In this tutorial paper, we explore the field of quantized feedback control, which has gained significant attention due to the growing prevalence of networked control systems. These systems require the transmission of ...
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In this tutorial paper, we explore the field of quantized feedback control, which has gained significant attention due to the growing prevalence of networked control systems. These systems require the transmission of feedback information, such as measurements and control signals, over digital networks, presenting novel challenges in estimation and control design. Our examination encompasses various topics, including the minimal information needed for effective feedback control, the design of quantizers, strategies for quantized control design and estimation,achieving consensus control with quantized data, and the pursuit of high-precision tracking using quantized measurements.
In this paper, the containment control problem in nonlinear multi-agent systems(NMASs) under denial-of-service(DoS) attacks is addressed. Firstly, a prediction model is obtained using the broad learning technique to t...
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In this paper, the containment control problem in nonlinear multi-agent systems(NMASs) under denial-of-service(DoS) attacks is addressed. Firstly, a prediction model is obtained using the broad learning technique to train historical data generated by the system offline without DoS attacks. Secondly, the dynamic linearization method is used to obtain the equivalent linearization model of NMASs. Then, a novel model-free adaptive predictive control(MFAPC) framework based on historical and online data generated by the system is proposed, which combines the trained prediction model with the model-free adaptive control method. The development of the MFAPC method motivates a much simpler robust predictive control solution that is convenient to use in the case of DoS attacks. Meanwhile, the MFAPC algorithm provides a unified predictive framework for solving consensus tracking and containment control problems. The boundedness of the containment error can be proven by using the contraction mapping principle and the mathematical induction method. Finally, the proposed MFAPC is assessed through comparative experiments.
In this paper,the authors consider how to design defensive countermeasures against DoS attacks for remote state estimation of multiprocess *** each system,a sensor will measure its state and transmits the data packets...
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In this paper,the authors consider how to design defensive countermeasures against DoS attacks for remote state estimation of multiprocess *** each system,a sensor will measure its state and transmits the data packets through an unreliable channel which is vulnerable to be jammed by an *** limited communication bandwidth,only a subset of sensors are allowed for data transmission,and how to select the optimal one to maximize the accuracy of remote state estimation is the focus of the proposed *** authors first formulate this problem as a Markov decision process and investigate the existence of optimal ***,the authors demonstrate the piecewise monotonicity structure of optimal *** the difficulty of obtaining an optimal policy of large-scale problems,the authors develop a suboptimal heuristic policy based on the aforementioned policy structure and Whittle’s ***,a closed form of the indices is derived in order to reduce implementation complexity of proposed scheduling policy and numerical examples are provided to illustrate the proposed developed results.
Linear temporal logic(LTL)is an intuitive and expressive language to specify complex control tasks,and how to design an efficient control strategy for LTL specification is still a *** this paper,we implement the dynam...
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Linear temporal logic(LTL)is an intuitive and expressive language to specify complex control tasks,and how to design an efficient control strategy for LTL specification is still a *** this paper,we implement the dynamic quantization technique to propose a novel hierarchical control strategy for nonlinear control systems under LTL *** on the regions of interest involved in the LTL formula,an accepting path is derived first to provide a high-level solution for the controller synthesis ***,we develop a dynamic quantization based approach to verify the realization of the accepting *** realization verification results in the necessity of the controller design and a sequence of quantization regions for the controller ***,the techniques of dynamic quantization and abstraction-based control are combined together to establish the local-to-global control *** abstraction construction and controller design are local and dynamic,thereby resulting in the potential reduction of the computational *** each quantization region can be considered locally and individually,the proposed hierarchical mechanism is more efficient and can solve much larger problems than many existing ***,the proposed control strategy is illustrated via two examples from the path planning and tracking problems of mobile robots.
This paper proposes a novel impulsive thrust strategy guided by optimal continuous thrust strategy to address two-player orbital pursuit-evasion game under impulsive thrust *** strategy seeks to enhance the interpreta...
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This paper proposes a novel impulsive thrust strategy guided by optimal continuous thrust strategy to address two-player orbital pursuit-evasion game under impulsive thrust *** strategy seeks to enhance the interpretability of impulsive thrust strategy by integrating it within the framework of differential game in traditional continuous ***,this paper introduces an impulse-like constraint,with periodical changes in thrust amplitude,to characterize the impulsive thrust ***,the game with the impulse-like constraint is converted into the two-point boundary value problem,which is solved by the combined shooting and deep learning method proposed in this *** learning and numerical optimization are employed to obtain the guesses for unknown terminal adjoint variables and the game terminal ***,the accurate values are solved by the shooting method to yield the optimal continuous thrust strategy with the impulse-like ***,the shooting method is iteratively employed at each impulse decision moment to derive the impulsive thrust strategy guided by the optimal continuous thrust *** examples demonstrate the convergence of the combined shooting and deep learning method,even if the strongly nonlinear impulse-like constraint is *** effect of the impulsive thrust strategy guided by the optimal continuous thrust strategy is also discussed.
