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In this paper, an adaptive fixed-time output feedback formation control problem is investigated for nonlinear multi-agent systems with a nonstrict-feedback structure. In the controller design procedure, the neural network state observer is designed to estimate the unmeasurable state variables. Dynamic surface control (DSC) technique is applied to avoid the repeated differentiation for the virtual control signals. The dynamic surface compensation signals can realise the practical fixed-time bounded. Utilising the classified discussion method, the difficulty of controller design caused by the existence of observer error term is addressed. The technique of transformation of the index set is employed to cope with the related variables of the neighbour states, which simplifies the controller design. Under the presented control mechanism, all closed-loop signals remain bound for a fixed period of time, the formation control performance target between all followers and leader can be achieved. And the formation errors and state observers errors are both bounded such that can converge to a little domain around zero. Simulation results are provided to test the availability of the presented strategy. [ABSTRACT FROM AUTHOR]

In this paper, an online convex optimisation problem with stochastic constraints in the bandit setup is investigated. We are particularly interested in the scenario where the gradient information of both loss and constraint functions is unavailable. Under this scenario, only the values of loss and constraint functions at a few random points near the decision are provided to the decision maker after the decision is submitted. We first propose an online bandit algorithm based on the virtual queue in which two-point feedback is used to approximate the gradient feedback. Then we adopt the static benchmark to analyse the optimisation performance and establish the sub-linear expected static regret and sub-linear expected constraint violations of the proposed algorithm in the two-point bandit feedback setup. Moreover, the expected static regret and constraint violations are further improved to O (ln ⁡ T) when loss functions satisfy the condition of strong convexity. Finally, an online job scheduling numerical simulation is shown to demonstrate the performance of the proposed method and to corroborate the theoretical guarantees. [ABSTRACT FROM AUTHOR]

In this paper, a hybrid-based model-free iterative learning control algorithm is proposed to improve the robustness and convergence speed of model-free iterative learning control in noisy environments. The proposed algorithm divides the iterative process into a rapidly decreasing error phase and an error convergence phase, and uses different control algorithms in different phases, thus combining different advantages of the original algorithms. In addition to this, this work proves the convergence and robustness of the proposed algorithm and summarises the design idea of this controller. Finally, the convergence performance of the algorithm in noisy environments and in variable reference trajectory environment is simulated to demonstrate the effectiveness of the algorithm proposed in this work. [ABSTRACT FROM AUTHOR]

In this paper, a novel fractional-order Proportional-Integral Derivative (PID) controller design depending on optimal selection of frequency domain specifications is proposed for time delay systems. The frequency domain specification sets, namely, (i) phase margin and gain crossover frequency and (ii) phase margin and gain margin are determined so that the reference model is optimal according to three time domain performance indices, i.e. Integral Square Error (ISE), Integral Time Square Error (ITSE) and Integral Absolute Error (IAE). Here, the delayed Bode's ideal transfer function is employed in the reference model. Moreover, the stability region of the reference model is given via a theorem. In simulation studies, the proposed methodology is compared with other two different methods using the same frequency domain specifications. It is observed that the proposed optimal fractional-order PID controllers outperform according to the mentioned performance indices, and they also possess considerably acceptable performance in terms of other time domain specifications such as overshoot, settling time, etc. [ABSTRACT FROM AUTHOR]

This paper is concerned with the linear quadratic optimal control problem for the time-delay stochastic system with partial information. The main contribution is to derive the equivalent solvability condition and give the explicitly optimal controller under partial information in terms of the Riccati equations. The key is to explicitly solve the forward and backward stochastic difference equations with partial information, which is derived from the stochastic maximum principle. [ABSTRACT FROM AUTHOR]

An adaptive approximated inverse control scheme for a class of high-order nonlinear multi-agent systems with unknown control directions is proposed in this paper. The adaptive control problem under the case it is not required to be identical for the unknown control directions is solved by some novel Nussbaum functions and a monotonously increasing sequence, leading our multiple Nussbaum functions reinforce rather than counteract each other. Also, it is introduced in the design and analysis like some integrable auxiliary signals and a novel contradiction argument. Moreover, hysteresis nonlinearity is counteracted by constructing its approximated inverse compensator. With these efforts, stability analysis ensures that all the closed-loop system signals are uniformly bounded, and it is successfully achieved the asymptotic convergence of tracking error to zero, circumventing the obstacle caused by the unknown control directions. Experiment results illustrate the effectiveness of the proposed scheme. [ABSTRACT FROM AUTHOR]

