By Bo Shen, Zidong Wang, Huisheng Shu
Nonlinear Stochastic methods addresses the frequently-encountered challenge of incomplete details. The reasons of this challenge thought of right here contain: lacking measurements; sensor delays and saturation; quantization results; and sign sampling.
Divided into 3 components, the textual content starts with a spotlight on H∞ filtering and regulate difficulties linked to normal periods of nonlinear stochastic discrete-time structures. Filtering difficulties are thought of within the moment half, and within the 3rd the idea and methods formerly built are utilized to the answer of matters coming up in advanced networks with the layout of sampled-data-based controllers and filters.
Among its highlights, the textual content presents:
• a unified framework for filtering and keep watch over difficulties in complicated verbal exchange networks with restricted bandwidth;
• new recommendations comparable to random sensor and sign saturations for extra sensible modeling; and
• demonstration of using innovations equivalent to the Hamilton–Jacobi–Isaacs, distinction linear matrix, and parameter-dependent matrix inequalities and sums of squares to deal with the computational demanding situations inherent in those platforms.
The number of contemporary examine effects awarded in Nonlinear Stochastic procedures might be of curiosity to educational researchers on top of things and sign processing. Graduate scholars operating with verbal exchange networks with lossy info and keep watch over of stochastic structures also will take advantage of interpreting the book.
Read or Download Nonlinear Stochastic Systems with Incomplete Information: Filtering and Control PDF
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Additional resources for Nonlinear Stochastic Systems with Incomplete Information: Filtering and Control
2, shows that the quantized H∞ control problem for stochastic time-delay systems with Lipschitz-like nonlinearities and missing measurements can be solved by the numerically appealing LMI approach. 3 Let the disturbance attenuation level γ > 0 be given. 91) . 90) are feasible, the desired controller parameters are given by Fc = Y R2−1 , Gc , and Uc = XR2−1 . 89), respectively. 76) can be rewritten as H2 (x, xd ) = ϑ T Υ1 ϑ, where ⎡ Σ11 ⎢ ∗ ⎢ Υ1 = ⎢ ⎣ ∗ ∗ Σ12 Σ22 μ−1 (1 + ε3 )AT1 E μ−1 (1 + ε3 )AT1 Ed μ−1 (1 + ε3 )AT1d Ed ⎥ ⎥ ⎥, μ−1 (1 + ε3 )E T Ed ⎦ μ−1 (1 + ε3 )AT1d E ∗ μ−1 (1 + ε3 )E T E ∗ ∗ ⎤ μ−1 (1 + ε3 )EdT Ed Σ11 = μ−1 (1 + ε3 ) AT1 A1 + AT2 A2 + θ ATw P1 Aw + Q1 − P1 + μ−1 1 + ε3−1 LT Γ¯ GTc Gc Γ¯ L + ε1−1 LT Γ¯ Λ2 Γ¯ L T T + μ−1 LT Cmc GTcm Gcm Cmc L + ε1−1 LT Cmc Λ2m Cmc L, Σ12 = μ−1 (1 + ε3 ) AT1 A1d + AT2 A2d + θ ATw P1 Awd , Σ22 = μ−1 (1 + ε3 ) AT1d A1d + AT2d A2d + θ ATwd P1 Awd − Q1 .
2 Main Results 25 1 1 + θ FwT (ηk , ηk−d )V1ηη (ηαk )Fw (ηk , ηk−d ) + ηkT V1ηη (ηαk )ηk 2 2 + F1T (ηk , ηk−d )V1ηη (ηαk )H1 (ηk )vk − ηkT V1ηη (ηαk )H1 (ηk )vk − F1T (ηk , ηk−d )V1ηη (ηαk )ηk + 1 2 1 + 2 p αr2 G1rT (ηk )V1ηη (ηαk )G1r (ηk ) r=1 p m βr2 G2rT (ηk )V1ηη (ηαk )G2r (ηk ) + r=1 αr2 G3rT (ηk )G3r (ηk ) r=1 + F2T (ηk , ηk−d )F2 (ηk , ηk−d ) + 2F2T (ηk , ηk−d )H2 (ηk )vk + vkT H2T (ηk )H2 (ηk )vk + V2 (ηk ) − V2 (ηk−d ) − γ 2 vk 2 1 = E −vkT A(ηk , ηαk )vk + F1T (ηk , ηk−d )V1ηη (ηαk )F1 (ηk , ηk−d ) 2 1 + 2B(ηk , ηαk , ηk−d )vk + θ FwT (ηk , ηk−d )V1ηη (ηαk )Fw (ηk , ηk−d ) 2 1 T + ηk V1ηη (ηαk )ηk + F2T (ηk , ηk−d )F2 (ηk , ηk−d ) 2 T − F1T (ηk , ηk−d )V1ηη (ηαk )ηk + V1η (ηk )F1 (ηk , ηk−d ) T (ηk )ηk + V2 (ηk ) − V2 (ηk−d ) + − V1η + 1 2 1 2 p αr2 G1rT (ηk )V1ηη (ηαk )G1r (ηk ) r=1 p m βr2 G2rT (ηk )V1ηη (ηαk )G2r (ηk ) + r=1 αr2 G3rT (ηk )G3r (ηk ) .
5. 5975 . 5 Summary In this chapter, the quantized H∞ control problem has been addressed for a class of nonlinear stochastic time-delay network-based systems with data missing. Two logarithmic quantizers have been employed to quantize both the measured output and the input signals in the NCSs, and one diagonal matrix whose leading diagonal elements are Bernoulli-distributed stochastic variables has been used to model the data missing phenomena. Then, we have derived a sufficient condition under which the closed-loop system is stochastically stable and the controlled output satisfies H∞ performance constraint for all nonzero exogenous disturbances under the zero initial condition by applying the method of sector bound uncertainties.