This paper proposes a novel quasi-preview control method for structural vibration control using real-time seismic wave data from multiple remote observation sites and structural response. The method uses an adaptive filter based on a polynomial dynamic model to estimate the future seismic waveform at the controlled structural system. The coefficients of the adaptive filter are updated with the normalized least mean square (NLMS) method in every sample period. The estimated waveform is used for feedforward control, while the structural response is used for feedback control. The control strategy is referred to as the quasi-preview control. We also incorporate a switching mechanism into the quasi-preview control to select the optimal control input from multiple candidates of control inputs obtained from the multiple remote observation sites based on a performance index. The performance index involves the one-step-ahead prediction of the structural response obtained by the model of the structural system and the control input candidate to perform the switching action. All design parameters in the quasi-preview control are optimized with the particle swarm optimization (PSO) algorithm. We demonstrate the proposed quasi-preview control method through simulations with recorded data of a major seismic event. The proposed method achieves superior control performance compared to a conventional LQR feedback control method. The proposed method also enhances the robustness of the control system with the switching mechanism by using multiple observation sites.

In future space missions, cooperative attitude control is required for essential tasks with multiple spacecraft, such as satellite constellations. In recent years, spacecraft have increased in size and weight, necessitating infinite-dimensional systems. This paper discusses a leader-follower attitude consensus control of a multiagent system with multiple flexible spacecraft. Each flexible spacecraft consists of two flexible structures and a rigid hub, and its dynamic behavior is given by a hybrid PDE-ODE model. For this controlled system, to achieve attitude consensus control and suppress the elastic vibration of the system simultaneously, we propose a distributed boundary controller and show that the controller exponentially stabilizes a closed-loop system. We also investigate the closed-loop system’s stability in the context of varying communication topologies and in the presence of disturbances. Finally, we carried out numerical simulations to validate the effectiveness of the proposed controller.

This study addresses the challenge of suppressing residual vibrations in container by integrating feedback control mechanisms. Conventional input shaping control alone proves insufficient, particularly in the presence of external disturbances. To overcome this limitation, the study proposes the incorporation of an Active Mass Damper (AMD) and a driving mechanism. A testbed was constructed, utilizing a ball-screw mechanism connected to an AC servomotor for trolley movement. Wires connected the payload to the trolley, with an AMD employing a linear motor mounted on the payload. Acceleration of the payload was measured through an accelerometer, while encoders tracked linear positions of the trolley and the active mass. The Negative Acceleration Feedback (NAF) Control algorithm was employed, and the stability of the control system was theoretically investigated, followed by numerical simulations. Both numerical and experimental results demonstrate that the proposed control system effectively suppresses payload vibrations with additional feedback control to the trolley motion. The study establishes both theoretical and experimental success in employing the proposed control technique for container vibration control.

In casting, removing surface defects such as burrs is a crucial finishing process. Burrs, which are unwanted convex defects formed during casting, can adversely affect the product's functionality and aesthetics. This research aims to develop a robotic control system to automate burr deburring from complex-shaped surfaces. The system integrates a compact tool capable of accessing narrow gaps with a 6-degrees-of-freedom robot arm, enabling precise operation in confined spaces. To address the challenge of tool deflection during machining, the proposed system employs feedback control that utilizes both tool-tip reaction forces and position. By regulating the tool feed velocity to maintain a consistent machining reaction force, the system achieves highly accurate and efficient material deburring. Deburring experiments were performed to determine appropriate feedback control parameters. The PI control parameters were determined based on an evaluation of the responsiveness and vibration of the machining reaction force, and the target machining reaction force was determined by evaluating the residual height of the workpiece. The results showed that adjusting the tool feed velocity and compensating for tool deflection using machining reaction force in real-time significantly improved machining accuracy. Furthermore, the target value of the machining reaction force was found to directly influence the quality and speed of the process, with appropriate values ensuring precise and efficient finishing. The system's versatility was validated through experiments on various casting materials, including carbon steel (S50C), aluminum alloy (A7075), and cast iron (FCD4). Analysis of the experimental data revealed a strong correlation between material properties and appropriate control parameters, suggesting that material properties can streamline parameter determination. This adaptability makes the proposed system a promising solution for enhancing productivity and consistency in industrial casting processes.

