Type 1 diabetes (T1D) is a specific form of diabetes wherein the immune system destroys insulin-producing β cells until complete inability to secrete insulin. Patients with T1D require insulin therapy to maintain blood glucose (BG) levels within the desired range, although this is often difficult to achieve. To reduce the burden of the insulin therapy, closed-loop blood glucose control methods have been studied. In this review, we first introduce some important mathematical models of glucose-insulin metabolism, followed by some representative blood glucose control systems developed to date and discuss their implications in the near future.
The Ministry of Education, Culture, Sports, Science and Technology will enhance teaching with ICT at the elementary school curriculum guideline that will be fully implemented from fiscal 2020. It is necessary to research and develop the evaluation indicators and the evaluation methods for the objectively evaluating the transformation of students by "education with ICT". In this paper, the research results related to "skill visualization of student behavior data" that integrates the education field and the engineering field are introduced. Specifically, "skill model estimation of ability for reading drawings" and "parameter estimation of a skill evaluation model" are introduced.
It is well known that some major control specifications, e. g., a sensitivity reduction, guarantee a stability margin, disturbance attenuation and etc, can be achieved by shaping frequency responses of open-loop transfer functions. In this paper, control system design methods which shape the frequency response of the open-loop transfer functions with a numerical optimization are shown.
Recently, many researches extracting an essense from a huge number of data receive much attention in the various field of engineering. In the field of control engineering, the controller sysntheses from time-domain and/or frequency-domain data are energetically studied based on numerical optimization techniques. This paper presents a recent development of data-based controller synthesis by convex optimization, and shows that a special case of nonconvex optimization problems, which is often encounterd in the control field, is reformulated as a convex optimization problem by introducing the Concave-Convex Procedure or the Iterated LMI constraints. As an application, the H∞ loop shaping design procedure reformulated using frequency response data of a controlled plant is presented.
This paper introduces Model-Reference Robust Tuning (MoReRT), where the trade-off relationship between the tracking performance and the robust stability is designed. Firstly, the design objective of MoReRT and its feature are given. Secondly, the model-based design methods are shown for the design methods for the continuous-time control system, the discrete-time control system and the sampled-data control system, respecitvely. Finally, the data-driven design method is introduced.
The grid connection inverter is built in the PCS (Power Conditioning Subsystem) for the distributed power supply, such as photo voltaic system. In order to utilize the power source, it is necessary that the grid connection inverter of the PCS predicts the load and output fluctuation in customer side. Therefore, this paper investigates a load estimation in the grid connection inverter of the PCS. The proposed estimation method adds superimposing perturbative signals in the inverter reference. The validity of the proposed estimation method is experimentally verified. In addition, the perturbative signals for load estimation consist of three different frequency components. As the result, it is experimentally clarified the proposed method improves the estimation accuracy.
This paper discusses a design method for a single-input single-output multi-rate sampled-data control system, where the sampling interval of a plant output is an integer multiple of the hold interval of a control input. In such a sampled-data control system, the intersample output can oscillate even if the sampled output converges to the reference input. Because of the oscillation, heavy load is on the actuator, and the control performance is deteriorated. To resolve the problem, in a conventional method, a control law is extended using the null-space, and the intersample response is improved such that the sampled response is maintained. The conventional method has been designed based on the transfer function representation. In the proposed method, on the state-space representation, the null-space is introduced, and the existing control system is extended. Finally, through numerical examples, the effectiveness of the proposed method is verified.
ASPR based output feedback adaptive control system for input saturated systems sometimes causes a degradation of control performance or the destabilization of the system when input is saturated. In this paper, we propose a design method of output feedback adaptive control system with an anti-windup compensator aimed at improving control performance in transient state. Moreover, the effectiveness of the proposed method will be confirmed through numerical simulations.
In this paper, we consider the consensus control of multi-agent systems with quantized signal communication. In such a network system, when the static quantizer is used, the control performance is degraded because of the influence of the quantization error. To compensate the quantization error, in a conventional method, a probabilistic quantizer is used. On the other hand, in this paper, the dynamic quantizer is introduced instead of the static quantizer. Because the dynamic quantizer is optimally designed, the control performance of the proposed method can be improved better than the conventional methods. Finally, the effectiveness of the proposed method is demonstrated through numerical examples.
