Final-State Control Using Polynomial and Time-Series Data

We have proposed a frequency-shaped final-state control method that can reduce a residual vibration after positioning by minimizing Fourier gain of feedforward input at desired frequency points. In this method, the feedforward input is obtained as a time series data, therefore, it requires a large memory size to store them in an embedded controller. In this paper, we propose a final-state control method based on a polynomial input. It only requires to store the coefficient of the polynomial, and the required memory size can be drastically reduced. Furthermore, by considering the time symmetry of input, a method to reduce the order of the polynomial without a performance degradation is proposed. The effectiveness is verified by simulations.

For information devices such as hard disk drives, actuators must be controlled as quickly and precisely as possible. The design of the feedforward input is very important in satisfying these requirements. Therefore, we have proposed design methods based on final-state control so as to reduce its spectrum at the desired frequency points. Furthermore, the final-state control method has been extended to generate the feedforward input using a polynomial. By using a polynomial, the required memory size can be drastically reduced because only the coefficients of the polynomial must be stored. However, when the step number of the input increases, the method may not produce a correct solution because of a numerically ill-posed problem. In this paper, we propose a design method for the final-state control based on a time-symmetric polynomial input. The simulation results show that the proposed method contributes to the improvement of not only the numerically ill-posed problem but also the performance.

As a method to generate a feedforward input that achieves high speed and high precision positioning,a polynomial-input-type final-state control has been proposed.This method can generatea feedforward input that which drives an initial state to a final state in a finite time.However,the existence of the solution is not always ensured for any initial and final states.To solve this problem, a final-state control method using a polynomial and time-series data has been proposed,though,it requires an extra memory to store the time-series data.In this research,we propose a method that does not require the time-series data by introducing a negligibly-sinall final-state error.The effectiveness of the proposed method is verified by performing simulations.

This paper proposes a new design method of track-seeking trajectory for hard disk drives by using final-state control method. The proposed method can obtain a feedforward control input whose frequency components are minimum at the desired frequency points. In our approach, the control input is evaluated in continuous-time domain, and the frequency components higher than the Nyquist frequency can be also optimized. Simulation and experimental results are shown to evaluate the effectiveness of the proposed method.

In Hard Disk Drives, there are two seek modes. One is a short distance seek mode, the other is a long distance seek mode. There is not saturaliton in the short distance seek mode, so many methods were proposed to realize a low acoustic noise and low vibration seek. However, in order to realize a low acoustic noise seek in Hard Disk Drives, the long distance seek mode is very important. So, a new method for the long distance seek is proposed in this paper. In conventional methods, a reference velocity curve is used. This reference velocity curve can be considered a switching line in the phase plane. In the proposed method for a long distance seek, the sliding mode controller with a frequency-shaped switching line is designed for a feedforward controller. The advantage of this method is a hign frequency ingredient in the feedforward input can be eliminated by setting the frequency-shaped switching line. The validity of the proposed method was confirmed by numerical and experimental results using a miniature 2.5-inch Hard Disk Drive.

Role and member selection in team formation using resource estimation for large-scale multi-agent systems

In this paper we deal with active control of shock in a collision problem between two objects. In order to make it clear how the deformation of the shock-receiving object can be maximized while minimizing the deformation of the shock-giving object and how energy can be transmitted unilaterally, the relationships among contact stiffness, deformation time, deformation ratio and energy balance are discussed. The final-state control is applied to obtain a feedforward input to deform the shock-receiving object by a desired amount in a predetermined time. Thus, the energy balance and the energy efficiency are verified. Furthermore we examine the conditions necessary to realize a ‘dynamical diode’ that can transmit energy unilaterally from the shock-giving object to the shock-receiving object. It is demonstrated experimentally that the appropriate feedforward input can be obtained by final-state control under specified conditions of contact stiffness and deformation time.

The issue of optimal output transition control for nonlinear differential flat systems with constraints is investigated. Of special interest is the generation of a state reference trajectory and a feedforward input, which are essential to the two-degree-of-freedom design. The proposed approach is to transfer the transition problem in the real output space into a trajectory planning issue in the flat output space. The distinguishing feature of our approach is the generation of a noncausal trajectory for the flat output. This approach is shown to be highly effective in creating performance improvements. It should also be noted that the proposed methodology guarantees that the planned trajectories are feasible for all nonlocal transitions. This allows the application of stable inversion in the planning of optimal output transitions. The proposed method is illustrated on a benchmark system, the isothermal continuous stirred tank reactor, although its applicability is much wider.

Slope deformation prediction is crucial for early warning of slope failure, which can prevent property damage and save human life. Existing predictive models focus on predicting the displacement of a single monitoring point based on time series data, without considering spatial correlations among monitoring points, which makes it difficult to reveal the displacement changes in the entire monitoring system and ignores the potential threats from nonselected points. To address the above problem, this paper presents a novel deep learning method for predicting the slope deformation, by considering the spatial correlations between all points in the entire displacement monitoring system. The essential idea behind the proposed method is to predict the slope deformation based on the global information (i.e., the correlated displacements of all points in the entire monitoring system), rather than based on the local information (i.e., the displacements of a specified single point in the monitoring system). In the proposed method, (1) a weighted adjacency matrix is built to interpret the spatial correlations between all points, (2) a feature matrix is assembled to store the time-series displacements of all points, and (3) one of the state-of-the-art deep learning models, i.e., T-GCN, is developed to process the above graph-structured data consisting of two matrices. The effectiveness of the proposed method is verified by performing predictions based on a real dataset. The proposed method can be applied to predict time-dependency information in other similar geohazard scenarios, based on time-series data collected from multiple monitoring points.

