Recursive identification of structured multivariate models is known to be difficult due to the general non-convexity of the likelihood function. In this work, we propose a recursive multivariate weighted null-space fi...
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Recursive identification of structured multivariate models is known to be difficult due to the general non-convexity of the likelihood function. In this work, we propose a recursive multivariate weighted null-space fitting method for identification of structured multivariate models. The proposed method first uses recursive least squares to estimate a high order non-parametric model, then a parametric model is obtained through weighted least squares from the non-parametric model. In this way, the method avoids directly optimizing a non-convex likelihood function and has guaranteed global convergency. Moreover, the proposed method is flexible in model structures and has the same finite sample performance as its off-line counterpart. We use simulation examples to illustrate the performance.
This paper provides some sufficient conditions to achieve asymptotic stability of switched systems under spatiotemporal specifications via a state-dependent switching law. A common finite-time barrier function, multip...
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This paper provides some sufficient conditions to achieve asymptotic stability of switched systems under spatiotemporal specifications via a state-dependent switching law. A common finite-time barrier function, multiple barrier functions and multiple Lyapunov functions are merged as a tool for analyzing the asymptotic stability of a switched nonlinear system under spatio-temporal specifications. Finally, a numerical example is presented to demonstrate the effectiveness of our proposed method.
This paper proposes a multi-frequency controller design scheme for Markov jump systems (MJSs) based on the self-triggered strategy in a resource-aware way. Firstly, a derandomization technique is introduced to make su...
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This paper proposes a multi-frequency controller design scheme for Markov jump systems (MJSs) based on the self-triggered strategy in a resource-aware way. Firstly, a derandomization technique is introduced to make sure the transition probability information is included in the finite frequency specification analysis. Then, a self-triggered policy is developed to update the control input of the system via the history measurement. Finally, sufficient conditions are deduced that guarantee the multiple range frequency performances and the reduction of computation and communication occupation for the controlled MJSs, simultanously. The cart- spring system is employed to illustrate the effectiveness of the proposed approach.
In this paper, we consider a stochastic distributed nonconvex optimization problem with the cost function being distributed over n agents having access only to zeroth-order (ZO) information of the cost. This problem h...
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For a stratospheric airship under internal and external uncertainties, controller strategies with robust integral sign of the error (RISE) are proposed for asymptotic trajectory tracking control. Specifically, a fully...
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Many control tasks can be formulated as tracking problems of a known or unknown reference signal. examples are motion compensation in collaborative robotics, the synchronisation of oscillations for power systems or th...
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Many control tasks can be formulated as tracking problems of a known or unknown reference signal. examples are motion compensation in collaborative robotics, the synchronisation of oscillations for power systems or the reference tracking of recipes in chemical process operation. Both the tracking performance and the stability of the closed-loop system depend strongly on two factors: Firstly, they depend on whether the future reference signal required for tracking is known, and secondly, whether the system can track the reference at all. This paper shows how to use machine learning, i.e. Gaussian processes, to learn a reference from (noisy) data while guaranteeing trackability of the modified desired reference predictions within the framework of model predictive control. Guarantees are provided by adjusting the hyperparameters via a constrained optimisation. Two specific scenarios, i.e. asymptotically constant and periodic REFERENCES, are discussed.
This paper investigates the high-speed train rescheduling (HSTR) problem under a partial station blockage and proposes an efficient problem-specific strengthen elitist genetic algorithm (PS-SEGA) for HSTR. An HSTR mod...
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Evacuation of crowds in a corridor with only one exit has been considered in this paper where distributed controllers have been constructed to regulate the crowd’s evacuation speed so that stampede tragedy can be avo...
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Evacuation of crowds in a corridor with only one exit has been considered in this paper where distributed controllers have been constructed to regulate the crowd’s evacuation speed so that stampede tragedy can be avoided. Macroscopic model for crowds of pedestrians has been firstly derived based on inspiration of LWR (Lighthill-Whitham and Richards) model and Greenshields model from traffic system where finite volume method has been introduced to simplify the obtained PDEs into finite ODEs. Distributed evacuation controllers have been constructed based on inspiration of multi-agent system and stability analysis of obtained closed-loop system has been simplified to linear system with the delicate controllers proposed. Comparisons between distributed evacuation controllers and previous evacuation controllers have also been presented to show the advantages and disadvantages of different controllers under different initial density of crowds so that tragedy of crowd stampede can be effectively avoided with appropriate selection of different controllers.
Reaction wheels as the main actuators for attitude control of spacecraft are very prone to malfunction,which may significantly degrade the performance of the spacecraft attitude control *** this paper a novel active f...
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Reaction wheels as the main actuators for attitude control of spacecraft are very prone to malfunction,which may significantly degrade the performance of the spacecraft attitude control *** this paper a novel active fault-tolerant control scheme is proposed to react the reaction wheel faults actively.A combined observer is first designed to detect the reaction wheel faults,by combining a traditional adaptive Luenberger observer and a newly designed neural network（NN） *** inherits the advantages of the low computational cost of the Luenberger observer and the high performance of the NN ***,a fault isolation scheme is given to locate ***,an adaptive fault-tolerant controller is designed to achieve graceful performance degradation under reaction wheel faults,based on the diagnosis results of the combined observer and the judgment results of the fault isolation ***,simulation results show that the proposed scheme is able to achieve precise fault diagnosis and fault-tolerant control of spacecraft in the presence of external interference and limited computation.
In this paper, a novel robust back-stepping fault- tolerant control scheme is proposed, which enables hypersonic reentry vehicles with model uncertainties to accurately track the attitude commands under the condition ...
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ISBN:
(数字)9781728180250
ISBN:
(纸本)9781728180267
In this paper, a novel robust back-stepping fault- tolerant control scheme is proposed, which enables hypersonic reentry vehicles with model uncertainties to accurately track the attitude commands under the condition of both unknown actuator faults and external disturbances. Firstly, a control-oriented hypersonic reentry vehicle model is established on the basis of regarding three factors mentioned above as lumped disturbance. Then, a fixed-time observer is used to achieve the fixed-time lumped disturbance estimation. Based on the disturbance observer and back-stepping technology, the proposed fault-tolerant control laws are designed to ensure control performance. Meanwhile, the “differential explosion” problem is solved by the sigmoid function-based tracking differentiator. Finally, the stability and effectiveness of the proposed controller are verified from theoretical analysis and extensive numerical simulations respectively.
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