This paper focuses on the linear quadratic optimal control problem for stochastic systems with a special terminal penalty. The specialty lies in that the terminal penalty is a quadratic term over the conditional expectations of the terminal state. The essential difficulty lies in an additional measurability constraint on the input induced by the conditional expectation term, which is shared by the control problems for the stochastic system with delays, rational expectations problems, control problems involving conditional expectation terms, asymmetric information control and so on. A new idea, dynamic programming combined with orthogonal decomposition, is proposed to deal with this problem. The orthogonal decomposition eliminates the additional measurability constraint on the input. The solvability condition and the optimal controller are obtained by developing generalised Riccati equations. Numerical experiment is provided to support the achieved results. [ABSTRACT FROM AUTHOR]

This paper addresses the output regulation problem with prescribed performance for nonlinear lower-triangular systems. To achieve the transient prescribed performance, the output transformation technique and barrier Lyapunov function technique are introduced to solve the output regulation problem. The prescribed performance control scheme based on normal backstepping is constructed not only to restrict the output error of the closed-loop system keeping in a prescribed performance bound, but also to achieve that the output tracks a designed trajectory asymptotically. The effectiveness of the proposed method is illustrated by two simulation examples. [ABSTRACT FROM AUTHOR]

This paper addresses the output tracking control problem for networked systems with plant-model mismatch, where two-channel random network delays are considered. According to the different ways of obtaining future control commands, two networked predictive control (NPC) methods are designed. One is the NPC method using one-way time delays, called ONPC, and the other is the NPC method using round-trip time delays, called RNPC. Furthermore, they are compared in terms of the way of compensation for two-channel delays, prediction process, and communication load, respectively. Then, the closed-loop stability conditions of the RNPC system and the ONPC system for the plant-model mismatch and match cases are derived, and their output tracking performance is also theoretically analysed. Finally, the results of the theoretical analysis are verified through numerical simulation that illustrates the effectiveness of the proposed two NPC methods as well as their separate advantages. [ABSTRACT FROM AUTHOR]

This paper studies the target circumnavigation problem by multiple second-order agents under directed topology. All agents need to surround the target with prescribed formation and circular velocity. Firstly, according to the control objectives, the cooperative circumnavigation problem is converted into the stability problem of the corresponding error system. Then, the error system is divided into two second-order subsystems, and a distributed controller comprised of two parts is delivered. The stability analysis of the whole system is given by the employing cascaded control theory. One key merit of the proposed controller is that the prescribed formation is an extensive case and unlimited, including different tracking radii and angular spacing. Another merit is that the communication topology among agents only needs to have a directed spanning tree. Furthermore, the controller can be implemented by each agent in its local frame so that only local information is utilised without knowing global information. These all extend the scope of practical application, the controller is more universal. Finally, the simulations validate the effectiveness of the proposed controllers. [ABSTRACT FROM AUTHOR]

In this paper, an adaptive finite-time impedance control strategy based on optimised backstepping (OB) technique is proposed for robotic manipulators subject to state constraints. The existing OB methods approximately solve the intractable Hamilton-Jacobi-Bellman equation by reinforcement learning (RL) with Bellman residual error, which has intricate actor-critic updating laws and persistence excitation requirement. To overcome this drawback, we construct the simplified RL updating laws by converting the problem to the solution of a positive-definite function, which is composed of actor-critic network weights. Then, the simplified RL updating laws can significantly reduce the controller complexity and relax the persistence excitation. Based on the barrier Lyapunov function, a barrier-type performance index function is constructed for the optimised controller under state constraints. The finite-time stability theory can guarantee the finite-time convergence property of the closed loop system without violating the prescribed constraints. Finally, we demonstrate the effectiveness of the proposed method in the simulation example with environment-robot interaction. [ABSTRACT FROM AUTHOR]

This paper addresses the problem of event-triggered control for a class of nonlinear systems with unknown control coefficients, time-varying delays, full state constraints and external disturbances, simultaneously. Firstly, based on integral Barrier-Lyapunov Functionals, an adaptive event-triggered controller is designed to account for the impacts of complete state constraints, unknown time-varying delays and external disturbances. Using fuzzy logic systems, the unknown functions of systems are then roughly estimated. The system redundancy can be significantly reduced by implementing the event-triggered control technique in the meanwhile. By introducing the separation technique and Lyapunov–Krasovskii functionals, it is shown that the strategy can ensure tracking performance greatly and all the closed-loop signals of the system are bounded. Compared with the existing results, the proposed design scheme is less conservative and has a wilder application range. Finally, the simulation results show the effectiveness of the proposed approach. [ABSTRACT FROM AUTHOR]

