Iterative learning control applies to systems that repeatedly execute the same finite duration task. The distinguishing feature of this form of control action is that all data generated on a previous execution of the ...
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Iterative learning control applies to systems that repeatedly execute the same finite duration task. The distinguishing feature of this form of control action is that all data generated on a previous execution of the task are available to compute the control action for the subsequent execution. This paper uses the linear repetitive process stability analysis and optimization techniques to design a dynamic controller that, in contrast to previous designs in the repetitive process/2D systems setting, does not require measurement of the state dynamics or observer-based estimation. Supporting experimental validation results are also given.
A novel liveness verification method of systems specified by Petri nets is proposed. The idea utilizes the initial analysis of the Petri net structure in order to detect unique sequences that influence the liveness pr...
A novel liveness verification method of systems specified by Petri nets is proposed. The idea utilizes the initial analysis of the Petri net structure in order to detect unique sequences that influence the liveness property. Although the technique is mainly intended for cyber-physical systems, it is applicable to other Petri net-based designs, including control systems. The presented method was verified empirically with 242 benchmarks, including real-life cyber-physical systems.
In the paper bounded and place invariant-covered Petri nets are considered for the specification of concurrent control systems, especially the control part of cyber-physical systems (CPSs). Although these terms are cl...
In the paper bounded and place invariant-covered Petri nets are considered for the specification of concurrent control systems, especially the control part of cyber-physical systems (CPSs). Although these terms are closely related, verification of the system usually refers to the examination of the boundedness. In this work it is shown that such an analysis might be in some cases insufficient, and additional place invariant-cover is also required. A CPS specified by a bounded, but uncovered Petri net may lead to the improper functionality of the system. The discussed issues are illustrated by a case-study example.
This work presents an innovative learning-based approach to tackle the tracking control problem of Euler-Lagrange multi-agent systems with partially unknown dynamics operating under switching communication topologies....
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ISBN:
(数字)9798350382655
ISBN:
(纸本)9798350382662
This work presents an innovative learning-based approach to tackle the tracking control problem of Euler-Lagrange multi-agent systems with partially unknown dynamics operating under switching communication topologies. The approach leverages a correlation-aware cooperative al-gorithm framework built upon Gaussian process regression, which adeptly captures inter-agent correlations for uncertainty predictions. A standout feature is its exceptional efficiency in deriving the aggregation weights achieved by circumventing the computationally intensive posterior variance calculations. Through Lyapunov stability analysis, the distributed control law ensures bounded tracking errors with high probability. Simulation experiments validate the protocol's efficacy in effectively managing complex scenarios, establishing it as a promising solution for robust tracking control in multi-agent systems characterized by uncertain dynamics and dynamic communication structures.
The article describes the process of construction and testing a floating offshore drilling platform model with focus on cooperation of its diverse subsystems in order to stabilise the position and control the movement...
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The paper deals with the design of an active fault-tolerant control scheme, which is based on the actuator and sensor fault estimator. Thus, the paper starts with the development of such a fault estimation scheme capa...
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The method for constructing joint distribution copula based models is proposed. The copula model parameters are estimated by the method of maximum likelihood which turned out to be effective according to the mean squa...
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This paper addresses an application of a fault-tolerant control to a cubes `packing system. The core issue concerns a control of a set of parallel manipulators which transport cubes from various points to a final stor...
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ISBN:
(数字)9781728177090
ISBN:
(纸本)9781728177106
This paper addresses an application of a fault-tolerant control to a cubes `packing system. The core issue concerns a control of a set of parallel manipulators which transport cubes from various points to a final storage. The main contribution of this paper is an analytical description of a set of manipulators by means of the max-plus algebra equations. The task of these manipulators is a handling of transport of cubes in accordance with a reference schedule. The proposed mathematical approach has to take into consideration both synchronization and choice issues as well as faults. In addition, diagnostics and fault-tolerant control strategy are developed and applied to the system of cubes' packing being considered. All constraints are defined and incorporated into this control strategy. The proposed approach is able to compensate or eliminate the influence of some faults, e.g., delays occurring in the manipulators or reduced velocities of transportation means. Finally, an example exhibiting effectiveness of the proposed control scheme is presented.
Blockchain is an emerging decentralized technology of electronic *** current main consensus protocols are not flexible enough to manage the distributed blockchain nodes to achieve high efficiency of *** practical impl...
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Blockchain is an emerging decentralized technology of electronic *** current main consensus protocols are not flexible enough to manage the distributed blockchain nodes to achieve high efficiency of *** practical implementation,the consensus based on random linear block code(RLBC)is proposed and applied to blockchain voting *** with achieving the record correctness and consistency among all nodes,the consensus method indicates the active and inactive consensus *** ability can assist the management of consensus nodes and restrain the generating of chain *** achieve end-to-end verifiability,cast-or-audit and randomized partial checking(RPC)are used in the proposed *** voter can verify the high probability of correctness in ballot encryption and *** experiments illustrate that the efficiency of proposed consensus is suitable for *** proposed electronic voting scheme is adapted to practical implementation of voting.
Parkinson's disease (PD) is a neurodegenerative condition characterized by frequently changing motor symptoms, necessitating continuous symptom monitoring for more targeted treatment. Classical time series classif...
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Parkinson's disease (PD) is a neurodegenerative condition characterized by frequently changing motor symptoms, necessitating continuous symptom monitoring for more targeted treatment. Classical time series classification and deep learning techniques have demonstrated limited efficacy in monitoring PD symptoms using wearable accelerometer data due to complex PD movement patterns and the small size of available datasets. We investigate InceptionTime and RandOm Convolutional KErnel Transform (ROCKET) as they are promising for PD symptom monitoring. InceptionTime's high learning capacity is well-suited to modeling complex movement patterns, while ROCKET is suited to small datasets. With random search methodology, we identify the highest-scoring InceptionTime architecture and compare its performance to ROCKET with a ridge classifier and a multi-layer perceptron on wrist motion data from PD patients. Our findings indicate that all approaches can learn to estimate tremor severity and bradykinesia presence with moderate performance but encounter challenges in detecting dyskinesia. Among the presented approaches, ROCKET demonstrates higher scores in identifying dyskinesia, whereas InceptionTime exhibits slightly better performance in tremor and bradykinesia estimation. Notably, both methods outperform the multi-layer perceptron. In conclusion, InceptionTime can classify complex wrist motion time series and holds potential for continuous symptom monitoring in PD with further development.
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