This paper considered a backward path-tracking control method for an articulated vehicle. One of the most effective method in this research area is the exact feedback linearization based approach. Although this method can design the control law systematically, the controller has singular point that the control law cannot be defined. One such a singular point is the situation which the angle between a tractor and a trailer is the right angle. To avoid such an uncontrollable situation and improve the control performance, we proposed a method which is added a new input to the exact feedback linearization controller. This additional input constraints the change of the angle and avoids the vehicle to approach the singular point. The stability of the additional input was discussed by the Lyapunov's direct method. To confirm the effectiveness of our proposed method in actual use, we carried out the tractor-trailer model experiment. In this experiment, the FastSLAM method was employed to estimate the location of the model. The experimental result indicated that our proposed method was fasible even if the actual system.
This paper proposes a desing method of smart strong stability system based on self-tuning controller, which is defined as strong stability system that the ratio of closed-loop and open-loop gain is near to 1. The proposed method can design the controller independently to the closed-loop transfer function by extending generalized minimum variance control.
This paper discusses a design method for dual-rate systems, in which the sampling interval of the plant output is an integer multiple of the holding interval of the control input. In such dual-rate systems, even if the sampled output follows the reference input the intersample output might vibrate because of the disturbance. In this paper, a new design method is proposed so that a dual-rate control law is extended independent of the disturbance response as well as the reference response in discrete time.
In this paper, we propose a design method of an adaptive control system for input redundant 2 input 1 output system. The feature of the proposed method is that the control input can be adjusted by an arbitrary external signal by utilizing the degree of freedom of the control input in the input redundant system, and the reference model output tracking can be achieved. A numerical example is shown at the end of this paper, and the proposed method is verified.
Because almost strictly positive real (ASPR) condition can be satisfied using the parallel feedforward compensator (PFC), the stable control system is easily designed with simple adaptive control (SAC) method. The augmented system output, in which the PFC is included, converges to the reference model output, and on the other hand, there is the steady-state error between the actual system output and the reference model output because of the PFC. In this study, an SAC law is extended using the null-space and it is applied to a rotation control system.
In the junior high school learning guideline (technology education) since FY2012, there is "D-(3) Automatic measurements and controls via computer programs" in "Technology of information processing" and it is compulsory. In this study, the following developments were made and evaluated on the contents of “measurement and control” instructed in junior high school technology education. (1) Learning contents and goals of measurement and control, and (2) Development of teaching materials such as illumination light and sensor car. In developing these teaching materials and teaching materials, I considered "the relationship between our lives and technology" and "the practical and hands-on learning activities".
In this paper, we propose a novel control method which combine collision avoidance method and RISE(Robust Integral of the Sign of Error) for multiple Quad-rotor formation control methods for cooperative control, and confirm effectiveness of this method by experiment using actual Quad-rotor. First, this work describes a method to suppress nonlinear disturbance using RISE which is a type of sliding mode control. In addition, collision avoidance method and the conditions to achieve accurate formation are explained. Finally, the effectiveness of proposed method is confirmed functioning correctly, by implemented an algorithm in the actual Quad-rotor.
In this paper, A student in the teacher training course learns the basic theory and principle of operation in the field of control, and through basic experiments and practices, basic concepts related to sequence control and feedback control, which are the main handling items within the course of electronic measurement control and mechanism. It aims to propose a lesson curriculum that can be learned experientially with respect to properties. Lecture on the proposed curriculum. Also, conduct a questionnaire to students. As a result, we analyze students' understanding of measurement and control from questionnaire data and verify effectiveness.
PID controllers have been widely employed in real processes. Since PID gains strongly affect the control performance, lots of schemes for tuning PID gains have been proposed. Recently, data-driven PID tuning schemes which determine PID gains directly from the closed-loop operating data attract attentions. Lots of controlled objects are multi-input and multi-output systems, though almost data-driven PID tuning schemes target single-input and single-output systems. In this paper, a data-driven multi-loop self-tuning PID controller design is proposed. The proposed scheme first employs a post-compensator to remove mutual interference. Multi-loop self-tuning PID controller is designed for the decoupled system. The effectiveness of the control scheme is evaluated by a simulation example.