This paper mainly addresses control problems of strict-feedback systems(SFSs)with increasing *** with the commonly-considered SFSs where the subsystems have the same dimension,we aim to handle more complex cases,i.e.,...
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This paper mainly addresses control problems of strict-feedback systems(SFSs)with increasing *** with the commonly-considered SFSs where the subsystems have the same dimension,we aim to handle more complex cases,i.e.,the subsystems in the considered SFSs are assumed to have increasing *** transforming the systems into highorder fully-actuated system(HOFAS)models,the stabilizing controllers can be directly *** first-order SFSs,secondorder and high-order SFSs are also considered.
This work investigates the implementation of distributed prescribed-time neural network(NN)control for nonlinear multiagent systems(MASs)using a dynamic memory event-triggered mechanism(DMETM).First,it introduces a co...
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This work investigates the implementation of distributed prescribed-time neural network(NN)control for nonlinear multiagent systems(MASs)using a dynamic memory event-triggered mechanism(DMETM).First,it introduces a composite learning technique in NN *** method leverages the prediction error within the NN update law to enhance the accuracy of the unknown nonlinearity ***,by introducing a time-varying transformation,the study establishes a distributed prescribed-time control *** notable feature of this algorithm is its ability to predetermine the convergence time independently of initial conditions or control ***,the DMETM is established to reduce the actuation frequency of the *** the conventional memoryless dynamic event-triggered mechanism,the DMETM incorporates a memory term to further increase triggering *** a distributed estimator for the leader,the DMETM-based NN prescribed-time controller is designed in a fully distributed manner,which guarantees that all signals in the closed-loop system remain bounded within the prescribed ***,simulation results are presented to validate the effectiveness of the proposed algorithm.
Nowadays,there has been an increasing focus on integrated flight propulsion control and the inlet-exhaust design for the aero-propulsion *** component-level models are inadequate due to installed performance deviation...
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Nowadays,there has been an increasing focus on integrated flight propulsion control and the inlet-exhaust design for the aero-propulsion *** component-level models are inadequate due to installed performance deviations and mismatches between the real engine and the model,failing to meet the accuracy requirements of supersonic *** paper establishes a quasi-one-dimensional model for the inlet-exhaust system and conducts experimental ***,a mechanism-data fusion adaptive modeling scheme using an Extreme Learning Machine based on the Salp Swarm Algorithm(SSA-ELM)is *** study reveals the inlet model’s efficacy in reflecting installed performance,flow matching,and mitigating pressure distortion,while the nozzle model accurately predicts flow coefficients and thrust coefficients,and identifies various operational *** model’s output closely aligns with typical experimental *** combining offline optimization and online adaptive correction,the mechanismdata fusion adaptive model substantially reduces output errors during regular flights and varying levels of degradation,and effectively handles gradual degradation within a single flight ***,the mechanism-data fusion adaptive model holistically addresses total pressure errors within the inlet-exhaust system and normal shock location *** approach significantly curbs performance deviations in supersonic *** example,at Ma=2.0,the system error impressively drops from 34.17%to merely 6.54%,while errors for other flight conditions consistently stay below the 2.95%*** findings underscore the clear superiority of the proposed method.
Thrust estimation is a significant part of aeroengine thrust control *** traditional estimation methods are either low in accuracy or large in *** further improve the estimation effect,a thrust estimator based on Mult...
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Thrust estimation is a significant part of aeroengine thrust control *** traditional estimation methods are either low in accuracy or large in *** further improve the estimation effect,a thrust estimator based on Multi-layer Residual Temporal Convolutional Network(M-RTCN)is *** solve the problem of dead Rectified Linear Unit(ReLU),the proposed method uses the Gaussian Error Linear Unit(GELU)activation function instead of ReLU in residual *** the overall architecture of the multi-layer convolutional network is adjusted by using residual connections,so that the network thrust estimation effect and memory consumption are further ***,the comparison with seven other methods shows that the proposed method has the advantages of higher estimation accuracy and faster convergence ***,six neural network models are deployed in the embedded controller of the micro-turbojet *** Hardware-in-the-Loop(HIL)testing results demonstrate the superiority of M-RTCN in terms of estimation accuracy,memory occupation and running ***,an ignition verification is conducted to confirm the expected thrust estimation and real-time performance.
This paper presents a human-like motion decision-making method for unmanned aerial vehicles(UAVs)navigating in trap *** proposed a space partitioning method based on sampling and consistency control to conduct a preli...
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This paper presents a human-like motion decision-making method for unmanned aerial vehicles(UAVs)navigating in trap *** proposed a space partitioning method based on sampling and consistency control to conduct a preliminary analysis of the indoor environment based on architectural *** method reduces the dimensionality of the path planning problem,thereby enhancing the ***,we designed a target-switching logic for the dynamic window *** improvement endows the UAV with the capability of both real-time obstacle avoidance and global navigation,enhancing the efficiency of the UAV in flying to task spots ***,by applying human-like methods of batch distance perception and obstacle perception to this scheme,we have further enhanced the robustness and efficiency of path ***,considering the scenario of high-rise fire rescue,we conducted simulation *** demonstrates that our scheme enhances the efficiency and robustness of path planning.
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