Adaptive dynamic surface control using neural networks for hypersonic flight vehicle with input nonlinearities

This study proposes an effective adaptive dynamic surface control (DSC) method based on the radial basis function neural networks and the auxiliary system for hypersonic flight vehicle (HFV) systems in the presence of system uncertainties, external disturbances, and state variable and control input constraints. Firstly, to enhance the robustness of the system, the neural network is combined with the robust term to deal with the uncertainties and external disturbances of the system. Secondly, to prevent the deterioration of the dynamic performance of the system due to the over-adaptation of the neural networks and the robust terms caused by the state and control input constraints, the auxiliary system is added at each step in the DSC design to adjust the dynamic process of the reference signal and virtual control. Furthermore, the variable structure control is used to solve the problem of dead zone in the control input. Using the Lyapunov analysis method, all signals of the closed-loop system are semi-globally uniformly ultimate bounded. The simulation results illustrate the effectiveness of the proposed control scheme for the HFVs.     

Improved delay‐partitioning approach to robust stability analysis for discrete‐time systems with time‐varying delays and randomly occurring parameter uncertainties

This paper is concerned with the robust stability problem for uncertain discrete‐time systems with interval time‐varying delays and randomly occurring parameter uncertainties. By construction of a suitable Lyapunov–Krasovskii functional and utilization of new zero equalities with delay‐partitioning approach, improved delay‐dependent criteria for the robust stability of the systems are derived in terms of linear matrix inequalities for guaranteeing the asymptotic stability of the concerned systems. The effectiveness and reduction of conservatism of the derived results are demonstrated by three numerical examples. Copyright © 2014 John Wiley & Sons, Ltd.     

Dose planning variations related to delineation variations in MRI-guided brachytherapy for locally advanced cervical cancer

PurposeTo examine the variability in prescribed dose due to contouring variations in intracavitary image-guided adaptive brachytherapy for cervical cancer. To identify correlations between dosimetric outcomes and delineation uncertainty metrics.Methods and MaterialsA data set from an EMBRACE sub-study on contouring uncertainties was used, consisting of magnetic resonance images of six patients with cervical cancer delineated by 10 experienced observers (target volumes and organs at risk). Two gold standard contours were generated, an expert consensus and the simultaneous truth and performance level estimation. Plans were individually optimised to all of the contour sets (12 in total). Plans were applied to the gold standard contour sets, and dose volume histogram parameters including D₉₀, D₉₈ and D_2cm³ were determined. The variability between plans was assessed. Dose volume histogram parameters and delineation uncertainty metrics were correlated using the Spearman's non-parametric rank correlation.ResultsThere is a dosimetric variability between observers, patients and the gold standard contour used for analysis. Approximately 3 Gy D₉₀ EQD2₁₀ variability (SD) was observed for the CTVHR and 1.2-3.6 Gy D_2cm³ EQD2₃ for the organs at risk. The maximum geometric dimensions of the delineations are most commonly correlated with dosimetry changes. Although the correlations are similar across gold standards, the direction of these correlations differs, indicating that the dosimetric outcomes are dependent on the contour that the plan is optimised to.ConclusionThis study highlights the dosimetric differences interobserver uncertainty in contouring can have for cervical cancer brachytherapy. The importance of carefully choosing a gold standard from which to benchmark is reiterated.     

PUGS: A novel scale to assess perceptions of uncertainties in genome sequencing

Expectations of results from genome sequencing by end users are influenced by perceptions of uncertainty. This study aimed to assess uncertainties about sequencing by developing, evaluating, and implementing a novel scale. The Perceptions of Uncertainties in Genome Sequencing (PUGS) scale comprised ten items to assess uncertainties within three domains: clinical, affective, and evaluative. Participants (n=535) from the ClinSeq® NIH sequencing study completed a baseline survey that included the PUGS; responses (mean = 3.4/5, SD=0.58) suggested modest perceptions of certainty. A confirmatory factor analysis identified factor loadings that led to elimination of two items. A revised eight‐item PUGS scale was used to test correlations with perceived ambiguity (r = ?0.303, p < 0.001), attitudinal ambivalence (r = ?0.111, p = 0.011), and ambiguity aversion (r = ?0.093, p = 0.033). Results support nomological validity. A correlation with the MICRA uncertainty subscale was found among 175 cohort participants who had received results (r = ?0.335, p < 0.001). Convergent and discriminant validity were also satisfied in a second sample of 208 parents from the HudsonAlpha CSER Project who completed the PUGS (mean = 3.4/5, SD = 0.72), and configural invariance was supported across the two datasets. As such, the PUGS is a promising scale for evaluating perceived uncertainties in genome sequencing, which can inform interventions to help patients form realistic expectations of these uncertainties.     

Dosimetric consequences of seed placement accuracy in permanent breast seed implant brachytherapy

PurposeThis study quantifies the dosimetric impact of implant accuracy and derives a quantitative relationship relating implant accuracy to target dosimetry.Methods and MaterialsA framework was developed to simulate multiple implants for error combinations. Spherical clinical target volumes (CTVs) were modeled with volumes 1.4 cm³, 9.2 cm³, and 20.6 cm³, representing the range seen clinically. Each CTV was expanded 10 mm isotropically to create a planning target volume (PTV).. Random and systematic seed placement errors were simulated by shifting needles from their planned positions. Implant errors were simulated over the range of clinically practical errors in permanent breast seed implant. The relative effect on target coverage was evaluated. Regression analysis was performed to derive relationships between CTV dosimetry and the magnitude of implant accuracy. The validity of the clinically used 10 mm PTV margin for each of the CTVs was assessed.ResultsIntroducing practical implant errors resulted in CTV V_90% median (10th and 90th percentile) of 97.7% (85.9% and 100%), 96.2% (86.8% and 99.7%), and 100% (77.8% and 100%) for the typical, large, and small CTV, respectively. All CTVs show similar trends in target coverage. Polynomials were derived relating seed placement accuracy to median (R² = 0.82) and 10th percentile (R² = 0.78) CTV V_90%._.ConclusionsThis work quantitatively describes the relationship between implant accuracy and CTV coverage. Based on simulations, the 10 mm PTV margin is adequate to maintain target coverage. These equations can be used with institutional seed placement accuracy to estimate coverage.     

一类非线性不确定系统的滑模观测器设计及其在故障检测中的应用

研究了一类非线性部分满足Lipschitz条件的非线性不确定系统的鲁棒滑模观测器的设计问题。提出了一种将Thau观测器与WalcottZak观测器结合的非线性鲁棒滑模状态观测器设计方案,并利用Lyapunov定理证明了状态观测误差最后一致收敛于一个紧集。将所设计的滑模观测器应用于故障检测,仿真实验结果验证了该方法的有效性。