In this paper, the problem of the networked set-membership state estimation is discussed for a class of nonlinear discrete time-varying systems subject to cyber attacks and time delays. Two forms of malicious attacks (i.e. Denial-of-Service (DoS) attack and bias injection attack) are taken into account to describe the adversary's attempt to destroy/deteriorate the system performance via communication network. It is the aim of the investigated issue to propose a set-membership state estimator ensuring the required estimation performance despite the existence of both the external mixed attacks and internal time delays. By resorting to the feasibility of a series of matrix inequalities, sufficient conditions are provided for the solvability of the addressed state estimator design problem. Furthermore, an optimisation strategy is developed with the purpose of seeking the local optimal estimator parameters. At last, a numerical simulation example is presented to demonstrate the effectiveness of the proposed theoretical algorithm. [ABSTRACT FROM AUTHOR]

This paper studies the consensus tracking problem based on optimised backstepping technique for multiagent systems with power exponential functions and the privacy protection. Under the optimised backstepping technique, the controllers with power functions are designed by utilising the reinforcement learning strategy. Moreover, the synchronisation error converges to a predetermined region within a user-defined settling time by utilising a speed function. To ensure the safety of communication, the privacy protection is applied to multiagent systems, which effectively prevent information exposure. Based on Lyapunov stability theory, the tracking errors of the system with power exponential functions converge to a predetermined region, and a simulation example proves the feasibility of the proposed strategy. [ABSTRACT FROM AUTHOR]

This paper investigates the stochastic event-triggered remote state estimation problem over a collision channel. The remote estimator does not have the knowledge of the measurement in the case of collision and the origin of the data packet in the case of successful transmission, resulting in the non-Gaussianity of the estimation process in the two cases. By using a commonly used Gaussian approximation method, the posterior distribution of the system state is proved to be a mixture of two Gaussians and a mixture of three Gaussians in the cases of collision and successful transmission, respectively. Then an approximate minimum mean squared error estimator with adaptive weights is proposed, and the weights convexly combine the estimates for the possible transmission situations. Moreover, the proposed estimator is also shown to be conventional forms under three extreme situations. Finally, numerical results illustrate the effectiveness of the proposed estimator based on the incomplete information. [ABSTRACT FROM AUTHOR]

This paper addresses a low-cost adaptive prescribed time tracking control strategy for switched nonlinear systems with input quantisation and unknown backlash-like hysteresis. Initially, a transformation function is introduced into the control design, which allows the tracking error of the controlled systems to a specified accuracy within a preassigned settling time. Unlike the existing prescribed time control scheme that only uses transformation function technique in the first step of the backstepping design, the transformation function is introduced to each step of the controlled systems, which makes only one adaptive parameter that needs to be updated online. Then, to synthesise a low-cost control scheme, a first-order sliding mode differentiator and a single-parameter estimation method are implemented based on the newly constructed coordinate transformations. Meanwhile, the Nussbaum technique successfully solves the effects caused by the unknown control direction, unknown backlash-like hysteresis and quantised input. All signals of the closed-loop systems are bounded under the proposed control scheme with arbitrary switching signal. Finally, the validity of the presented method is confirmed via two simulation examples. [ABSTRACT FROM AUTHOR]

Tracing the rapid progress of communication network, the control of dynamic evolution of network has become a central issue. There are a lot of tipping phenomena in network congestion systems. Therefore, tipping control principally centres on traditional control policies, and some advanced control approaches need to be supplemented. In this paper, a fractional-order proportional-integral-derivative (PID) controller is introduced to a network congestion model to ponder corresponding bifurcation-induced tipping regulation. First, a fractional-order congestion model with fractional-order PID controller is constructed. Then the onset of the tipping induced by Hopf bifurcation of the uncontrolled model is studied. By contrast, the tipping point can be delayed under the controller for the controlled model. Some conditions under which Hopf bifurcation occurs are given. The stable and unstable ranges of control parameters for the controlled model are also deduced. At last, some simulated examples are given to verify the theoretical results and demonstrate the superiority of the controller in tipping regulation. Moreover, the bidirectional effects of the controller are displayed by manipulating the control parameters. [ABSTRACT FROM AUTHOR]

