In this paper, event-triggered secure fusion estimation is investigated for a multirate multisensor system under linear man-in-the-middle (MITM) attacks and correlated heavy-tailed noises. A dynamic event-triggered mechanism is proposed to reduce measurement information transmission over communication networks with linear MITM attacks. A watermarking strategy is designed to address impact of linear MITM attacks by fully recovering measurement information. An event-triggered local estimator is designed to obtain local estimates under correlated heavy-tailed noises and event-triggered measurements. A distributed fusion estimator is presented to improve estimation accuracy based on sequential fast covariance intersection fusion technique. Sufficient conditions are given to ensure boundedness on estimation error scale matrices of the event-triggered local estimator and the distributed fusion estimator. Simulation and experimental results are given to illustrate validity of the event-triggered secure fusion estimation.

In this paper, a motion control strategy is proposed for a pneumatic flexible manipulator with joint decoupling and a grasped load. A nonlinear extended state observer (ESO) is employed to estimate grasped load disturbances and joint coupling in the pneumatic flexible manipulator. An adaptive tornambe controller (TC) is proposed to provide further compensation and achieve robust precision motion control. A sliding mode tracking differentiator (TD) is designed to arrange a rapid transition process for the pneumatic flexible manipulator. Moreover, stability analyses of the sliding mode TD, the nonlinear ESO and the adaptive TC are conducted by Lyapunov methods. Experimental results are given to illustrate the feasibility of the proposed motion control strategy for the pneumatic flexible manipulator.

In this paper, a practically finite-time active disturbance rejection control (PFTADRC) method is proposed for angle tracking on a 3-degree-of-freedom (3-DOF) parallel mechanism of pneumatic muscle actuators (PMAs) with couplings and disturbances. A coupling characterization is presented to determine whether the couplings are beneficial for the system. Based on this, a practically finite-time controller is designed, where detrimental and beneficial couplings are eliminated and remained, respectively. Moreover, when couplings change, the practically finite-time stability of the system is analyzed and guaranteed. Two Lyapunov criteria of practically finite-time stability are proposed to improve convergence rate of the system. Both the bounded region and the settling time are calculated. Finally, the numerical simulation results and experiment results are presented to illustrate the effectiveness of the proposed method.

In this paper, a fixed-time dynamic surface disturbance rejection control (FTDSDRC) method is proposed to achieve desired angle tracking control performances of the pneumatic soft bending actuator. To achieve active disturbance rejection, a fixed-time disturbance observer (FTDOB) is designed to estimate the unknown disturbance in the pneumatic soft bending actuator. Then, a fixed-time dynamic surface disturbance rejection controller is proposed to achieve desired angle tracking control performances by compensating for the unknown disturbance. Finally, angle tracking control experimental results demonstrate that the proposed FTDSDRC method effective in achieving desired angle tracking control performances.

In this article, a novel error-driven variable gain active disturbance rejection control (ADRC) approach is developed for pneumatic servo system, and the desired performance of trajectory tracking and the disturbance rejection can be guaranteed. The proposed variable gain ADRC includes three parts: 1) variable gain tracking differentiator (TD); 2) variable gain extended state observer (ESO); and 3) variable gain error feedback controller (EFC). The proposed variable gain TD is noise tolerant and possesses a variable gain, which can be dynamically adjusted according to the tracking error, and the performance for tracking the reference signal and extracting its derivative is improved. The variable gain ESO is also equipped with a variable gain driven by estimation errors to improve the estimation performance. Then, the variable gain EFC is further designed to improve control accuracy. Finally, simulations and experimental results are presented to verify the efficiency of the proposed methods.

In this article, an adaptive sliding-mode control strategy is investigated for an inertial reference unit with an adaptive tracking differentiator (TD). A dynamic second-order system is established from a spring-mass-damper system by abstracting and analyzing the inertial reference unit. The adaptive TD is used to reduce overshoot and improve tracking speed for the inertial reference unit by designing adaptive parameters and hyperbolic tangent functions. An adaptive sliding-mode controller is designed to improve response rapidity via adaptive laws and adaptive gains based on an integral terminal sliding-mode function. Effectiveness analysis is shown on error convergence for the adaptive TD and the adaptive sliding-mode controller based on Lyapunov methods. A series of experiments are given to illustrate the effectiveness of the adaptive sliding-mode control strategy in the inertial reference unit.

