Dear Editor,The letter deals with the distributed state and fault estimation of the whole physical layer for cyber-physical systems(CPSs) when the cyber layer suffers from DoS attacks. With the advancement of embedded...
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Dear Editor,The letter deals with the distributed state and fault estimation of the whole physical layer for cyber-physical systems(CPSs) when the cyber layer suffers from DoS attacks. With the advancement of embedded computing, communication and related hardware technologies, CPSs have attracted extensive attention and have been widely used in power system, traffic network, refrigeration system and other fields.
This paper proposes an event-triggered stochastic model predictive control for discrete-time linear time-invariant(LTI) systems under additive stochastic disturbances. It first constructs a probabilistic invariant set...
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This paper proposes an event-triggered stochastic model predictive control for discrete-time linear time-invariant(LTI) systems under additive stochastic disturbances. It first constructs a probabilistic invariant set and a probabilistic reachable set based on the priori knowledge of system *** with enhanced robust tubes, the chance constraints are then formulated into a deterministic form. To alleviate the online computational burden, a novel event-triggered stochastic model predictive control is developed, where the triggering condition is designed based on the past and future optimal trajectory tracking errors in order to achieve a good trade-off between system resource utilization and control performance. Two triggering parameters σ and γ are used to adjust the frequency of solving the optimization problem. The probabilistic feasibility and stability of the system under the event-triggered mechanism are also examined. Finally, numerical studies on the control of a heating, ventilation, and air conditioning(HVAC) system confirm the efficacy of the proposed control.
antagonistic interactions,data security and transient-steady state performance of the system are two key *** ensure data security,an intermittent privacy preservation(IPP)mechanism is proposed for the first time.A nov...
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antagonistic interactions,data security and transient-steady state performance of the system are two key *** ensure data security,an intermittent privacy preservation(IPP)mechanism is proposed for the first time.A novel setting time initial mask function and a novel intermittent mask function are *** can implement intermittent preservation for the system according to actual requirements,which solves the irreversibility problem after conventional mask disappears and balances control accuracy and system *** ensure transient-steady state performance,a novel error transformation function(ETF)is proposed and integrated into the predefined-time prescribed performance control *** to conventional hyperbolic tangent type ETFs,the proposed ETF can improve the convergence accuracy of errors under the same ***,a unified model of the air-sea HMASs is established,which improves the model accuracy compared with the simplified ***,the proposed IPP security control strategy is applied to the air-sea delivery mission to verify its feasibility and effectiveness.
In this study, we consider a single-link flexible manipulator in the presence of an unknown Bouc-Wen type of hysteresis and intermittent actuator faults. First, an inverse hysteresis dynamics model is introduced, and ...
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In this study, we consider a single-link flexible manipulator in the presence of an unknown Bouc-Wen type of hysteresis and intermittent actuator faults. First, an inverse hysteresis dynamics model is introduced, and then the control input is divided into an expected input and an error compensator. Second,a novel adaptive neural network-based control scheme is proposed to cancel the unknown input hysteresis. Subsequently,by modifying the adaptive laws and local control laws, a fault-tolerant control strategy is applied to address uncertain intermittent actuator faults in a flexible manipulator system. Through the direct Lyapunov theory, the proposed scheme allows the state errors to asymptotically converge to a specified interval. Finally,the effectiveness of the proposed scheme is verified through numerical simulations and experiments.
This paper considers the value iteration algorithms of stochastic zero-sum linear quadratic games with unkown ***-policy and off-policy learning algorithms are developed to solve the stochastic zero-sum games,where th...
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This paper considers the value iteration algorithms of stochastic zero-sum linear quadratic games with unkown ***-policy and off-policy learning algorithms are developed to solve the stochastic zero-sum games,where the system dynamics is not *** analyzing the value function iterations,the convergence of the model-based algorithm is *** equivalence of several types of value iteration algorithms is *** effectiveness of model-free algorithms is demonstrated by a numerical example.
Out-of-step oscillation is a very destructive physical phenomenon in power system, which could directly cause big blackout accompanied by serious sociology-economic impacts. Out-of-step splitting control is an indispe...