In this paper, we present an innovative decentralised control framework, designed to address stochastic dynamic complex systems that are influenced by multiple multiplicative noise factors. Our advanced approach builds upon the foundation of conventional Decentralised Fully Probabilistic Design (DFPD) by refining the Riccati equation to accommodate multiple noise sources effectively. By embracing the inherent stochastic nature of complex systems, our methodology fully characterises their dynamic behaviours using probabilistic state–space models, delivering a comprehensive representation of subsystem components. Importantly, the DFPD approach also incorporates system and input constraints by characterising their corresponding ideal distributions, ensuring optimal functionality and performance while adhering to permissible boundaries. To further enhance system performance, we introduce a probabilistic message passing architecture that enables seamless communication between neighbouring subsystems and promotes harmonised decision-making among local nodes. To demonstrate the efficacy of our proposed framework, we employ a three-inverted pendulum system as a numerical example and compare its performance to that of the conventional DFPD. Through this comparison, we showcase the advantages of our novel decentralised control approach in handling complex systems with multiple noise factors. [ABSTRACT FROM AUTHOR]

In this paper, the distributed mixed H 2 / H ∞ fusion filter design problem is investigated for a class of cyber-physical systems subject to non-ideal measurements under Round-Robin protocol. To save the limited communication resources, the Round-Robin protocol is employed to schedule the data transmissions from the sensors to the remote filters. The measurement is imperfect by taking into account the noises, the random saturations, nonlinearity perturbations and packet dropouts. The objective of this study is to propose a desired fusion filtering method that ensures the prescribed performance constraints on both the local and fusion filtering error dynamics. With the aid of Lyapunov function and stochastic analysis technique, a sufficient condition is established to guarantee the mixed H 2 / H ∞ performance index for the local filtering error systems, and then the filter parameter matrices are derived by resorting to the solutions to some matrix inequalities. Subsequently, on the basis of the obtained local state estimates, the proper fusion parameters are acquired by solving a convex optimisation problem. Finally, a numerical example is provided to demonstrate the effectiveness of the designed fusion filter. [ABSTRACT FROM AUTHOR]

In this paper, a novel image-based prescribed performance visual servoing control scheme with hysteresis quantised input is proposed for quadrotor unmanned aerial vehicles (QUAVs, for short). First, based on the perspective projection principle, effective image features are defined on a image plane called virtual image plane, and the decoupled image feature dynamics are achieved with respect to target points. Then, the image feature dynamics and QUAV dynamics are combined to derive a nonlinear dynamic system, and the nonlinear system is decoupled into two subsystems based on the commonly used inner–outer loop control framework. Furthermore, the prescribed performance control-based visual servoing control scheme with hysteresis quantizer is designed, and the necessary stability proof is presented. Finally, the numerical simulations and experiments are conducted to validate the effectiveness of the proposed control scheme. [ABSTRACT FROM AUTHOR]

This paper analyses the probabilistic stability of power control systems under Nakagami-m fading channels caused by multi-path propagation. First, the Nakagami-m fading model is utilised to capture the feature of shadowed fading channels. The Foschini–Miljanic algorithm is utilised to achieve the desired quality-of-service, and a stability condition is given for the power control system. Then, the probability of the system being stable is obtained for power control systems. Afterwards, the monotonicity of the probability with respect to the communication distance is revealed, which sheds light on the node configuration. Furthermore, it is shown that Nakagami-m fading links can model the channel gains better than Rayleigh fading links by adjusting the shape parameter. Finally, an example is given to illustrate the effectiveness of the theoretical results. [ABSTRACT FROM AUTHOR]

This paper studies the problem of dynamic adaptive event-triggered synchronisation control for a class of complex dynamical networks (CDNs) with parameter uncertainty and stochastic network attacks. In order to save communication resources, reduce the driving burden and overcome the conservatism of fixed parameters, an improved event-triggered control strategy is designed. Firstly, a new synchronisation error model with uncertain of internal coupling weights between nodes and stochastic network attacks on actuator is modelled. Secondly, the Bernoulli stochastic distribution process is used to describe the probability of stochastic attacks, and the actuator failure model is adopted to depict actuator failure. By establishing an appropriate Lyapunov function, some sufficient conditions to ensure the asymptotic stability of the synchronisation error system is derived, which reduces conservatism. In addition, the cooperative design of controller and adaptive event-triggered strategy is solved by solving linear matrix inequality. Eventually, two examples are given to illustrate the effectiveness and potential of the proposed design method. [ABSTRACT FROM AUTHOR]

