This note concerns the delay-dependent robust stability analysis for uncertain singular time-delay systems. The parameter uncertainty is assumed to be norm-bounded and possibly time-varying, while the time delay consi...
This note concerns the delay-dependent robust stability analysis for uncertain singular time-delay systems. The parameter uncertainty is assumed to be norm-bounded and possibly time-varying, while the time delay considered here is assumed to be constant but unknown. By using a new Lyapunov-krasovskii functional which splits the whole delay interval into two subintervals and defines a different energy function on each subinterval, some delay-dependent conditions are presented for the singular time-delay system to be regular, impulse free and robustly stable. The obtained delay-dependent criteria are effective and less conservative than previous ones, which are illustrated by numerical examples.
This note is concerned with the absolute stability analysis for time-delay Lurie control systems with nonlinearity located in an infinite sector and finite one. By using a new Lyapunov-Krasovskii functional that split...
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This note is concerned with the absolute stability analysis for time-delay Lurie control systems with nonlinearity located in an infinite sector and finite one. By using a new Lyapunov-Krasovskii functional that splits the whole delay interval into two subintervals and defines a different energy function on each subinterval and introducing some free-weighting matrices, some new delay-dependent robustly absolute stability criteria are presented in terms of strict linear matrix inequalities (LMIs). The obtained delay-dependent criteria are less conservative than previous ones, as are illustrated by numerical examples.
Based on linear matrix inequalities (LMI) approach,the problem of optimal reliable guaranteed cost (RGC) control with control input and regional poles constraints is investigated for a class of uncertain discrete-time...
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ISBN:
(纸本)9781424415304
Based on linear matrix inequalities (LMI) approach,the problem of optimal reliable guaranteed cost (RGC) control with control input and regional poles constraints is investigated for a class of uncertain discrete-time systems subject to actuator *** state-feedback controller is designed to meet the given upper bounds on the amplitudes of control signals and guarantee,for all admissible time-varying uncertainties and possible actuator failures,the closed-loop system satisfying the pre-specified regional pole index and having the optimal quadratic cost ***,with the constrained control input,the resulting closed-loop system can provide satisfactory stability,transient property and cost performance despite of possible actuator faults.
Data reconciliation is an effective technique for providing accurate and consistent value for chemical process. However, the presence of gross errors can severely bias the reconciled results. Robust estimators can sig...
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Data reconciliation is an effective technique for providing accurate and consistent value for chemical process. However, the presence of gross errors can severely bias the reconciled results. Robust estimators can significantly reduce the effect of gross errors and yield less-biased results. In this article, a new method is proposed to solve the robust data reconciliation problem of nonlinear chemical process. By using several technologies including linearization method, penalty function, virtual observation equation, and equivalent weights method, the robust data reconciliation problem can be transformed into least squares estimator problem which leads to the convenience in computation. Simulation results in a nonlinear chemical process demonstrate the efficiency of the proposed method.
This paper presents a decentralized controller for a binary distillation column. The interactions between subsystems are considered as uncertainty. Then appropriate local H infin problems are defined such that by sol...
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This paper presents a decentralized controller for a binary distillation column. The interactions between subsystems are considered as uncertainty. Then appropriate local H infin problems are defined such that by solving them and applying the designed controller to the system, closed-loop stability and diagonal dominance are guaranteed
Data reconciliation technology can decrease the level of corruption of process data due to measurement noise, but the presence of outliers caused by process peaks or unmeasured disturbances will smear the reconciled r...
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Data reconciliation technology can decrease the level of corruption of process data due to measurement noise, but the presence of outliers caused by process peaks or unmeasured disturbances will smear the reconciled results. Based on the analysis of limitation of conventional outlier detection algorithms, a modified outlier detection method in dynamic data reconciliation (DDR) is proposed in this paper. In the modified method, the outliers of each variable are distinguished individually and the weight is modified accordingly. Therefore, the modified method can use more information of normal data, and can efficiently decrease the effect of outliers. Simulation of a continuous stirred tank reactor (CSTR) process verifies the effectiveness of the proposed algorithm.
The estimation of time-variant parameters in nonlinear models remains as an open problem. In this work, we propose a new approach to addressing this problem by tuning weighting factors in the least-squares dynamic opt...
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The estimation of time-variant parameters in nonlinear models remains as an open problem. In this work, we propose a new approach to addressing this problem by tuning weighting factors in the least-squares dynamic opt...
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The estimation of time-variant parameters in nonlinear models remains as an open problem. In this work, we propose a new approach to addressing this problem by tuning weighting factors in the least-squares dynamic optimization. Through analysis of the solution procedure of the resulting optimization problem, it is found that parameter estimation with a weighted least-squares method is equivalent to a multi-variable closed-loop control system. The weighting factors in the objective function are equivalent to the controller parameters. Like any control system synthesis, the tuning can be made based on the output-input sensitivity analysis. The effectiveness of the approach is illustrated by estimating tray efficiencies and feed composition of a heat-integrated distillation column system.
A synthetical method of multivariable control system performance assessment is proposed in, this paper, which uses multivariable Minimum Variance control (MVC) benchmark to determine the stochastic performance, and No...
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A synthetical method of multivariable control system performance assessment is proposed in, this paper, which uses multivariable Minimum Variance control (MVC) benchmark to determine the stochastic performance, and Normalized Multivariate Impulse Response (NMIR) curve as an alternative measure of performance to test the dynamic performance, and with the help of Auto-Correlation Function (ACF) and Cross-Correlation Function (CCF) to analyse if there are oscillations exist. The method is applied to assess performance of multivariable predictive control system of industrial distillation column.
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