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1.
This paper is concerned with the problem of event-triggered dissipative state estimation for Markov jump neural networks with random uncertainties. The event-triggered mechanism is introduced to save the limited communication bandwidth resource and preserve the desired system performance. The phenomenon of randomly occurring parameter uncertainties is considered to increase utilizability of the proposed method. To describe such a randomly occurring phenomenon, some mutually independent Bernoulli distributed white sequences are adopted. A mode-dependent state estimator is designed in this paper, which ensures that the estimation error system is extended stochastically dissipative. By using the Lyapunov–Krasovskii functional approach and an optimized decoupling approach, an expected state estimator can be built by solving some sufficient conditions. Two numerical examples are presented to demonstrate the correctness and effectiveness of the proposed method.  相似文献   

2.
《Journal of The Franklin Institute》2021,358(18):10193-10212
In this paper, the non-fragile state estimation problem is investigated for a class of continuous-time delayed complex networks. In the addressed complex network model, the outputs only from partial network nodes are used to fulfill the state estimation task. For improving the efficiency of resource utilization, a dynamic event-triggering mechanism is applied in the design of estimator, where an auxiliary time-varying parameter is introduced to dynamically modulate the triggering condition. Our intention is to obtain the gain parameters of the desired non-fragile state estimator, which can tolerate the norm-bounded gain perturbation. In virtue of a novel Lyapunov functional and matrix inequality technique, sufficient conditions are provided to ensure robustly exponential boundedness for estimation error dynamics, and gain matrices of the estimator are computed based on certain matrix inequalities. An illustrative simulation is presented to show the validity of the non-fragile estimator proposed.  相似文献   

3.
In this paper a new integrated observer-based fault estimation and accommodation strategy for discrete-time piecewise linear (PWL) systems subject to actuator faults is proposed. A robust estimator is designed to simultaneously estimate the state of the system and the actuator fault. Then, the estimate of fault is used to compensate for the effect of the fault. By using the estimate of fault and the states, a fault tolerant controller using a PWL state feedback is designed. The observer-based fault-tolerant controller is obtained by the interconnection of the estimator and the state feedback controller. We show that separate design of the state feedback and the estimator results in the stability of the overall closed-loop system. In addition, the input-to-state stability (ISS) gain for the closed-loop system is obtained and a procedure for minimizing it is given. All of the design conditions are formulated in terms of linear matrix inequalities (LMI) which can be solved efficiently. Also, performance of the estimator and the state feedback controller are minimized by solving convex optimization problems. The efficiency of the method is demonstrated by means of a numerical example.  相似文献   

4.
This paper investigates the safe-circumnavigation problem of a single agent along a group of static targets. We assume in this paper that the distance information cannot be measured directly and only bearing measurements are available. In order to localize the targets, we design the positional estimator where the bearing measurements of the targets are used to construct the system matrix of the state equation of the estimator. To guarantee that the bearing angles are meaningful and with enough precision, we build the condition keeping safe distance between the agent and the targets. Furthermore, a gradual relaxed method is provided to reduce the limitations brought by the mutual restraint between the accuracy of the initial estimation and the desired encircling radius, so as to make the proposed method easy to apply. The performance of the proposed algorithms is verified through an experiment based on a wheeled robot platform.  相似文献   

5.
《Journal of The Franklin Institute》2022,359(18):11155-11185
Nowadays, cyber-physical systems (CPSs) have been widely used in various fields due to their powerful performance and low cost. The cyber attacks will cause security risks and even huge losses according to the universality and vulnerability of CPSs. As a typical network attack, deception attacks have the features of high concealment and strong destructiveness. Compared with the traditional deception attack models with a constant value, a deception attack with random characteristics is introduced in this paper, which is difficult to identify. In order to defend against such deception attacks and overcome energy constraints in CPSs, the secure state estimation and the event-triggered communication mechanism without feedback information are co-considered to reconcile accuracy of estimation and energy consumption. Firstly, an event-triggered augmented state estimator is proposed for secure state estimation and attack identification. Then, under the ideology of equivalence, the augmented state estimator is derived as a concise two-stage estimator with reduced order. The two-stage estimator can perform the secure state estimation and attack identification respectively. The estimators ensure the accuracy of attack identification well since not treating attack information as the trigger event. Afterward, the comparison of the computational complexity of these two algorithms is analyzed. Finally, an example of a target tracking system is supplied to prove the effectiveness and efficiency of the proposed algorithm.  相似文献   