In the production process of hard disk drive (HDD), there is a process of writing servo signals on magnetic disks to move the head to target address. However, conventional servo track writer takes longer time to draw servo signals because of recent increase of the capacity of HDD. Therefore, they desire a low-cost method to draw servo signals. In order to resolve the problems, self servo track writing (SSTW) method which draws servo signals with its own head was already suggested. In SSTW method, there are problems to realize it. One is how to know where the absolute position of head is. The other is that written servo tracks diverge because gain of the feedback controller is higher than 0[dB] in high frequency domain. In our past work, new method for SSTW has already been suggested [1][2]. This method is essentially different from other methods, and performance is dramatically improved. However, servo tracks diverge gradually if we apply this method to real product. The purpose of this paper is to make it clear why servo tracks diverge gradually by using hard disk benchmark software, which is produced by IEEJ Specialized Committee on Servo Technology for Next Generation Mass-Storage System [3]. We concluded that the reason is in measurement noise. Furthermore, consideration for a new feedforward input is described.

We propose a noise reduction method for unsteady pressure-sensitive paint (PSP) data based on modal expansion, the coefficients of which are determined from time-series data at optimally placed points. In this study, the proper orthogonal decomposition (POD) mode calculated from the time-series PSP data is used as a modal basis. Based on the POD modes, the points that effectively represent the features of the pressure distribution are optimally placed by the sensor optimization technique. Then, the time-dependent coefficient vector of the POD modes is determined by minimizing the difference between the time-series pressure data and the reconstructed pressure at the optimal points. Here, the coefficient vector is assumed to be a sparse vector. The advantage of the proposed method is a self-contained method, while existing methods use other data, such as pressure tap data for the reduction of the noise. As a demonstration, we applied the proposed method to the PSP data measuring the Kármán vortex street behind a square cylinder. The reconstructed pressure data agreed very well with the pressures independently measured by pressure transducers. This modal-based approach will be applicable not only to PSP data but other types of experimental data.

A phase-searching look-up table (PS-LUT) method is proposed to dramatically reduce the memory size of the new look-up table (N-LUT) method as well as to keep its advantage of fast computational speed. Small quantities of samples are chosen as the basic phase points (BPPs) in the principle fringe pattern (PFP), and phases of the object points for BPPs are precalculated and stored in the table. The phases of object point for the whole PFP could be quickly obtained through a phase-searching method. With proper reference beam phases, PFP could be rapidly generated. The experimental results reveal that the computational speed of the proposed method is about 24 times faster than that of the ray-tracing method, and the required memory size is 1731 times less than that of the N-LUT method. To eliminate the coherent noise of the N-LUT and PS-LUT, the random PFP N-LUT (RN-LUT) and PS-LUT (RPS-LUT), in which the PFP is randomly chosen for every object point, are put forward. The reconstructed images with a spatial light modulator indicate that both the RN-LUT and RPS-LUT methods are extremely effective in improving the quality of the reconstructed images.

We propose a new method based on the idea of delegating regressors for predicting the soil radon gas concentration (SRGC) and anomalies in radon or any other time series data. The proposed method is compared to different traditional boosting e.g., Extreme Gradient Boosting (EGB) and simple regression methods e.g., support vector regressors with linear kernel and radial kernel in terms of accurate predictions. R language has been used for the statistical analysis of radon time series (RTS) data. The results obtained show that the proposed methodology predicts SRGC more accurately when compared to different traditional boosting and regression methods. The best correlation is found between the actual and predicted radon concentration for window size of 2 i.e., two days before and after the start of seismic activities. RTS data was collected from 05 February 2017 to 16 February 2018, including 7 seismic events recorded during the study period. Findings of study show that the proposed methodology predicts the SRGC with more precision, for all the window sizes, by overlapping predicted with the actual radon time series concentrations.

It is well recognized that an adaptive output feedback control based on almost strictly positive real‐ness (ASPR) or output feedback strictly passivity (OFSP) property of the system has strong robustness with respect to disturbances and uncertainty. However, most practical systems do not have such properties. In order to realize an augmented ASPR system for designing adaptive output feedback controller, a kind of adaptive parallel feedforward compensator (PFC) design schemes have been proposed for linear systems. In this paper, we propose an adaptive PFC design scheme by Kernel method for nonlinear systems and provide output feedback passivity based adaptive output feedback control for nonlinear systems. The effectiveness of the proposed method will be confirmed through numerical simulations. © 2021 Institute of Electrical Engineers of Japan. Published by Wiley Periodicals LLC.

Computer systems are constantly under attack and illegal access is a constant threat which makes security even more critical. A system can be broken into and secret information, e.g. decryption key, may be exposed. Very recently, a new framework for the protection against such key exposure problem was suggested and was called, key-insulated encryption (KIE). In this paper, we study key insulated cryptosystems without computational assumptions. First, we define the model of KIE in unconditional setting and show lower bounds on required memory sizes. Our bounds are all tight since our concrete construction of KIE achieves the bounds. In other words, this construction is optimal in terms of memory sizes of a user, a trusted device and a sender. We then, extend the concept of it further, and add an extra property so that any pair of users in the system can communicate with each other. We called the version with this added extension, dynamic and mutual key insulated encryption (DMKIE), and concrete implementations of DMKIE are also shown. Finally, we discuss the relationship among KIE, key predistribution schemes (KPS) and broadcast encryption schemes (BES), specifically, showing that DMKIE can be constructed from KPS or BES.