dependent terminal cost and controller, as well as a terminal robust positive invariant set are designed. Numerical examples will be used to demonstrate that the proposed control design approach can ensure safety and achieve desired control performance. [ABSTRACT FROM AUTHOR]

This paper proposes a novel stable economic model predictive control (EMPC) strategy for constrained nonlinear systems with changing economic criteria. The traditional EMPC may lead to infeasibility and even instability of the closed-loop system when the criterion has been changed. Firstly, a generalised terminal constraint is introduced to ensure the recursive feasibility of the economic optimisation problem, which enforces the terminal states to converge to an arbitrary equilibrium state rather than a predetermined fixed one at the initial time. Then the stability constraint is constructed by solving an auxiliary optimisation problem online, which is the key to guaranteeing the asymptotic stability of the closed-loop system. Finally, sufficient conditions for feasibility and asymptotic stability are derived in the context of changing economic criteria. The main feature of the proposed strategy is that it does not need to know the changes of economic criterion in advance, and its properties and effectiveness are exemplified by simulations on a nonlinear chemical process example. [ABSTRACT FROM AUTHOR]

This paper addresses the problem of H∞ performance analysis of 2D discrete singular stochastic system described by Roesser model which is challenging since it involves 2D random variables and the disturbance simultaneously. Sufficient conditions are established for the regularity, causality and stability of the system. The proposed results are expressed in terms of strict linear matrix inequalities. Furthermore, a mean square asymptotic stability with an $ H_{\infty } $ H ∞ disturbance level is developed. Simulation example is provided in order to illustrate the relevance of our approach. [ABSTRACT FROM AUTHOR]

In this paper, the discrete Walsh functions are first used for time domain model order reduction (MOR) of discrete-time bilinear systems. Firstly, in terms of the discrete Walsh functions, the reduced order system is generated by means of the explicit solution formula for the discrete-time bilinear system. Meanwhile, we expand the discrete-time bilinear system under space spanned by the discrete Walsh functions. Then the reduced order system is produced by the orthogonal projection matrix that is defined by discrete Walsh coefficient matrix. Moreover, MOR method via discrete Walsh functions is investigated for discrete-time bilinear systems with nonzero initial conditions, where nonzero initial condition is also utilized to create the orthogonal projection matrix. Theoretical analyses show that the outputs of the resulting reduced order systems can match the first several outputs of the original system in finite intervals. Finally, an example is given to illustrate the effectiveness of the proposed methods. [ABSTRACT FROM AUTHOR]

This paper studies the problems of stability analysis and stabilisation synthesis for a class of impulsive switched stochastic systems. By constructing a novel impulsive switching condition, the sufficient conditions of globally asymptotic stability in probability and stochastic input-to-state stability for the considered systems are presented. Furthermore, the stabilising controller design method can be presented for the corresponding closed-loop systems. Two examples are given to illustrate the effectiveness of the obtained results. [ABSTRACT FROM AUTHOR]

This paper copes with a matter of event-triggered fast finite-time prescribed tracking control for non-affine stochastic nonlinear systems, in which deception attacks are taken into consideration. The main objective of the proposed controller is that all the closed-loop variables are bounded in probability, and the tracking error is constrained to the predefined funnel functions by choosing suitable parameters. Primarily, the mean value theorem is utilised to transform the considered systems into the equivalent systems with affine structures. Next, based on the backstepping algorithm, a modified event-triggered scheme is developed to save the network resources. Meanwhile, the unknown parts in the designed systems are approximated by neural networks. Finally, an actual simulation is conducted to verify the validity of the theorem. [ABSTRACT FROM AUTHOR]

Partially stable systems involve dynamical systems whose motion lie in a subspace of the state space resulting in system stability with respect to part of the system's states. In this paper, we develop partial stability theorems for nonlinear continuous-time and discrete-time dissipative feedback systems. Specifically, by invoking additional structural constraints on the forward loop and feedback loop system storage functions, we develop feedback interconnection partial stability results for dissipative nonlinear dynamical systems. Our results provide extensions of the positivity and small gain theorems for guaranteeing partial stability of feedback interconnected systems. [ABSTRACT FROM AUTHOR]

In this paper, we propose a novel adaptive friction estimator for simple mechanical systems with Coulomb friction. We assume that the friction constant is unknown and we propose an adaptive observer for its estimation. We show that under certain conditions the observer structure is asymptotically stable. The proposed observer dynamics has two tuning parameters and essentially behaves as a second-order switching system. These parameters could be utilised to tune some time domain performance measures such as settling time, per cent overshoot. etc., under certain conditions. Lastly, simulations reveal that when the actual friction is not confined to Coulomb friction only, the proposed design improves the position tracking performance, especially when the position controller has low bandwidth. [ABSTRACT FROM AUTHOR]

This paper proposes observer based controls for a MIMO Timoshenko beam system with disturbances and references from an exosystem, and by further limiting the references and disturbances, also gives reduced-order controls. At first, we propose state feedback controls to guarantee the output regulation problem of a nominal Timoshenko beam system, which is obtained by specially choosing known disturbances and references. This also makes the PDE observer easily designed based on tracking errors only. Then, exosystem observers and their reduced-order forms are proposed in case of different geometric multiplicities and limited conditions of disturbances, references and system uncertainties. This gives observer based robust controls and reduced-order observer based controls. Robust output regulation is proved for the Timoshenko beam under observer based controls. Simulation examples are provided for a Timoshenko beam system with different references and system uncertainties. [ABSTRACT FROM AUTHOR]

This paper applies iterative learning control to point-to-point tracking problems with a general networked structure. The data is quantised and transmitted through restricted communication channels from the controller to the actuator. Combining a logarithmic quantizer with an encoding and decoding mechanism to quantise the input signals reduces the influence of the quantisation error. New design algorithms are developed with conditions for convergence of the tracking error and an extension to fault-tolerant performance under actuator failures. A numerical-based case study demonstrates the application of the new designs, which includes a comparison with another ILC law and the relative merits of the encoding and decoding schemes. [ABSTRACT FROM AUTHOR]

The ranking of nodes in a network according to their centrality or ''importance'' is a classic problem that has attracted the interest of different scientific communities in the last decades. The COVID-19 pandemic has recently rejuvenated the interest in this problem, as the ranking may be used to decide who should be tested, or vaccinated, first, in a population of asymptomatic individuals. In this paper, we review classic methods for node ranking and compare their performance in a benchmark network that considers the community-based structure of society. The outcome of the ranking procedure is then used to decide which individuals should be tested, and possibly quarantined, first. Finally, we also review the extension of these ranking methods to weighted graphs and explore the importance of weights in a contact network by providing a toy model and comparing node rankings for this case in the context of disease spread. [ABSTRACT FROM AUTHOR]