6.
The paper proposes a decentralized state estimation method for the control of network systems, where a cooperative objective has to be achieved. The nodes of the network are partitioned into independent nodes, providing the control inputs, and dependent nodes, controlled by local interaction laws. The proposed state estimation algorithm allows the independent nodes to estimate the state of the dependent nodes in a completely decentralized way. To do that, it is necessary for each independent node of the network to estimate the control input components computed by the other independent nodes, without requiring communication among the independent nodes. The decentralized state estimator, including an input estimator, is developed and the convergence properties are studied. Simulation results show the effectiveness of the proposed approach.  相似文献   

7.
In this paper, we consider output feedback stabilization for an anti-stable Schrödinger equation with both the internal unknown dynamic and external disturbance. An unknown input type state observer is designed in terms of a new disturbance estimator. Different from the existing results, we never use high gain in the observer design. Hence, the boundedness assumption on the derivative of disturbance, that is usually required by finite-dimensional extended state observer, is no longer required. The anti-stable term is treated by the backstepping transformation which is given by ODE form to make the controller design easier. Although the close-loop system is nonlinear, both the well-posedness and the asymptotic stability are obtained by a linear method in terms of an invertible transformation. The numerical simulations are presented to illustrate that the proposed scheme is very effective.  相似文献   

8.
The consensus tacking problem for multi-agent systems with a leader of none control input and unknown control input is studied in this paper. By virtue of the relative state information of neighboring agents, state estimator and disturbance estimator are designed for each follower to estimate the system states and exogenous disturbance, respectively. Meanwhile, a novel control protocol based on two estimators is designed to make tracking error eventually converge to zero. Furthermore, the obtained results are further extended to the leader with unknown control input. A novel state estimator with adaptive time-varying gain is proposed such that consensus tracking condition is independent of the Laplacian matrix with regard to the communication topology. Finally, two examples are presented to verify the feasibility of the proposed control protocol.  相似文献   

9.
This paper is concerned with the robust state estimation problem for semi-Markovian switching complex-valued neural networks with quantization effects (QEs). The uncertain parameters are described by the linear fractional uncertainties (LFUs). To enhance the channel utilization and save the communication resources, the measured output is quantized before transmission by a logarithmic quantizer. The purpose of the problem under consideration is to design a full-order state estimator to estimate the complex-valued neuron states. Based on the Lyapunov stability theory, stochastic analysis method, and some improved integral inequalities, sufficient conditions are first derived to guarantee the estimation error system to be globally asymptotically stable in the mean square. Then, the desired state estimator can be directly designed after solving a set of matrix inequalities, which is robust against the LFUs and the QEs. In the end of the paper, one numerical example is provided to illustrate the feasibility and effectiveness of the proposed estimation design scheme.  相似文献   

10.
This paper develops a novel adaptive state tracking control scheme based on Takagi–Sugeno (T–S) fuzzy models with unknown parameters. The proposed method can deal with T–S models in a non-canonical form and allows the number of inputs to be less than state variables, which is more practical and has wider applications. The needed matching conditions for state tracking are relaxed by using a T–S fuzzy reference model to generate desired state reference signals. A new fuzzy estimator model is constructed whose states are compared with those of the T–S fuzzy model to generate the estimator state error which is used for the parameter adaptive law. Based on the Lyapunov stability theory, it has been proven that all the signals in the closed-loop system are bounded and the asymptotic state tracking can be achieved. The effectiveness of the proposed scheme is demonstrated through a magnetic suspension system and a transport airplane model.  相似文献   

