Prediction-based Iterative Learning Control (PILC) for Uncertain Dynamic Nonlinear Systems Using System Identification Technique

Prediction-based Iterative Learning Control (PILC) is proposed in this paper for a class of time varying nonlinear uncertain systems. Convergence of PILC is analyzed and the uniform boundedness of tracking error is obtained in the presence of uncertainty and disturbances. It is shown that the learning algorithm not only guarantees the robustness, but also improves the learning rate despite the presence of disturbances and slowly varying desired trajectories in succeeding iterations. The effectiveness of the proposed PILC is presented by simulations.     

Enhanced crystallization of poly(lactide) stereocomplex by xylan propionate

The effect of xylan propionate (XylPr) as a novel biomass‐derived nucleating agent on the poly(lactide) sterecomplex was investigated. Addition of XylPr to an enantiomeric blend of poly(l ‐lactide) (PLLA) and poly(d ‐lactide) (PDLA) was performed in either the solution state or molten state. The solution blend of PLLA/PDLA with XylPr was prepared by mixing equal volumes of 1 wt% XylPr/PLLA and 1 wt% XylPr/PDLA solutions in chloroform and precipitating in methanol. The solution blend with XylPr showed shorter half‐time crystallization than the solution blend without XylPr in isothermal crystallization between 80 and 140 °C, although homocrystallization occurred. Enhanced stereocomplex crystallization in the solution blend with XylPr was observed at 180 °C, where no crystallization occurred in the solution blend without XylPr. Addition of XylPr to PLLA/PDLA blend in the molten state was performed at 240 °C. Thereafter, the melt blend of PLLA/PDLA with or without XylPr was either quenched in iced water or isothermally crystallized directly from the melt. Isothermal crystallization of the melt‐quenched blend with XylPr gave a similar result to the solution blend with XylPr. In contrast, the melt‐crystallized blend with XylPr formed only stereocomplex crystals after crystallization above 140 °C. Furthermore, the melt‐crystallized blend with XylPr showed a higher crystallinity index and melting temperature than the melt‐crystallized blend without XylPr. This shows that XylPr promotes stereocomplex crystallization only when the blend of PLLA/PDLA with XylPr is directly crystallized from the molten state just after blending. © 2016 Society of Chemical Industry     

Model-less visual servoing using modified simplex optimization

This article describes a robot positioning task with respect to a static target by visual servoing. The vision system is uncalibrated, and the kinematic model of the robot may be totally unknown. The displacements of the robot at joint level are generated in real time in order to minimize the objective function. The objective function includes the quadratic error between the current and the desired target images. A simplex method is used to minimize the objective function, and a Newton-like method is also used near convergence. We successfully validated this method with simulations under the graphic library OpenGL. This work was presented in part at the 10th International Symposium on Artificial Life and Robotics, Oita, Japan, February 4–6, 2005     

Design of sampled-data critical control systems based on the fast-discretization technique

The fast-discretization is known as an approximate but efficient technique for design and analysis of sampled-data systems. In this paper, we propose a fast-discretization-based design for sampled-data critical control systems. Supposing a tracking problem or a slow-changing disturbance rejection problem, we assume that an exogenous input is a persistent and/or transient input with bound on the rate of change. It is shown that the critical constraint for such exogenous inputs can be given in the form of the inequality constraint on the unit step response. The design parameters are determined by a numerical search method subject to this constraint. However, instead of evaluating it strictly, we check the corresponding constraint which is obtained from the fast-discretized system. Although this approach is approximate, it provides an efficient numerical procedure for a computer-aided design. To show the validity of the proposed method, an example of a multi-objective critical control system design is presented.     

The effects of an angiotensin-converting inhibitor (enalapril) on patients with mild cardiac failure--evaluating cardiac function based on the relationship between daily walking pace and heart rate