In this paper, a novel multidisciplinary design optimisation (MDO) algorithm is proposed, which is named as the decomposition-based switching multi-objective whale optimiser (SMWO/D). In particular, a penalty-Tchebycheff value-based decomposition framework is designed to decouple the strongly correlated conflicting objectives, so as to give comprehensive considerations to different disciplinary demands. To overcome the shortcoming of premature in the complicated multi-modal non-linear decision space, two adaptively switchable evolutionary modes are defined to enhance the ability of escaping from local optimum and promote a thorough global search with rich learning strategies. The proposed SMWO/D is evaluated on a series of benchmark functions, and the results show its competitiveness in terms of comprehensive performance as compared with other four popular decomposition-based multi-objective optimisation algorithms (MOAs). In addition, sensitivity analysis is carried out to determine the best parameter configuration of SMWO/D. Finally, in a case study of a real-world turbine disk structural optimisation, the practicality of the proposed SMWO/D is validated, which can effectively handle the multidisciplinary property of this complicated problem, thereby providing valuable experiences in the aero-engine MDO domain. [ABSTRACT FROM AUTHOR]

Nonlinear dynamics is frequently encountered in practical applications. Adaptive dynamic programming (ADP), which is implemented via actor/critic neural networks with excellent approximation capabilities, is appropriate to be used in finding the solution for the control problem in the presence of known/unknown nonlinear dynamics. The objective of this paper is to introduce state-of-the-art ADP-based algorithms and survey the recent advances in the ADP-based control strategies for nonlinear systems with various engineering-oriented complexities. Firstly, the main motivation of the ADP-based algorithms is thoroughly discussed, and the way of implementing the ADP-based algorithms is highlighted. Then, the latest research results concerning ADP-based control policy design for nonlinear systems are reviewed in detail, Finally, we conclude the survey by outlining the challenges and possible research topics in the future. [ABSTRACT FROM AUTHOR]

This paper presents an efficient analytical approach for solving the problem of dissipative control in one-sided Lipschitz singular Caputo fractional-order systems subject to nonlinear perturbations. The approach is based on mathematical transformations, and fractional calculus. A state feedback controller is designed to ensure that the closed-loop system is regular, impulse-free, and finite-time bounded with a dissipativity performance index. The results are established using tractable strict linear matrix inequalities (LMIs) without any equality constraint. Two numerical examples are provided to demonstrate the effectiveness of the proposed approach. [ABSTRACT FROM AUTHOR]

This paper presents a series of structure-preserving model order reduction algorithms for K-power bilinear systems via Laguerre functions. The method first aims to rewritten the K-power bilinear system as a general bilinear system and calculate the approximate low-rank factors of the cross Gramian of the bilinear system by combining the idea of Laguerre functions expansion of the matrix exponential function. After that, the approximate balanced system of the K-power bilinear system is constructed by the corresponding projection transformation of each subsystem. In order to achieve the purpose of model order reduction, the states with smaller singular values are then truncated, so as to further obtain the reduced order model. For this approach, there is a disadvantage that unstable systems may be generated although the original one is stable. To alleviate the inadequacies of this approach, we have improved the model reduction procedure, which is based upon the dominant subspace projection method. In addition, we also carried out a correlation analysis on the stability of improved algorithms. Finally, numerical experiments are employed to substantiate the effectiveness of the presented algorithms. [ABSTRACT FROM AUTHOR]

This paper considers reachable set estimation for discrete-time linear time-delay systems. With the assumption that the unknown initial condition and disturbances are bounded by zonotopes, three zonotope-based methods are proposed to estimate the real-time reachable sets. We find that the couplings in the time-delay systems lead to conservative estimation results and propose a reachable set estimation method based on state augmentation. The augmentation-based method can reduce the conservatisms caused by the time-delay and achieve more accurate reachable set estimation. Simulation results demonstrate the performances of the proposed methods. [ABSTRACT FROM AUTHOR]

In this paper, we consider the energy-to-peak filtering issue for a class of linear parameter-varying (LPV) systems with time delays subject to certain communication regulation under which only one sensor is allowed to transmit its measurement data at each transmission instant. The data communication is regulated by the random access protocol (RAP) for the purpose of avoiding data collisions. The main purpose of this paper is to design an LPV filter such that the resultant filtering error system is asymptotically stable and also satisfies the prescribed l 2 - l ∞ performance in the mean square. Taking into account both the LPV nature and the possible gain perturbations, a parameter-dependent resilient filter is constructed according to the plant dynamics and scheduling behaviour of the RAP. The desired filter gain matrices are obtained by solving a set of linear matrix inequalities. Finally, a simulation example is given to validate the effectiveness and correctness of the filter design scheme. [ABSTRACT FROM AUTHOR]

In the paper, we are concerned about the global asymptotic synchronisation for a class of fuzzy master–slave inertial neural networks with time-varying delays. At present, most of the research on the global asymptotic synchronisation of fuzzy master–slave inertial neural networks with time-varying delays adopt the matrix measure method, linear matrix inequality approach and integral inequality method. While in our paper, we attain three criteria to assure the global asymptotic synchronisation between the master system and the slave system by designing three classes of different novel controllers via the maximum-value analysis approach. The controllers designed and the maximum-value method used in this paper are completely novel compared with these in the existing literatures, which enrich and extend the published results. [ABSTRACT FROM AUTHOR]