11.
In this paper, a hierarchical estimator combined with the nonlinear observer and particle filter (PF) is proposed to accurately estimate the vehicle state and tire forces of distributed in-wheel motor drive electric vehicles (DIMDEVs) when the traditional tire models are not available. The proposed estimator consists of lower and upper layers. The lower layer, i.e. longitudinal tire force nonlinear observer (LTFNO) aims at estimating the longitudinal force based on the available drive/brake torques and rotational speed of wheels. The convergence of LTFNO is proved by the invariant set principle. The upper layer receives these estimated longitudinal tire forces from LTFNO and estimates the vehicle state including lateral tire forces based on an expert model (EM). The designed EM utilizes basic knowledge and rules about tire characteristics to approximate the unknown lateral tire force. The upper estimator combines with EM (EEM) to further improve the accuracy. The EEM takes the modeling errors and disturbances into account and avoids the usage of complex established tire models. Then PF is applied in the upper layer to complete the estimation, which only needs measurable longitudinal/lateral accelerations and yaw rate signals. Finally, the effectiveness of the designed hierarchical estimator is verified by Carsim and Simulink co-simulations. The results show the proposed strategy can accurately estimate the vehicle state and tire forces in real-time.  相似文献   

12.
This paper addresses the control problem of an uncertain system suffering from an exogenous disturbance. A new degree of control freedom is developed to handle the problem based on the equivalent-input-disturbance (EID) approach. The effect of the disturbance and uncertainties is equivalent to that of a fictitious disturbance on the control input channel, which is called an EID. A state observer and an improved EID (IEID) estimator are devised to produce an estimate that is used to compensate for the disturbance and uncertainties in a control law. A second-order low-pass filter is employed in the estimator to provide a way to solve a tradeoff between disturbance rejection and noise suppression. The slope of the Bode magnitude curve at high frequencies is two times larger for the IEID estimator than for a conventional one. This makes the IEID estimator less sensitive to measurement noise and more practical. Sufficient analyses reveal the mechanism of disturbance rejection, uncertainty attenuation, and noise suppression of an IEID-based control system. A theorem is derived to guarantee system stability and a procedure is presented for system design. Simulations and experiments of the position control of a magnetic levitation system are carried out to show the validity of the presented method.  相似文献   

13.
In a multimodal, system, the growth in the number of possible modal paths makes state estimation difficult. Practical algorithms bound complexity by merging estimates that are conditioned on different modal path fragments. Commonly, the weight given to these local estimates is inversely related to the normalized magnitude of the residuals generated by each local filter. This paper presents a novel dual-sensor estimator that uses a merging formula that is based upon a different function of the residuals. Its performance is contrasted with an estimator using a single sensor and with another dual-sensor algorithm that requires fewer on-line calculations.  相似文献   

14.
This paper is devoted to solving the recursive state estimation (RSE) issue for a class of complex networks (CNs) with Round-Robin (RR) protocol and switching nonlinearities (SNs). A random variable obeying the Bernoulli distribution with known statistical properties is introduced to describe the switching phenomenon between two nonlinear functions. A Gaussian noise and time-varying outer coupling strength are adopted to show the changeable network topology (CNT). The RR protocol is applied to regulate signal transmissions, which determines that the element in measurement output has access to the communication networks at each step. The purpose of this paper is to construct a recursive state estimator such that, for all SNs, time-varying topology and RR protocol, the expected state estimation performance is guaranteed. Specifically, based on two recursive matrix equations, the covariance upper bound (CUB) of state estimation error is obtained firstly and then minimized via designing estimator gain in a proper way. Moreover, a feasible criterion is given to guarantee that the trace of obtained CUB is bounded and a monotonicity relationship is established between state estimation error and time-varying outer coupling strength. Lastly, a simulation experiment is illustrated to verify the feasibility of the addressed estimation method.  相似文献   

15.
We consider a remote state estimation process under an active eavesdropper for cyber-physical system. A smart sensor transmits its local state estimates to a remote estimator over an unreliable network, which is eavesdropped by an adversary. The intelligent adversary can work in passive eavesdropping mode and active jamming mode. An active jamming mode enables the adversary to interfere the data transmission from sensor to estimator, and meanwhile improve the data reception of itself. To protect the transmission data from being wiretapped, the sensor with two antennas injects noise to the eavesdropping link with different power levels. Aiming at minimizing the estimation error covariance and power cost of themselves while maximizing the estimation error covariance of their opponents, a two-player nonzero-sum game is constructed for sensor and active eavesdropper. For an open-loop case, the mixed Nash equilibrium is obtained by solving an one-stage nonzero-sum game. For a long term consideration, a Markov stochastic game is introduced and a Nash Q-learning method is given to find the Nash equilibrium strategies for two players. Numerical results are provided to show the effectiveness of our theoretical conclusions.  相似文献   