BACKGROUND: Heart failure has been evaluated by several methods, the New York Heart Association (NYHA) classification of heart failure based on symptoms being used most frequently. However, the degree of heart failure assessed by these criteria does not always correlate with cardiac function in daily life. HYPOTHESIS: The aim of the study was to evaluate cardiac function based on the walking pace/heart rate (HR) relationship to assess the effects of enalapril, an angiotensin-converting enzyme inhibitor, in patients with mild to moderate cardiac function. METHODS: To evaluate cardiac function objectively, we developed a method using a pedometer to count the steps walked while simultaneously recording HR using a Holter electrocardiograph (ECG). Step-count walk rate (WR) was recorded on the magnetic tape of the Holter apparatus, and both HR and walking pace were calculated automatically by the Holter ECG analysis system. Data were determined every hour, and mean pace and HR were plotted along the x and y axes, respectively. The slope of HR x WR was calculated using the least squares method. The slope and the total number of steps were regarded as indicators of cardiac function and quality of life, respectively. We analyzed 36 subjects, consisting of 8 normal volunteers, 8 patients in New York Heart Association (NYHA) class I. 11 in class II, and 9 in class III chronic mild heart failure, during maximal exercise work load by bicycle ergometer; furthermore, fractional shortening of the left ventricle on echocardiogram was determined in 14 patients with chronic mild heart failure and was compared with the slope of HR x WR. Enalapril was administered at a daily dose of 2.5-10 mg for 1-24 months (mean 6 months) in 60 patients to evaluate the effects of this drug on these parameters. RESULTS: There was a significant inverse relationship between maximal work load and the HR x WR slope, and also between the fractional shortening and the slope, suggesting that the slope may reflect the severity of cardiac dysfunction. Furthermore, the slope decreased significantly from 1.8 +/- 1.26 before enalapril to 1.0 +/- 0.94 (mean +/- standard deviation) after drug administration, while the total number of steps increased significantly from 4842 +/- 3581 to 7804 +/- 4793. CONCLUSION: The slope of the graph relating step count and HR proved to be a good, objective indicator of cardiac function, and enalapril therapy improved this parameter.     

A method for reducing the order of multivariable stochastic systems

This correspondence considers the problem of modeling a given linear time-invariant system by a reduced-order model. The method proposed here is based on the minimization of an equation error, which leads to a linear problem. An expression for a reduced-order model is given in the case when a random input is used.     

Mixed method of aggregation and i.s.e. criterion approaches for system reduction

A combination of dominant-eigenvalue concept and integral-squared-error criterion approach is proposed for the reduction of a high-order system.     

Moments of an output feedback system

The moments of an output feedback system are given explicitly in terms of the moments of the open-loop system and the feedback gain. From these expressions, it is clear that the moments of a high-order system and reduced model are the same under output feedback law provided that they are identical for the open-loop case.     

Iterative Learning Control Utilizing the Error Prediction Method

In this paper, iterative learning control utilizing the error prediction method is proposed for a class of linear time varying systems subjected to disturbances. Prediction of the error is done by identifying the system time varying parameters. Convergence of the proposed method is analyzed and the uniform boundedness of tracking error is obtained in the presence of uncertainty and disturbances. It is shown that the learning algorithm not only guarantees the robustness, but also improves the learning rate despite the presence of disturbances. The effectiveness of the proposed method is presented by simulations.     

The effects of topographic correction and gap filling in imagery on the detection of tropical forest disturbances using a Landsat time series in Myanmar

In this study, we evaluated the effects of topographic correction and gap filling of Landsat Enhanced Thematic Mapper Plus (ETM+) images on the accuracy of forest change detection through a trajectory-based approach. Four types of Landsat time series stacks (LTSS) were generated. These stacks resulted from combinations of topographically corrected and uncorrected imagery combined with gap-filled and unfilled stacks. These combinations of stacks were then used as input into a trajectory-based change detection. The results of change detection from trajectory-based analysis using these LTSS were compared in order to assess the effects of both topographic correction and gap-filling procedures on the ability to detect forest disturbances. The results showed that overall accuracies of change detection were improved after gap filling (10.5% and 7.5%), but were only slightly improved after topographic correction (3.6% and 0.6%). Although the gap-filling process introduced some uncertainty that might have caused false change detection, the number of pixels whose detection of disturbance was enhanced after gap filling exceeded those detecting false change. The results also showed that the topographic correction did not contribute much to improve the change detection in this study area. However, topographic correction has a potential to increase the accuracy of change detection in areas of more rugged terrain and steep slopes. This is because a direct relationship between the slope of the topography with topographic correction and an enhanced detection of disturbance in pixels from year to year was observed in this study. For robust change detection, we recommend that a gap-filling process should be included in the trajectory-based analysis procedures such as the one used in this study where a single image per year is used to characterize change. We also recommend that in areas of rugged terrain, a topographic correction in the image pre-processing should be implemented.