This paper proposes a new control technique for Multi-Inputs Multi-Outputs (MIMO) systems with multiple time delays. The control design method is the Generalized Minimum Variance Control (GMVC). As for MIMO systems, it is assumed that time constants are different greatly each other. In this case, setting a suitable sampling period in every control loop, we can reduce computational complexity very much keeping the effective performance.
The generalized minimum variance control (GMVC) is one of the design methods of self-tuning control (STC). In general, STC is applied as a discrete-time (DT) design technique. However, by some selection of the sampling period, the DT design technique has possibilities of generating unstable zeros and time-delays, and of failing in getting a clear grasp of the controlled object. For this reason, we propose a continuous-time (CT) design technique of GMVC, which we call CGMVC. In this paper, we confirm some advantages of CGMVC, and provide a numerical example.
The global positioning system (GPS) is a 3D positioning system using space satellites. It provides location information for navigation systems, location surveys, and so on. GPS uses two types of measuring methods; stand-alone positioning and relative measurement using another receiver with a known position. We focus on the method called differential GPS (DGPS), which is a relative measurement technique, because the measurement accuracy of DGPS is generally better than that of stand-alone positioning. However, when the baseline used in DGPS becomes long, the positioning error increases. Therefore, we propose to improve the accuracy in the measurement of the long baseline DGPS. For precise positioning by the long baseline DGPS, we use weighting coefficients of the elevation angle to satellites in the calculation and correct DGPS-specific bias errors by the proposed method. It is shown that we succeed in improving the measurement accuracy of the long baseline DGPS.
In this paper we study the stochastic optimal (LQG) tracking problems with preview for a class of linear continuous-time Markovian jump systems. The systems are described as continuous-time switching systems with Markovian mode transitions. Necessary and sufficient conditions for the solvability of our LQG tracking problems are given by coupled Riccati differential equations and coupled scalar differential equations with terminal conditions. Correspondingly feedforward compensators introducing future information are given by coupled differential equations with terminal conditions. We consider three different tracking problems depending on the property of the reference signals. Finally we give numerical examples and verify the effectiveness of our design method.
The Frenkel-Kontorova model is a nonlinear lattice model to represent extremely complicated behaviors such as a dislocation in crystal and DNA structures. This model is given as the dynamical system composed of infinitely many bonded particles. Thus, a spatially restricted model is used in numerical simulations of this model. However, a phenomenon called a reflection wave, which will occur at the boundary due to this finite approximations, is known to considerably degrade computational precision in the simulation. This paper thus proposes a method to analyze a property of this reflection wave via the Generalized Kalman-Yakubovich-Popov (GKYP) lemma.
Indium point cells are fabricated using ingots of various forms from a variety of sources (manufacturers). Using these cells, newly built indium point furnaces are evaluated and their reliability is confirmed. The indium point realizations based on the single solid-liquid method (SSL method) and multi solid-liquid method (MSL method) are evaluated. The effect of impurities in the ingots is evaluated from the dependency of the slope of the freezing curve on the change in furnace temperature, the indium point depression based on the impurity analysis, and the cell comparison. The results show equality among the cells. Based on the results obtained, the uncertainty in realizing the indium point using the described indium point cells and indium point furnaces is estimated. The new uncertainty budget introduces uncertainties coming from plateau repeatability and chemical impurity derived by the present work, the values of which are significantly lower than those adopted in the current calibration service.
Reducing tool differences is one of the important tasks to improve the yield of semiconductor device manufacturing. Various kinds of methods have been proposed to solve this problem. These methods enable us to find problematic tools from numbers of process tools. However, finding problematic tools is not always enough to work out the problem of tools. Visualization of the transition profile of tool differences provides us additional information to help finding the unknown control parameters. It helps us to find corresponding events such as maintenance, repair, and adjustment. We design a profiling algorithm based on the maximum likelihood estimation. This algorithm introduces a new constraint that “tools are stable at each process step for a short period”, and recursively uses a regression method by employing previous results of the estimation. Simulation results show that our algorithm extracts the transition profile of tool differences more precisely than existing regression methods.