16.
This paper is concerned with the anti-disturbance boundary feedback stabilization for a hybrid system coupling a non-uniform elastic string with a rigid body at one end by the active disturbance rejection control technology. An infinite-dimensional disturbance estimator and a Luenberger state observer are designed to estimate the disturbance and state of the system, respectively, based on which, a boundary output feedback control is further proposed to stabilize the system. The control consists of two parts: one part is for the stabilization of system without external disturbance, and the other part is for the rejection of the disturbance by virtue of the disturbance estimator. The well-posedness and exponential stability of the closed-loop system are proved by employing the semigroup theories and frequency domain method. Besides, all the signals of the closed-loop system are shown to be uniformly bounded. Finally, some numerical simulations are presented to validate the effectiveness of the proposed control strategy.  相似文献   

17.
In this paper, a constrained regularized least square (RLS) state estimator is developed for deterministic discrete-time nonlinear dynamical systems subject to a set of equality and/or inequality constraints. The stability of the estimation error is rigorously analyzed. The proposed estimator is then used to handle the important problem of secure communication. At the transmitting end, the output of the constrained unified chaotic system is used as a chaotic mask to achieve a satisfactory and typical secure communication scheme. The encrypted data signal is injected into the transmitter and simultaneously transmitted to the receiver through a public channel. At the receiving end, the constrained RLS estimator is used to reconstruct the states of the constrained unified chaotic system. Simulation results are presented to show the impact of the imposed constraints on the waveform and the pattern of the generated chaotic signal as well as the ability of the proposed estimator to synchronize the actual and estimated states of the constrained unified chaotic system. Moreover, the proposed estimator is applied to recover discrete signals such as digital images where computer simulation results are provided to show the effectiveness of the proposed estimation scheme.  相似文献   

18.
In this paper, we focus on the false data injection attacks (FDIAs) on state estimation and corresponding countermeasures for data recovery in smart grid. Without the information about the topology and parameters of systems, two data-driven attacks (DDAs) with noisy measurements are constructed, which can escape the detection from the residue-based bad data detection (BDD) in state estimator. Moreover, in view of the limited energy of adversaries, the feasibility of proposed DDAs is improved, such as more sparse and low-cost DDAs than existing work. In addition, a new algorithm for measurement data recovery is introduced, which converts the data recovery problem against the DDAs into the problem of the low rank approximation with corrupted and noisy measurements. Especially, the online low rank approximate algorithm is employed to improve the real-time performance. Finally, the information on the 14-bus power system is employed to complete the simulation experiments. The results show that the constructed DDAs are stealthy under BBD but can be eliminated by the proposed data recovery algorithms, which improve the resilience of the state estimator against the attacks.  相似文献   

19.
This paper is concerned with a security problem about malicious integrity attacks in state estimation system, in which multiple smart sensors locally measure information and transmit it to a remote fusion estimator though wireless channels. A joint constraint is considered for the attacker behaviour in each channel to keep stealthiness under a residual-based detector on the remote side. In order to degrade the estimator performance, the attacker will maximize the trace of the remote state estimation error covariance which is derived based on Kalman filter theory. It is proved that the optimal linear attack strategy design problem is convex and finally turned into a semi-definite programming problem. In addition, the tendency of attack behaviour on recursive and fixed Kalman filter system is analyzed. Several examples are given to illustrate the theoretical results.  相似文献   

20.
A novel interval observer filtering-based fault diagnosis method for linear discrete-time systems with dual uncertainties is proposed to detect actuator faults. The idea of minimization is adopted to design a fault-free state estimator by merging unknown but bounded and Gaussian disturbances and noises according to the signal average power principle. Using a fault-free state interval and measurement residual of the system, a fault detection indicator is designed based on the residual probability ratio, to achieve dynamic fault detection, isolation and identification. Finally, various simulation examples are provided to demonstrate the accuracy and effectiveness of the proposed method.  相似文献   

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