Exponential Euler differences for semi-linear differential equations of first order have got rapid development in the past few years and a variety of exponential Euler difference methods have become very significant researching topics. Therefore, exponential Euler differences for fractional-order differential models are novel and significant. In allusion to fuzzy Cohen–Grossberg neural networks of fractional order, this paper establishes a Mittag–Leffler Euler difference model on the basis of the constant variation formula in fractional calculus. In the second place, the existence of a unique global bounded solution and equilibrium point is studied by using the contractive mapping principle. Thirdly, global exponential stability and synchronisation of the derived difference models are investigated by employing some inequality techniques and reductio. At last, some illustrative examples and numerical simulations are employed to demonstrate the main results of this paper. [ABSTRACT FROM AUTHOR]

The problem of complete controllability is addressed for a class of switched time-varying impulsive systems under multiple input delays. Several controllability criteria are obtained with the aid of algebraic and geometric tools. Firstly, the explicit expression of solution on every impulsive interval for such systems is derived by mathematical induction and variation of parameters. Then, complete controllability is investigated for the underlying system based on the solution established. Specifically, the new necessary or/and sufficient algebraic controllability conditions are obtained without assuming that all impulse-dependent matrices are non-singular. In addition, the geometric criteria with regard to the constant matrices are further discussed when the considered system reduces to a time-invariant case. Finally, numerical examples are worked out to demonstrate the controllability tests derived in this paper. It is shown that the existence of the delayed term will potentially affect the controllability of the studied system. In contrast to the existing literatures, the criteria derived in this paper removing some constrained assumptions have less conservatism and can be used to verify the controllability of a more general linear hybrid system. [ABSTRACT FROM AUTHOR]

This paper addresses novel discrete-time H 2 and H ∞ filter designs for polytopic linear parameter-varying (LPV) systems. A less conservative approach is employed to obtain the synthesis conditions, such that the polytopic LPV system state-space representation may have all its matrices subject to time-varying parameters and be solved by an efficient procedure. Parameter-dependent Lyapunov functions are used to derive both H 2 and H ∞ discrete-time filter design conditions resulting in a poly-quadratic approach in terms of linear matrix inequalities. A multi-objective H 2 / H ∞ solution is also provided. The proposed conditions have the advantage of recovering the established poly-quadratic concept as a particular case, which was an unresolved problem until the present paper. Moreover, using the addressed approach, it is possible to obtain improved quadratic H 2 and H ∞ filters. Numerical examples illustrate the proposed design methods applicability as an observer to estimate LPV system states and its performance in comparison with other approaches. [ABSTRACT FROM AUTHOR]

In this paper, we deal with the problem of local passivity and local feedback passivation of smooth discrete-time nonlinear systems by considering their piecewise affine approximations. Sufficient conditions are derived for local passivity and local feedback passivity. These results are then extended to systems that operate over Gilbert-Elliott type communication channels. One of the main features of the approach presented in this paper is that it allows us to design the controller by solving a few linear matrix inequalities (LMIs) that are subject to certain constraints. As a special case, results for feedback passivity of piecewise affine systems over a lossy channel are also derived. [ABSTRACT FROM AUTHOR]

This paper is concerned with an adaptive neural output-feedback control for a class of stochastic nonlinear systems with unknown control directions and hysteresis input. An output-feedback controller is developed for stochastic nonlinear via using radial basis function neural networks (RBFNNs) and adaptive backstepping method. A state observer is designed to estimate the unmeasurable system state signals. Nussbaum gain technique is employed to deal with the unknown control directions. Simultaneously, the backlash-like hysteresis input control in this paper is considered. An adaptive controller is designed to ensure that the output tracking error converges on a small region of the origin. Finally, the control scheme ensures that all signals in the closed-loop systems are semi-global uniformly ultimately bounded. Results of simulation cases are presented to prove the effectivity of the theoretical analysis. [ABSTRACT FROM AUTHOR]

This paper addresses the adaptive finite-time tracking problem for nonlinear sandwich systems with dead-zone nonlinearity and full state constraints. The existence of the non-smooth dead-zone nonlinearity between the subsystems of the sandwich system makes the controller design as a challenging task. In this paper, a novel adaptive backstepping controller is proposed by employing the finite-time stability theorem and based on the barrier Lyapunov functions and finite-time command filters. The proposed controller guarantees the output tracking of the specified time-varying reference signal with the sufficiently small bounded tracking error in a finite-time. Moreover, all states of the controlled system are confined to predefined compact sets. To verify the theoretical achievements and show the applicability of the proposed method, simulation results are provided for both numerical and practical examples. [ABSTRACT FROM AUTHOR]