In this paper, an operator-based optimal equivalent load tracking control scheme for uncertain wireless power transfer systems is proposed. When the proposed control design scheme is adopted, the uncertain term could be dealt with by using the robust right coprime factorization approach, so the robust stability could be obtained. Then the optimal equivalent load for the coupling system can be matched to realize impedance matching without the acquisition of alternating current signal, thus the high efficiency could be obtained. Moreover, the reference signal of output voltage can be tracked. Simulation results are presented to show the effectiveness of the proposed control design system.
This paper considers the compensation of flow disturbance, which is the pressure variation of compressed air supplied to pneumatic anti-vibration apparatuses. In the case of single-loop control system, a notch filter is used as the tunable parameter of repetitive controller so as to reduce the transmissibility of pneumatic anti-vibration apparatus. On the other hand, in the case of multi-loop control system, the transmissibility is increased. To overcome this problem, a sky-hook spring approach is employed. It is shown that by using the proposed approach, the vibration caused by flow disturbance is attenuated and the transmissibility of pneumatic anti-vibration apparatuses is improved.
In the acoustic signal processing applications of finite impulse response (FIR) system identification, it is important to develop the identification method that is robust to super-Gaussian noises. Moreover, the identification method that estimates the FIR coefficients and the order of the unknown system is required, because the order of the unknown system is unavailable in advance. Therefore, in this paper, we propose a nonparametric Bayesian (NPB) model for FIR system identification using a super-Gaussian likelihood and the beta-Bernoulli process. In the proposed NPB model, we employ the hyperbolic secant distribution for the likelihood function. Then, we derive the inference algorithm to simultaneously estimate the FIR coefficients and the order of the unknown system. Our inference algorithm based on a hybrid inference approach combining the majorization-minimization (MM) algorithm and the Gibbs sampler. The simulation results suggest that the proposed method outperforms the conventional identification algorithms in a super-Gaussian noise environment.
Operations of the hydraulic excavator are difficult, and the productivity depends on operating skills. In order to improve the productivity of non-expert, it is necessary to quantitatively evaluate the operating skills difference between expert and non-expert. However, since a hydraulic excavator has the multi-link structure, the evaluation is not easy. In this paper, the evaluation system of skills which is expressed as the combined CoM (Center of Mass) of attachment is newly proposed. The system parameters are identified based on the motion of CoM at the boom up deceleration. Skills are estimated from these parameters, and the evaluation index is constructed.
In this paper, we propose a new data-driven controller parameter tuning method for the position control of mechanical systems by the semi-closed loop control. The proposed method is based on the Fictitious Reference Iterative Tuning (FRIT) approach, which enables us to obtain an appropriate controller parameter that improve the control performance in the load position using only one-shot experimental data. The feature of the proposed method is to use not only the output data of motor but also the output data of load to construct the cost function in FRIT. As a result, we can obtain an appropriate controller parameter that match the load position with the desired response. Finally, we provide some experimental results to show the effectiveness of the proposed method.
This paper shows a PI-D controller design method with a finite number of frequency responses(FNFR) model so that it stabilizes a closed-loop system and matches a transfer function of the closed-loop system to that of ideal model. In this paper FNFR model is introduced with a ratio of the discrete Fourier transformation of input and output signals. The main contribution of this paper is to propose a method to reduce the control problem to a convex optimization problem. The efficiency of the method with FNFR model is shown through experimental results via a magnetic levitation system.
This study proposes a new design method for a dual-rate cascade control system, in which the interval of the outer loop is longer than that of the inner loop. In the proposed method, the controller parameters are optimized off-line using the controlled data. The effectiveness of the proposed method is demonstrated through numerical simulations.
To maintain high performance of controlling and minimize the total cost for readjustments of the controller parameters, determination the appropriate timing for readjustment the controller parameters is important. This paper proposes a design of performance-driven control system to maintain the system performance by detecting the system change using the recurrent neural networks and readjusting the control parameters based on Fictitious Reference Iterative Tuning (FRIT). This paper conducts some numerical experiments to verify the availability of the proposed method to some systems.