A new HVAC (Heating, Ventilating, and Air-Conditioning) system for buildings is proposed. The key technology for the system is a twin coil air handling unit (AHU) and its advanced control method. One coil is equipped to cool and dehumidify the fresh air intake, and the other coil is for cooling circulated air. The deeply chilled water is necessary only for removing the moisture from the fresh air. The latter coil requires moderately cool water according to the HVAC load. Then 2 kinds of chilled water in terms of temperature should be prepared. The structure helps saving the energy consumption for air-conditioning because the higher chilled water temperature implies the better chiller efficiency (COP: Coefficient of Performance). In addition, an advanced control method that is called an ‘Air-Water cooperation system’ is introduced. The control system mainly focuses on energy savings through changing the temperature of the chilled water and supply air according to the HVAC load and weather conditions. In this paper, we introduce a Next Generation HVAC system with its control system and present evaluation results of the system for the model-building simulator.
Modeling and control of dynamics of three-dimensional object grasping by using a pair or triplet of multi-joints robot fingers are investigated under rolling contact constraints and arbitrary shapes of the object and fingertips. It is assumed that a rolling contact between two rigid bodies with smooth surfaces is governed by the condition that the two surfaces coincide at the common contact point and share the same tangent plane. The contact constraint expressing the contact of the two surfaces at a single point in the 3-dimensional Euclidean space is reinterpreted by a set of three Pfaffian constraints, one of which is a velocity equivalence in the normal to the tangent plane at the contact point and the other two are velocity equivalence relations on the tangent plane. The Euler-Lagrange equation of motion of the overall fingers/object system is derived by introducing Lagrange multipliers corresponding to those Pfaffian constraints together with update laws of length parameters of loci of each contact point on the fingertips and object surfaces. It is shown that the Euler-Lagrange equation is parameterized by the length parameters through quantities of the first fundamental form of the surfaces, but the update laws of length parameters are governed by quantities of the second fundamental form. Furthermore, it is shown that the rolling constraints are directionally integrable. In accordance with this result, a control signal for maintaining contacts with the object is suggested from the standpoint of fingers-thumb opposability.
Positioning systems supported by satellites are increasingly used because of the widespread use of cheap and small personal Global Positioning System (GPS) receivers. Personal GPS receivers are used in cellular phones and car navigation systems. The positioning method used by these personal GPS receivers often produces inaccurate positioning results. Because of the price and size constraints of personal GPS receivers, their accuracy is compromised, and as a result, high-accuracy positioning methods are not widely used. In this paper, we propose a high-accuracy positioning method that can be used with personal GPS receivers. Our proposed method is based on a new approach that takes into account both the systems and solar wind environments. To verify our method, we target the positioning accuracy equivalent to that of the dual-frequency positioning system, which is the highest-accuracy positioning method among all standalone positioning methods. Our approach is implemented in software only, meaning it can be implemented in even the most widely used GPS receivers. Processing speeds associated with the implementation of our proposed method using the CPUs of cellular phones and car navigation systems are well-tolerated.
Chronic Obstructive Pulmonary Disease is a disease in which the airways and tiny air sacs (alveoli) inside the lung are partially obstructed or destroyed. Emphysema is what occurs as more and more of the walls between air sacs get destroyed. The goal of this paper is to produce a more practical emphysema-quantification algorithm that has higher correlation with the parameters of pulmonary function tests compared to classical methods. The use of the threshold range from approximately -900 Hounsfield Unit to -990 Hounsfield Unit for extracting emphysema from CT has been reported in many papers. From our experiments, we realize that a threshold which is optimal for a particular CT data set might not be optimal for other CT data sets due to the subtle radiographic variations in the CT images. Consequently, we propose a multi-threshold method that utilizes ten thresholds between and including -900 Hounsfield Unit and -990 Hounsfield Unit for identifying the different potential emphysematous regions in the lung. Subsequently, we divide the lung into eight sub-volumes. From each sub-volume, we calculate the ratio of the voxels with the intensity below a certain threshold. The respective ratios of the voxels below the ten thresholds are employed as the features for classifying the sub-volumes into four emphysema severity classes. Neural network is used as the classifier. The neural network is trained using 80 training sub-volumes. The performance of the classifier is assessed by classifying 248 test sub-volumes of the lung obtained from 31 subjects. Actual diagnoses of the sub-volumes are hand-annotated and consensus-classified by radiologists. The four-class classification accuracy of the proposed method is 89.82%. The sub-volumetric classification results produced in this study encompass not only the information of emphysema severity but also the distribution of emphysema severity from the top to the bottom of the lung. We hypothesize that besides emphysema severity, the distribution of emphysema severity in the lung also plays an important role in the assessment of the overall functionality of the lung. We confirm our hypothesis by showing that the proposed sub-volumetric classification results correlate with the parameters of pulmonary function tests better than classical methods. We also visualize emphysema using a technique called the transparent lung model.