The problem of impulse analysis is considered for the T-S fuzzy singular system by using the Kronecker index and the generalised Kronecker index in this paper. The T-S singular system is divided into two cases: the uniformly regular T-S fuzzy singular system and the non-uniformly regular T-S fuzzy singular system. The contribution of this paper is twofold. First, a new definition of the generalised Kronecker form is introduced, and the algorithm of finding the generalised Kronecker form is given. Second, two theorems are proved, one is that the uniformly regular T-S fuzzy singular system is impulsive if and only if the Kronecker index is greater than one, the other one is the non-uniformly regular T-S fuzzy singular system is impulsive if and only if the generalised Kronecker index is greater than one. Finally, two numerical simulations and the population model with stage structure are carried out to show the consistency with theoretical analysis and illustrate the effectiveness of the algorithm. [ABSTRACT FROM AUTHOR]

This paper considers the dynamic output feedback robust model predictive control (MPC) for a system with both polytopic model parametric uncertainty and bounded disturbance. For this topic, the techniques for handling the unknown true state are crucial, and the strict guarantee of the input/output/state constraints requires replacing the true state by its bounds in the optimisation problems. Previously, in the separate works, we (i) gave the general polyhedral bound; (ii) proposed the general ellipsoidal bound; (iii) applied some special polyhedral bounds to tighten the ellipsoidal bound since the latter is crucial for guaranteeing recursive feasibility. In this paper, (i)-(iii) are unified, and the up-to-date least conservative treatment of the true state bound is given, so the control performance can be greatly improved. The contribution mainly lies in overcoming the difficulties in developing technical details for the unification. A numerical example is given to illustrate the effectiveness of the new method. [ABSTRACT FROM AUTHOR]

The paper established a conventional bus traffic network and a subway network by using the method of space R based on the existing public traffic network model. Regarding these two networks as the sub-networks, this paper presented a new two-layer-coupled public traffic network with multi-weights through the transfer relationship between conventional bus lines and subway lines. Every edge of this model's two sub-networks has one or several different property weights, and the coupling edges between two sub-networks have one weight. Based on the method of network split, the paper splits the complex networks with multi-weights into several different single-weighted two-layer-coupled public traffic networks and then investigates its global synchronisation. Finally, according to the synchronisation theory of coupling networks with multi-weights and taking 'Lorenz system' as the network node, some numerical examples are given to show the impact of congestion degree, passenger-flow density, transfer degree and capacity matching degree to the two-layer-coupled public traffic network balance. [ABSTRACT FROM AUTHOR]

This paper is concerned with the problem of finite time dissipativity-based reliable control for a time-varying system with linear fractional uncertainty (LFU) and time delay. An actuator fault model consisting of both linear and nonlinear faults is considered during the time-varying control process. By implementing an augmented time-varying Lyapunov functional and using the Wirtinger-type integral inequality, delay-dependent finite time dissipative conditions are established in forms of derivative linear matrix inequalities (DLMIs), which can guarantee the closed-loop system is finite time dissipative for all admissible uncertainties. Then, the DLMIs are transformed into a series of recursive linear matrix inequalities (RLMIs) based on the discretization method. And an algorithm is given to solve the RLMIs to obtain the state feedback gain. Simulation results demonstrate the validity of the proposed approach. [ABSTRACT FROM AUTHOR]

This paper is to investigate the linear minimum mean square error estimation for Markovian jump linear system subject to unknown Markov chains, multi-channel mode and observation delays, and packet losses. The reorganisation method is employed to convert the delayed measurement system into an equivalent delay-free one and a new state variable is introduced, by which the original state estimation with transmission delays and data losses is transformed into the new state estimation for the reorganised delay-free system with jumping parameters and multiplicative noises. The new state estimation is derived via the innovation analysis method, and an analytical solution to the estimator is given in terms of a set of generalised Riccati difference equations based on a set of coupled Lyapunov equations. Then the original state estimation will be obtained via the jumping property. Finally, we show that the difference Riccati equations converge to a set of generalised algebraic Riccati equations under appropriate assumptions, which result in an optimal stationary filter. [ABSTRACT FROM AUTHOR]