Since the cranes are well used in many industrial situation, efficient crane control algorithm is required. The anti-sway control is one of the most important task. For anti-sway control of overhead crane, a deflection angle must be estimated. However, it is difficult to estimate deflection angle directly. Therefore, this paper treats an indirect measurement method for the angle by using two microphones. Here, we show a selection of initial solution to improve the convergence speed of the Newton's method. Also, we utilize a median filter to remove impulse noise from the angle. From experimental results, the number of iteration can be reduced by using the proposed method.
We treat an optimization problem for low delay FIR digital filters with sparse coefficients in the least squares sense. Sparse filters indicate that the coefficients include not only real value but also 0 coefficients. In this study, we consider l1 regularization scheme to solve the design problem for sparse filters. Here, we employ an algorithm for design of sparse FIR filters based on an accelerated proximal gradient method. Finally, we show examples to demonstrate the effectiveness of the proposed method by comparing with equivalent non-sparse filters and filters designed by FOBOS.
In the new education guidelines to be implemented from 2020, the programming education is introduced from the elementary school stage. The programming education at elementary schools is aimed at nurturing "Computational Thinking". So, we develop teaching materials using "Measurements and Controls via Programmings" to promote the computational thinking for elementary school students. And we held a workshop using the Learning materials. In this paper, we propose the learning materials and learning contents, moreover consider the utility of learning materials and learning contents from survey of the workshop.
In this paper, we design both an individual blade pitch controller (IBP) and a collective blade pitch controller for a floating offshore wind turbine. To design IBP, we obtain a linear time-invariant system from a linear periodic system by using the Multi-Blade Coordinate transformation. We evaluate the performance of two controllers and compare them using the high-fidelity wind turbine simulator, FAST. Nonlinear simulations with a vertical windshear condition show that the individual blade pitch control has a good blade fatigue loads reduction performance with regulating generator power by reflecting each blade position.
This paper proposes the state and parameter estimation method in order to compensate for random communication delay. By using time-stamp information, particle filter can be available even in the presence of the delay. The numerical simulation verifies that estimation error can be reduced by using the proposed method.
The Noniterative Correlation-based Tuning (NCbT) is known as one of the data-driven controller design methods. The NCbT guarantees closed-loop stability based on the small-gain theorem, which is a sufficient condition for closed-loop stability. As the result, the designed control performance might be conservative. This paper proposes the new stability constraint based on the Nyquist stability criterion to improve conservativeness for control performance. By improvement of conservativeness, the control system could reduce the stability margins, gain margin and phase margin. In order not to achieve low stability margins, the constraint for stability margin is additionally proposed. Since the gain and the phase margins are still commonly used indices for stability margins in industries, the direct designation of the gain and the phase margins in data-driven approach is highly appreciated. The effectiveness of the proposed constraints for stability and stability margins are confirmed by numerical simulations.
The paper proposes a linearly parametrized data-driven controller design method based on minimum variance evaluation. The approach updates control parameters that improves disturbance attenuation properties from regulatory control input and output measurements. The proposed method uses linearly parametrized controllers, and obtains sub-optimal control parameters based on variance evaluation. The paper considers a new data-driven cost criterion on the assumption that disturbance model is unknown. Then, the analysis using the approach of “Domain of Attraction (DOA)” is provided to confirm that minimization of the proposed cost criterion reduces the value of the original cost criterion. Finally, the paper shows the effectiveness of the proposed method through a numerical example.
This paper proposes a reference model design method for data-driven controller tuning using closed-loop step response data. The reference model design has a great influence on controller tuning. However, it is difficult to design the reference model on the condition that the mathematical plant model is unknown. The proposed method estimates an input of the closed-loop system consisting of a desired controller. By using the estimated input, unstable zeros are estimated and a reference model for non-minimum phase plants is designed by considering manipulated variable evaluation. Finally, the paper shows the effectiveness of the proposed method by using a numerical simulation.
