In this paper, a novel non-monotonic Lyapunov-Krasovskii functional approach is proposed to deal with the stability analysis and stabilization problem of linear discrete time-delay systems. This technique is utilized ...
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In this paper, a novel non-monotonic Lyapunov-Krasovskii functional approach is proposed to deal with the stability analysis and stabilization problem of linear discrete time-delay systems. This technique is utilized to relax the monotonic requirement of the Lyapunov-Krasovskii theorem. In this regard, the Lyapunov-Krasovskii functional is allowed to increase in a few steps, while being forced to be overall decreasing. As a result, it relays on a larger class of Lyapunov-Krasovskii functionals to provide stability of a state-delay system. To this end, using the non-monotonic Lyapunov-Krasovskii theorem, new sufficient conditions are derived regarding linear matrix inequalities(LMIs)to study the global asymptotic stability of state-delay ***, new stabilization conditions are also proposed for time-delay systems in this article. Both simulation and experimental results on a p H neutralizing process are provided to demonstrate the efficacy of the proposed method.
An indirect iterative learning control law is proposed for a class of continuous-time batch processes with time-varying uncertainties, input delay, and disturbances. First, by designing a predictor based on a state ob...
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ISBN:
(数字)9789887581598
ISBN:
(纸本)9798331540845
An indirect iterative learning control law is proposed for a class of continuous-time batch processes with time-varying uncertainties, input delay, and disturbances. First, by designing a predictor based on a state observer we are able to estimate the future state and compensate for the input delay. Then, based on the estimated state we design a robust
$H$
∞ controller in the presence of time-varying uncertainties and load disturbances. Additionally, the differential repetitive process setting for the design of the iterative learning control scheme is applied and hence the convergence of the tracking error in trial-to-trial direction occurs. Finally, the simulation results verify the new method's effectiveness.
Trajectory prediction is a crucial task of autonomous driving and benefits vehicles travel safely in complex traffic environments. However, most existing trajectory prediction methods suffer from low accuracy issue du...
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This paper designs an impulsive controller for nonlinear positive systems with uncertain parameters and input saturation constraints. To address the issue of modeling errors caused by parameter uncertainties, system m...
This paper designs an impulsive controller for nonlinear positive systems with uncertain parameters and input saturation constraints. To address the issue of modeling errors caused by parameter uncertainties, system modeling is done using an interval type-2 (IT2) polynomial fuzzy model. Also, a premise mismatched controller design strategy is employed to improve controller design flexibility. In addition, to attenuate the conservatism of the analytical results, a novel impulse-time-dependent discretized polynomial copositive Lyapunov function (IDDPCLF) is employed, and the obtained non-convex resultant conditions are handled by the proposed convexification method. Finally, the usefulness of the impulsive controller design approach and the convexification method are verified through an example.
In this paper,we investigate formation tracking control of autonomous underwater vehicles(AUVs)with model parameter uncertainties and external *** external disturbances due to the wind,waves,and ocean currents are com...
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In this paper,we investigate formation tracking control of autonomous underwater vehicles(AUVs)with model parameter uncertainties and external *** external disturbances due to the wind,waves,and ocean currents are combined with the model parameter uncertainties as a compound *** a disturbance observer(DO)is introduced to estimate the compound disturbance,which can be achieved within a finite time independent of the initial estimation *** on a DO,a novel fixed-time sliding control scheme is developed,by which the follower vehicle can track the leader vehicle with all the states globally stabilized within a given settling *** effectiveness and performance of the method are demonstrated by numerical simulations.
The operation of most wastewater treatment systems is an open-loop system. There is limited feedback control of membrane bioreactors (MBR) which makes it impossible to regulate the quality of the treated water. The ob...
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With an increasing application of the multivariate statistical process monitoring method, the fault identification becomes more and more crucial after the fault detection, which is benefited to fault troubleshooting e...
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The observability property of population balance equations with biomass measurements is addressed within the framework of indistinguishable trajectories. The population balance equation is described by a partial integ...
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The observability property of population balance equations with biomass measurements is addressed within the framework of indistinguishable trajectories. The population balance equation is described by a partial integro-differential equation which is coupled with an ordinary differential equation for the nutrient dynamics. For the semi-discretized model equations, the dynamics of indistinguishable trajectories are derived and evaluated for the special case of equal partitioning at cell division revealing that the observability property is guaranteed as long as the nutrient concentration is not depleted. Based on these results, an observer is designed and tested in simulation to estimate the cell population distribution using biomass measurements in a batch bioreactor for the case of a bi-structured population.
In this paper, we address the decentralized optimal output regulation problem for two-time-scale (TTS) interconnected systems with unknown slow dynamics through adaptive dynamic programming (ADP). Firstly, singular pe...
In this paper, we address the decentralized optimal output regulation problem for two-time-scale (TTS) interconnected systems with unknown slow dynamics through adaptive dynamic programming (ADP). Firstly, singular perturbation theory is leveraged to decompose the TTS interconnected system into a slow subsystem and several interconnected fast time-scale subsystems. Secondly, we develop a decentralized optimal control scheme for the fast time-scale subsystems with interconnections. Also, we devise an off-policy ADP algorithm to learn the optimal control strategy for the slow time-scale subsystem with unknown dynamics. Moreover, we combine the slow and fast control strategies to design the composite decentralized optimal output regulator. Both optimality and stability of the closed-loop system are rigorously analyzed. Finally, simulation results are provided to validate the effectiveness of the proposed methodology.
This paper develops an iterative learning control law for a class of nonlinear systems. The approach used to represent the nonlinear system dynamics is a Takagi-Sugeno fuzzy repetitive process that considers the two d...
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