In this paper, a set of conditions for defining output functions is derived such that a system can become passive by static state feedback. A key feature of the proposed set of conditions is that several output functions that satisfy these conditions can be defined without any transformation into a normal form or any need of linearisation of the system. In essence, this paper introduces a new connection between the Lyapunov stability concept and minimum phase property which is indeed a necessary condition of feedback passivity. [ABSTRACT FROM AUTHOR]

This paper studies adaptive finite-time control problem of a class of nonlinear systems with dynamic and parametric uncertainties. The power of systems in this paper is any positive odd rational number but not necessary equal to or greater than one. To solve this problem, finite-time input-to-state stability (FTISS) is used to characterise the unmeasured dynamic uncertainty. By skillfully combining Lyapunov function, sign function, adding a power integrator, adaptive control and FTISS methods, an adaptive state feedback controller is designed to drive the states to the origin in finite time while maintaining all the closed-loop signals bounded. [ABSTRACT FROM AUTHOR]

This paper is concerned with the event-triggered containment control for stochastic multi-agent systems subject to packet dropouts. The adopted event-triggered protocol is with absolutely triggered conditions catering for the requirement of real-time to an extreme. In light of such a protocol, a novel definition of containment control in mean-square sense, named as χ-containment, is proposed to better describe the tracking dynamics of followers. Based on relative measurement outputs, the purpose of this paper is to design an output-feedback controller such that all followers converge into the convex hull spanned by leaders. First, with the help of the property of the Laplacian matrix, the containment control problem is transformed to an easily setting step by step. Then, sufficient conditions with the form of matrix inequalities are derived to guarantee the desired χ-containment which depends on the initial values and the event-triggered thresholds. By introducing a free matrix combined with an orthogonal basis of the null space of control matrix, the controller gain can be obtained by solving a set of linear matrix inequalities. Finally, a simulation example is given to verify the effectiveness of the designed control protocol. [ABSTRACT FROM AUTHOR]

This paper studies the problem of output feedback disturbance attenuation for a class of nonlinear systems with input matching uncertainty, whose nonlinearities are bounded by unmeasured states multiplying unknown input and output polynomial functions. Combining the technique of dynamic gain and extended state observer, an adaptive output feedback controller is designed to guarantee that the states of the closed-loop system are globally bounded, and the disturbance attenuation is achieved in the -gain sense. [ABSTRACT FROM AUTHOR]

The finite-time almost disturbance decoupling problem is investigated for nonlinear systems in strict feedback form using backstepping. A recursive design algorithm is proposed to construct a continuous stabilising feedback controller so that the corresponding closed-loop system is finite-time stable when there is no external disturbances and the influence of the external disturbances on the output is attenuated to a given degree. This paper is the first to solve the finite-time almost disturbance decoupling problem. Two examples are given to show the feasibility of the proposed design method. [ABSTRACT FROM AUTHOR]

This paper proposes a new adaptive gain robust model-following/tracking controller for a class of uncertain linear systems. The proposed adaptive gain robust controller is composed of state feedback laws with fixed gains, feedfoward inputs for the reference model and nonlinear compensation inputs with adjustable time-varying parameters. Moreover, the proposed control strategy can achieve good transient performance and avoid the excessive control input by means of the design parameter. In this paper, linear matrix inequality-based sufficient conditions for the existence of the proposed adaptive gain controller are given, and two design strategies are presented. Finally, simple illustrative examples are included to show the effectiveness of the proposed adaptive gain robust controller. [ABSTRACT FROM AUTHOR]

In this paper, the problem of H2 and H∞ mixed switching control of uncertain discrete switched systems with time delay is considered via a switching signal design. New Lyapunov functional and Wirtinger inequality are used to guarantee the mixed performance for discrete switched time-delay system. The number of using LMI variables is less than our past proposed approach. Finally, a numerical example is illustrated to show the improvement of the developed results. [ABSTRACT FROM AUTHOR]

This paper investigates the adaptive finite-time modified function projective lag synchronisation with definite attenuation rate for a class of chaotic systems with unknown parameters. Firstly, a novel integral type terminal sliding surface is proposed to ensure the finite-time stability of the sliding motion. Subsequently, an adaptive finite-time control law is designed to guarantee the occurrence of the sliding motion in a limited time and the accurate estimation of the unknown parameters. Moreover, the exponential attenuation rate designed in this paper can further cut down the synchronisation time. Numerical simulations are presented to verify the feasibility and effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]

This paper is concerned with a class of neutral-type competitive neural networks with multi-proportional delays, distributed delays and leakage delays. By employing the differential inequality theory, some sufficient conditions are given to ensure that all solutions of the addressed system converge exponentially to zero vector. An illustrative example is also given at the end of this paper to show the effectiveness of our results. [ABSTRACT FROM AUTHOR]