The authors have pursued the application of Central Pattern Generator (CPG) in order to suppress flow disturbance caused by pressure variation of compressed air supplied to pneumatic anti-vibration apparatus (AVA). CPG has been used to improve performance by implementing it in the control system of walking robot. However, in any relevant documents, CPG was implemented in addition to stabilizing compensators. Meanwhile, this paper shows that the control system using only CPG can realize the stable levitation and the disturbance suppression simultaneously. In addition, the stable levitation by the proposed method is verified based on describing function.
This study proposes a data-driven control method for a dual-rate sampled-data control system, where the sampling interval of a plant output is shorter than the holding interval of a control input. The proposed data-driven method is based on an open-loop input/output data. Therefore, the controller parameter is optimized using only the one-shot controlled data. Finally, the effectiveness of the proposed method is demonstrated through a numerical example.
Spreading portable devices widely, the small MEMS on-board microphone IC is paid attention. The small and high-accurate sigma-delta modulator is used for the MEMS on-board microphone IC. The sigma-delta modulator must use amplifiers for the integrator. Due to using the integrators for high order noise-shaping characteristic, its power consumption increases. We proposed changing amplifiers to filters and confirmed 100dB of S/N+THD in the 20kHz audio band.
A 2-D torus network is one of the most popular networks for parallel processing. Many algorithms have been proposed based on the turn model, but most of them cannot be applied to a torus network without modification. In this paper, we mention the North-South First (NSF) routing that is applicable to a 2-D torus and combines the North-First method (NF) and the South-First method (SF). Our methods focused on the proposal of routing algorithms aimed at avoiding congestion of the coupled network, so we have not evaluated the fault tolerance. In fact, since the proposed method was a routing algorithm that guarantees the shortest path between source and destination, it was superior in congestion tolerance, but it was not known whether it had fault tolerance. In this paper, we evaluate the congestion tolerance of NSF by software simulation and evaluate the fault tolerance by simulation with faulty PE. Moreover, we propose an improved North-South First method (Improved NSF, NSF-IP) which is a new routing algorithm with improved fault tolerance by correcting the conventional NSF algorithm. For the proposed method, we evaluated both of congestion resistance and fault tolerance by dynamic communication performance evaluation by simulation. The software simulation showed that improved NSF method has higher performance.
An ultra-compact binary power plant converts thermal energy into electric power using low temperature difference thermal energy between heat source and cooling source. In control of the binary power plant, the negative effects such as characteristic changes caused by environmental condition and corrosion of related equipment, and coupling between control loops are the main difficulties in designing a controller and fine-tuning its parameters. In order to realize the stable power generation it is necessary to consider a control system to keep control performance when characteristic change of the binary power plant, and to compensate coupling in Multi-Input and Multi-Output (MIMO) systems. A Multiply-Connected (MC) Neuro PID control system using a Neural Network architecture connected directly by neurons of each control loop is proposed to overcome above difficulties, and its strategy for design of the control system is introduced. The proposed MC Neuro PID control system is compared to traditional control systems to show the effectiveness of the MC Neuro PID control through simulations in this paper.
This study covers the problem of information overload in workers of different occupations in a home medical care field. This system enables push notification of only highly urgent information by using COI (Conditions of interest) of each worker though specialized information sharing system.
The application of Central Pattern Generator (CPG) has been realized in order to suppress flow disturbance caused by pressure variation of air supplied to pneumatic anti-vibration apparatus (AVA) with one degree-of-freedom. In this paper, CPG is applied to pneumatic AVA with two degrees-of-freedom. First, experimental results show that stable levitation of AVA is possible by using only CPG without PI compensator. Next, the suppression performances of PI compensator and CPG are compared. As a result, the superiority of performance by CPG is confirmed.
In this study, we used a miniature electrocardiogram (ECG) data-logger and evaluated the physiological response of carrion crows (Corvus corone) to an auditory repellent stimulus. Three carrion crows had an average heart rate of 243 bpm before they were exposed to the auditory stimulus. Their heart rates increased significantly to 302 bpm on initial exposure to the auditory stimulus and decreased gradually as the stimulus was repeated.
On ETL processing using Pentaho, we propose automatic shortening processing time method by tuning each step concurrency level for Pentaho data transformation. It monitors queue length for each processing steps, and tunes number of threads for the step of longest queue length. For certain in-house data transformation target, proposed method can shorten processing time comparable to tune manually by expert.