Battery technology is becoming more diverse; sodium-sulfur batteries that can operate at high temperatures and high-energy-density lead-acid or lithium-ion batteries for electric vehicles have been developed. However, these chemical battery types differ in their cycle lives. In this study, a theoretical stochastic process method was used to model the charge–discharge behavior and cycle life of batteries to increase the efficiency of battery storage systems. The developed modeling methodology represents the charging and discharging behavior of a battery using the birth and death rates of the birth–death process. However, the countable state space of the birth–death process generally cannot be used for a continuous representation of remaining energy. Hence, a Markov kernel was used to construct a positive real representation system for the remaining energy in a battery.

View full abstract

In this research, a nurse call system with simplified initial setting is developed. The system is constructed by improving an existing nurse call system driven by eye movement, where the movement is detected by image processing. In the initial setting of previous research, template images for the detection of face and eye were created manually. However, it was not easy for system operator to generate suitable template images. To solve this problem, in the research, automatic generation of template images is attempted to simplify the initial setting. The system with simplified initial setting is realized by introducing gamma correction, cascade classifier and false positive rejection. The usefulness of the proposed system was verified through operation of not only initial setting but also nurse call.

View full abstract

The GNSS (Global Navigation Satellite System) is currently used in a variety of applications [1], and its positioning accuracy requirements become more and more demanding. We focus on an automatic strawberry pollination robot (under development in Kobe City College of Technology) and study a method of successive moving baseline vector estimation [2]. In this paper, we propose a method to estimate accurate successive moving baseline vectors based on the difference of the single GNSS receiver observables obtained at two successive observation time (epoch). Furthermore, we also propose a method to estimate the bias error included in the moving baseline vector. Throughout the experiment, the proposed method and the relative positioning method are compared that the error is 0.97 [cm].

View full abstract

The authors have been developing an assistance system for mobility scooters. The users of mobility scooters are usually elderly people or visually impaired people. Thus, an additional warning system can assist them when driving. The goal of this warning assistance system is not to achieve autonomous driving, but to assist human-driven vehicles with sound or vibration. Realizing autonomous driving not only requires high cost but also has the problem of attribution of accident responsibility. A more feasible solution is to provide a warning system to assist driving. This paper describes the design of our system, where the perception of various dangerous information is performed via vision algorithms and visual sensors. Finally, we demonstrate some preliminary recognition results through practical experiments.

View full abstract

The stability of the stochastic age-structured infectious model is studied in this paper. At present, we have still various kinds of the infectious disease threats including Corona virus disease, influenza and monkeypox. Hence, the analysis of infection diseases plays an important role in the modern society. In the past, a great deal of research of infectious diseases has been performed using various kinds of mathematical tools and models. Most of the conventional research is based on the deterministic mathematical tools and models. However, in the realistic spread of the infectious disease, environmental change and individual difference cause some kinds of random fluctuations in the infection, the recovery rates and the vaccination effect. Moreover, the parameters of the population dynamics such as infection, recovery, birth and death rates depend on age. Taking these facts into consideration, we propose the stochastic age-structured infectious model. Since the spread of infection has reference to the stability of the steady state of the stochastic infectious models, we consider the stability of the stochastic infectious models and derive the sufficient conditions for the steady state to be stable by using the stochastic Lyapunov theorem.

View full abstract

Efficient numerical procedure for the ruin/survival probability is proposed, which is concerned with a new numerical scheme of the integral equation describing the behavior of the ruin/survival probability. Properly transforming the infinite domain of integration of the equation into a bounded interval, we bypass the problem of truncation range and then we apply the Chebyshev-Gauss-Radau collocation method. Numerical experiments of test problems involving the Pareto distribution ensure that our method works well also in the asymptotic behavior.

View full abstract

This paper proposes a PCM method that is a method invoking Piecewise Continuous Map (PCM) to investigating nonlinear phenomena of oscillations in parametrically excited pendulums. At first, Sine Circle Map (SCM) is derived from the oscillations in the nonlinear oscillatory systems. Secondly, by applying least mean square method to SCM, approximate PCM is obtained. Fundamental properties of obtained PCM are shown to investigate the nonlinear phenomena in the oscillatory systems. Finally, the motions of mapped points in the PCM are investigated for various values of the parameters of the PCM. Furthermore, the relations of the PCM and the oscillations in the systems are shown for synthesis of the oscillatory nonlinear systems.

