Dear editor,The uncertain input delay is frequently encountered in engineering control systems. Adaptation is indispensable when the uncertain input delay is significant. In existing delayadaptive controllers [1–6], ...
Dear editor,The uncertain input delay is frequently encountered in engineering control systems. Adaptation is indispensable when the uncertain input delay is significant. In existing delayadaptive controllers [1–6], the actuator state must be measured to achieve global stability. Recently, a logic-based switching delay-adaptive state-feedback controller [7] was proposed to realize global stability without measuring the actuator state.
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.
Deep learning has revolutionized the field of artificial *** on the statistical correlations uncovered by deep learning-based methods,computer vision tasks,such as autonomous driving and robotics,are growing *** being...
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Deep learning has revolutionized the field of artificial *** on the statistical correlations uncovered by deep learning-based methods,computer vision tasks,such as autonomous driving and robotics,are growing *** being the basis of deep learning,such correlation strongly depends on the distribution of the original data and is susceptible to uncontrolled *** the guidance of prior knowledge,statistical correlations alone cannot correctly reflect the essential causal relations and may even introduce spurious *** a result,researchers are now trying to enhance deep learningbased methods with causal *** theory can model the intrinsic causal structure unaffected by data bias and effectively avoids spurious *** paper aims to comprehensively review the existing causal methods in typical vision and visionlanguage tasks such as semantic segmentation,object detection,and image *** advantages of causality and the approaches for building causal paradigms will be *** roadmaps are also proposed,including facilitating the development of causal theory and its application in other complex scenarios and systems.
This work considers the localizability of multi-agent systems based on local bearing measurement. A novel prescribed-time orientation estimation algorithm is first proposed to guarantee that the local reference frame ...
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Deep reinforcement learning (DRL) has been recognized as a powerful tool in quantum physics, where DRL's reward design is nontrivial but crucial for quantum control tasks. To address the problem of over-reliance o...
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Deep reinforcement learning (DRL) has been recognized as a powerful tool in quantum physics, where DRL's reward design is nontrivial but crucial for quantum control tasks. To address the problem of over-reliance on human empirical knowledge to design DRL's rewards, we propose a DRL with a novel reward paradigm designed by the learning process information (DRL-LPI), where the learning process information (LPI) comprises the state information and the experiences. In DRL-LPI, the state information after being classified by a fidelity threshold, and the experiences are first stored simultaneously in the respective sequences, and this process is repeated until a similar-segment ends. Then, the stored state information is converted to the real value and used to design the reward value by applying a self-Amplitude function. Next, the designed reward values are integrated with the stored experiences to compose transitions for DRL's training. Through comparisons to five representative reward schemes, the proposed DRL-LPI is evaluated on two typical quantum control tasks, i.e., the spin-(1/2) quantum state control and many-coupled qubits state control, and the experimental results show the superior learning efficiency and control performance of the proposed *** results show that DRL-LPI exhibits the ability to learn the control strategy with few control actions compared to stochastic gradient descent (SGD) and genetic algorithm (GA). Impact Statement-Over the past few years, quantum machine learning has received growing attention. In particular, reinforcement learning (RL) and quantum physics have gradually intersected, and one representative aspect is that some impressive results have been achieved regarding the application of RL algorithms in quantum system tasks. Despite some advances, the full potential of RL remains massively unexplored in quantum physics. A major limitation is howto reward the learning *** previousworks adopted hand-designed methods, wh
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.
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.
Purpose-The elderly service industry is emerging in *** Chinese government introduced a series of policies to guide elderly service enterprises to improve their service *** study explores novel differentiated subsidy ...
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Purpose-The elderly service industry is emerging in *** Chinese government introduced a series of policies to guide elderly service enterprises to improve their service *** study explores novel differentiated subsidy strategies that not only promote the improvement of service quality in elderly service enterprises but also alleviate the financial burden on the ***/methodology/approach-Evolutionary game and Hotelling models are employed to investigate this ***,a Hotelling model that considers consumer word-of-mouth preferences is ***,an evolutionary game model between local governments and enterprises is constructed,and the evolutionary stable strategies of both parties are ***,simulation experiments are ***-The findings indicate that local government decisions have a significant influence on the behavior of elderly service *** the proportion of local governments opting for subsidy strategies helps incentivize elderly service enterprises to improve their service ***,providing differentiated subsidies based on the preferences of the customer base of elderly service enterprises can encourage service quality improvement while reducing government *** findings offer valuable insights into the design of government subsidy ***/value-Compared with previous research,this study examines the role of consumer preferences in a differentiated subsidy *** enriches the authors’understanding of the field by incorporating neglected aspects of consumer preferences in the context of the emerging elderly service industry.
While coupons that can be redeemed only in online channels have been issued by e-commerce platforms for decades, a new type of platform’s coupons, i.e., omnichannel coupons, which can be redeemed in both online and s...
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While coupons that can be redeemed only in online channels have been issued by e-commerce platforms for decades, a new type of platform’s coupons, i.e., omnichannel coupons, which can be redeemed in both online and store channels, is gaining popularity with the rise of the omnichannel retail mode. It is interesting to explore the conditions under which omnichannel coupons are more advantageous to platforms and multichannel suppliers that sell products through platforms and physical stores. Two game models are developed in two cases where an e-commerce platform offers single channel coupons or omnichannel coupons for a multichannel supplier. Two scenarios are considered: one in which a consumer’s valuation of a product that fits his or her need is homogeneous and another in which the valuation is heterogeneous. Equilibrium outcomes show that under the homogeneous scenario, the product price and coupon face value in both coupon modes increase with the product’s fit probability when the cross-selling revenue is high, while decrease with the product’s fit probability when the cross-selling revenue is low. However, under the heterogeneous scenario, the price in both modes increases with the product’s fit probability only when the supplier’s loss from returns is low and the cross-selling revenue is high, and the coupon face value always decreases with the product’s fit probability. Compared with single channel coupons, omnichannel coupons may lead to a higher product price under certain conditions. Furthermore, omnichannel coupons can lead to higher total demand and benefit both the platform and the supplier if and only if the product’s fit probability is low and the supplier’s loss from returns is high. An extension shows that the platform’s preference for omnichannel coupons is weakened when the supplier offers a partial refund policy.
Dear Editor,In this letter,the multi-objective optimal control problem of nonlinear discrete-time systems is investigated.A data-driven policy gradient algorithm is proposed in which the action-state value function is...
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Dear Editor,In this letter,the multi-objective optimal control problem of nonlinear discrete-time systems is investigated.A data-driven policy gradient algorithm is proposed in which the action-state value function is used to evaluate the *** the policy improvement process,the policy gradient based method is employed.
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