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Out-of-step oscillation is a very destructive physical phenomenon in power system, which could directly cause big blackout accompanied by serious sociology-economic impacts. Out-of-step splitting control is an indispensable means, which could protect the system from major shocks of out-of-step oscillation. After years of development, it has achieved certain amount of research results. Have the existing methods been able to meet the requirements of out-of-step splitting? What improvements are needed? Under this background, this review is written. It combs the development of out-of-step splitting control technologies and analyzes the technical routes and characteristics of different methods. It points out the contradiction between rapidity and optimality is the biggest technical problem, existing in both the traditional local measurement based out-of-step splitting protection and the wide-area information based out-of-step splitting protection. It further points out that the advantages of the two types of protections can be combined with the unique physical characteristics of the out-of-step center to form a more advantageous splitting strategy. Besides, facing the fact of large-scale renewable energy access to power grid in recent years, this review also analyzes the challenges brought by it and provides some corresponding suggestions. It is hoped to provide some guidance for the subsequent research work.
Swift perception of interaction forces is a crucial skill required for legged robots to ensure safe human-robot interaction and dynamic contact ***-based interactive force is widely applied due to its outstanding cros...
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Swift perception of interaction forces is a crucial skill required for legged robots to ensure safe human-robot interaction and dynamic contact ***-based interactive force is widely applied due to its outstanding cross-platform *** this paper,we present a novel interactive force observer,which possesses superior dynamic tracking *** propose a dynamic cutoff frequency configuration method to replace the conventional fixed cutoff frequency setting in the traditional momentum-based observer(MBO).This method achieves a balance between rapid tracking and noise ***,to mitigate the phase lag introduced by the low-pass filtering,we cascaded a Newton Predictor(NP)after MBO,which features simple computation and *** precision analysis of this method has been *** conducted extensive experiments on the point-foot biped robot BRAVER to validate the performance of the proposed algorithm in both simulation and physical prototype.
Fast charging of lithium-ion batteries (LIBs) is a key technology for the popularization of electric vehicles. However, regardless of physical constraints, high-rate charging will accelerate the decline of battery cap...
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Real-time systems are widely implemented in the Internet of Things(IoT) and safety-critical systems, both of which have generated enormous social value. Aiming at the classic schedulability analysis problem in real-ti...
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Real-time systems are widely implemented in the Internet of Things(IoT) and safety-critical systems, both of which have generated enormous social value. Aiming at the classic schedulability analysis problem in real-time systems, we proposed an exact Boolean analysis based on interference(EBAI) for schedulability analysis in real-time systems. EBAI is based on worst-case interference time(WCIT), which considers both the release jitter and blocking time of the task. We improved the efficiency of the three existing tests and provided a comprehensive summary of related research results in the field. Abundant experiments were conducted to compare EBAI with other related results. Our evaluation showed that in certain cases, the runtime gain achieved using our analysis method may exceed 73% compared to the stateof-the-art schedulability test. Furthermore, the benefits obtained from our tests grew with the number of tasks, reaching a level suitable for practical application. EBAI is oriented to the five-tuple real-time task model with stronger expression ability and possesses a low runtime overhead. These characteristics make it applicable in various real-time systems such as spacecraft, autonomous vehicles, industrial robots, and traffic command systems.
In this paper, a command filter-based adaptive fuzzy predefined-time event-triggered tracking control problem is investigated for uncertain nonlinear systems with time-varying full-state constraints. By designing a sl...
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In this paper, a command filter-based adaptive fuzzy predefined-time event-triggered tracking control problem is investigated for uncertain nonlinear systems with time-varying full-state constraints. By designing a sliding mode differentiator, the inherent computational complexity problem within the predefined-time backstepping framework is solved. Different from the existing command filter-based finite-time and fixed-time control strategies that the convergence time of the filtering error is adjusted through the system initial value or numerous parameters, a novel command filtering error compensation method is presented,which tunes one control parameter to make the filtering error converge in the predefined time, thereby reducing the complexity of design and analysis of processing the filtering error. Then, an improved event-triggered mechanism(ETM) that builds upon the switching threshold strategy, in which an inverse cotangent function is designed to replace the residual term of the ETM,is proposed to gradually release the controller's dependence on the residual term with increasing time. Furthermore, a tan-type nonlinear mapping technique is applied to tackle the time-varying full-state constraints problem. By the predefined-time stability theory, all signals in the uncertain nonlinear systems exhibit predefined-time stability. Finally, the feasibility of the proposed algorithm is substantiated through two simulation results.
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