View full abstract

First, we define a stochastic shortest path problem (SSP) on Borel space considering the distribution of the total cost. Next, for this SSP, policy classes are set considering the number of steps to reach the terminal state for the first time, and a policy is designed for each class. There is no guarantee that the probability of a large total cost is small for a policy with a small expected value of total cost (expected total cost). The policy that minimizes the expected total cost or Conditional Value at Risk (CVaR) may not reach the terminal state. The proposed policy in this paper by the method of reducing to δ-perturbed problem (δ-PP) or the method of combining the policies obtained by discounted problems has a low probability of a large total cost and is guaranteed to reach the terminal state. Finally, we compare the proposed methods with the policy that minimizes the expected total cost or CVaR.

View full abstract

This paper proposes a multi-robot system to estimate the position of an unknown moving object and track it. Concerning tracking mobile objects, it is important to know where the target is. To recognize the target, we consider attaching a monocular camera to each robot. The target’s position is calculated in two directions of the target from robots. However, since the camera’s information includes observation noises, it is difficult to use simply calculated positions to track the target. In this research, we employed an extended Kalman filter to estimate the position of a moving object. In addition, the estimation accuracy was improved by introducing pseudo-measurement. Each robot track target by optimal control based on the differential game theory. If the target and robots align, the noise is amplified because of triangulation. To avoid this situation, we employed virtual springs to control multi-robots formationFinally, numerical simulations in a two-dimensional plane were performed to verify the usefulness of this method.

View full abstract

In this paper, we study Nash game problems for linear discrete-time Markovian jump systems over finite time intervals. We introduce double coupled difference equatuons (CDREs) to give solutions of the game problems with multi-players. Using these solutions, we obtain Nash strategies by state feedback. In this paper, we focus on the derivation of the necessary conditions for the solvability of the game problems by variational approach.

View full abstract

A new approach is proposed for estimating bivariate SVAR systems with Gaussian distribution shocks. Each sequence of independent shocks has two unknown variance parameters and a structural matrix also leaves their non-diagonal elements unknown. So, there are four unknown parameters, while the symmetric covariance matrix of the residuals in reduced VAR gives us three components. We propose an estimation method such that a new variable with independent Gaussian distributions is added to the original 2-d system. By setting a structural matrix with three unknown parameters and taking three variance parameters into consideration, the number of unknwn parameters becomes six, and we can solve this 3-d SVAR system whose covariance matrix gives us six components. Since the residuals in 3-d system are disturbed by a new noise variable, the estimated parameters are changed from those of 2-d system. By finding 3-d system depending on a perturbed new noise variable whose black line is very close to that of the original 2-d system, we can estimate the true set of parameters as an intersection point of two black lines. Simulation experiments support the utility of our estimation method.

View full abstract

The authors derived a best linear unbiased estimate (BLUE) for the estimation of the noise covariance matrix, where the covariance matrix of the residuals of the linear regression equation is required. In the previous paper, the sample covariance of the residuals was given, but the consistency of the sample covariance was not analyzed. In this paper, theoretical analysis shows that the proposed sample covariance matrix is a consistent estimate of the covariance matrix in a certain sense.

View full abstract

In this study, we propose a novel optimization method, which can track multiple optimal solutions for dynamic problems. In our previous study, we proposed a gravitational particle swarm algorithm (GPSA), which is able to search for multiple optimal solutions. In this paper, first, we apply the original GPSA to a multi-solution tracking problem and reveal its drawback. Second, we propose a modified GPSA, called 𝜏GPSA, by replacing original GPSA’s update rule for personal bests with a tolerance update rule. Finally, we demonstrate that 𝜏GPSA can track multiple optimal solutions in an one-dimensional shifting sphere function.

View full abstract

In this paper, we propose a novel gearbox design method, called multiple gearbox optimization (MGO), that can simultaneously design multiple patterns of feasible gearbox. This MGO consists of a penalty handling method and a multimodal optimization method. The handling method converts an existing constrained gearbox design problem to unconstrained one. The multimodal optimization method is developed by making our previously proposed gravitational particle swarm algorithm (GPSA) to solve mixed-integer optimization problems. As the results, our MGO simultaneously designed more than 3 patterns of gearbox in a single run that satisfies all design constraints. The averaged number of designed pattern was 14.18.

View full abstract