For wireless cyber–physical systems (CPSs) suffering jamming attacks, an optimal resilient control method is proposed through a novel cross-layer dynamic game structure in this article. To confirm to practical conditions of the cyber-layer, incomplete communication information is taken into consideration, and a Bayesian Stackelberg game approach is utilized to model interactions between a smart jammer and a cyber-user. Then, an$H_{\infty }$optimal resilient controller is studied for the closed-loop system with jam-induced packet losses and external disturbance in the sense of physical layer. With assumptions that the smart jammer has abilities of decoding system inputs and states, the changes of the jamming strategy are studied, and a coupled design between cyber and physical layers is presented with an algorithm to depict the dynamic variations of the CPSs. Moreover, the convergence of the proposed algorithm is also discussed. To validate the advantages of the proposed methods, a numerical simulation is performed in the end.

In this article, event-triggered distributed fusion is investigated for a multirate multisensor system subject to heavy-tailed noises under packet dropout. The heavy-tailed noises are modeled by a multivariate$t$-distribution for the multirate multisensor system. An event-triggered local estimator is designed to gain local estimates with packet dropout in communication networks. An event-triggered distributed fusion algorithm is proposed by sequential fast covariance intersection (SFCI) fusion technology. Sufficient conditions on the boundedness of the estimation error scale matrices are given for the event-triggered local estimator and distributed fusion. Finally, numerical simulation is put forward to indicate validity of the presented event-triggered local estimator and distributed fusion.

In this work, we develop a novel abrupt-jump detection algorithm for seismic signal deconvolution. This new method significantly suppresses the effect of side lobes. It begins with transforming a seismic trace to a series of innovations with a Kalman filter and then estimates the likelihood ratios of the reflectivity impulses from the innovations. Secondly, it modifies the likelihood ratios by imposing an additional punishment on its asymmetry. Therefore, the likelihood ratios induced by the side lobes are highly suppressed. Hence the reflectivity impulses recovered from the modified likelihood ratios are less effected by the side lobes, leading to significantly enhanced resolution. The efficacy of the proposed method is numerically validated on a synthetic and a field dataset. The experimental results show that the proposed scheme is efficient and practical in enhancing signal quality of seismograms than the original likelihood-ratio-based abrupt-jump detection.

In this paper, a finite-time control is proposed based on an extended state observer (ESO) for a pneumatic cylinder servo system. First, an ESO is designed to estimate the friction and varying loads using a super-twisting algorithm. Then, a finite-time controller is designed using a power integrator technology to ensure stability and improve control performances of the pneumatic cylinder servo system. Furthermore, both the effectiveness of the proposed ESO and the finite-time convergence of the closed-loop system are accordingly proven. Finally, experimental results demonstrate that both the control precision and the response rapidity are improved by applying the developed techniques.

This article proposes an innovative scheme for recovering sparse reflectivity series from uniformly quantized seismic signals. In this scheme, the statistically less affected impulses by the quantization error are assigned higher weights than the ones with a larger error. First, the orthogonal matching pursuit (OMP) algorithm is applied on a quantized seismic trace to obtain a set of conservative estimates of the reflectivity impulses. Second, the quantization error is formulated as a systematic uncertainty within a neighborhood of the obtained conservative estimates from the OMP. Finally, a robust worst case (RWC) deconvolution method is developed to recover an improved estimate of the reflectivity impulses. The proposed scheme significantly increases the robustness and enhances the recovered reflectivity impulses obtained by the OMP algorithm. This is substantiated by experiments on both synthetic and real seismic data. Specifically, the falsely or overly estimated impulses are significantly suppressed, and the robustness to the change of the quantization interval is enhanced.

In this paper, a generalized nonlinear extended state observer is applied to an integral sliding mode (ISM) tracking control method for a pneumatic cylinder servo system with varying loads. The observer is established to estimate the total disturbance and its derivative for the system. An ISM controller is designed to ensure control performances of the system. Both finite-time convergence of the observer and finite-time stabilization of the closed-loop system are realized using Lyapunov's stability theory. Lastly, experimental results demonstrate that control precision and response rapidity are improved using the proposed method.

This paper considers trajectory tracking control for a one-degree of freedom (DoF) manipulator system driven by pneumatic artificial muscles. A switched sliding mode controller is accordingly designed. In the proposed scheme, a novel extended state observer based on a generalized super-twisting algorithm is first designed to deal with internal uncertainties and external disturbances in the one-DoF manipulator system. Second, the finite time convergence of the closed-loop system with the proposed sliding mode technique is analyzed. Lastly, some experimental results are presented to show the validity and advantages of the proposed approach.