In a mass measurement system using relay feedback of displacement, an object to be measured was guided mechanically by leaf springs to restrict its motion to a single translation. Such a mechanical guide produces restoring force that affects the estimation of mass based on the measured periods of oscillation. However, such effects on mass measurement have not been studied sufficiently. In this research, an experimental device is designed and manufactured to verify the analytical results experimentally. The nonlinearity of the spring is compensated by feeding back the deflection of the spring. Mass measurements are conducted with this device. The measured results support the analytical results.

In recent years, fueled by both the improvement of communication technology and societal changes fueled by the COVID-19 pandemic, the demand for various online classes and courses has increased, especially for physical education and music lessons. However, current online lessons are limited to instruction through screens, an inadequate approach that lacks precision and efficiency. For more efficient teaching, this study measured upper body movements using inertial sensors, which are inexpensive and have few spatial limitations, and focused on piano playing because it requires high precision for measurement movements. We calculated a performance technique called tremolo, in which two notes separated by the pinky and the thumb are quickly and alternately repeated. A wearable hand-movement-measurement system using an inertial sensor was attached to one skilled subject and several novices, and a movement model was constructed to obtain each joint’s angle. Singular value decomposition was performed on the obtained joint angles of the hand and the arm to evaluate the characteristics of the movements, and we investigated how the tremolo of the novices changed when their learning was based on the characteristics of the skilled subject. Every novice’s movement results approached the movements of the skilled subject before and after the teaching, and the order of the improvement rates of the movements of each subject was consistent with the order of the improvement rate of their tremolo skills. By analyzing and extracting the characteristics of the skilled subject’s tremolo, we confirmed that the novices learned the skilled subject’s tremolo and improved their own skills.

In recent years, there is a gap in the life expectancies between the average and the healthy populations of the aging society of Japan. One factor that influences the decline in healthy life expectancy is muscle weakness due to sarcopenia. Its symptoms tend to be accelerated when patients are forced to remain bedridden during treatment for various illnesses or injuries. Therefore, better prevention methods must be developed for sarcopenia that can be used during bed rest. This study establishes a new prevention method for sarcopenia by focusing on the soleus and gastrocnemius muscles. We developed a rehabilitation device that adjusts the ankle joint angle to a specified slant in a specified time while measuring the load on the foot. Our rehabilitation device was developed based on an orthosis to which we attached a mechanism that adjusts the ankle joint. By promoting dorsiflexion by tensing a belt fixed at two points on both the toe and knee sides, a prototype was fabricated using a servo motor as a power source. We created a control system through which the device adjusts the ankle joint angle to a target angle within a target operation time and experimentally verified the device operation with five subjects. Our prototype was able to dorsiflex and plantarflex at specified angles. Most significantly, except for a few results, both the dorsiflexion and plantar-flexion movements were completed approximately 10% more quickly than the target operation time. If we can integrate a training program that accounts for differences in muscle fibers into the device and demonstrate its effectiveness, we believe that it will contribute to the enrichment of rehabilitation methods for preventing sarcopenia in bedridden patients.

This study focuses on the transient response in a bowed string with the stick-slip vibration for the clear understanding of its behavior and tone at the beginning of playing. Helmholtz waves can be observed in a bowed string instrument such as a violin, and many researchers have studied the phenomenon, focusing on its unique movements and the mechanism of sounds. However, the transient response in a bowed string has not yet been completely clarified, and little research exists on it. Thus, this paper investigates multiple Helmholtz waves in the transient response occurring in a bowed string using numerical simulation. In the analytical model considered in this paper, the string is a damped free vibrating system of discretized masses connected by springs. The bow and the string are in contact at a single point, and the frictional characteristic is modeled as a function of the relative velocity between the bow and the string with a negative gradient to the velocity. It is confirmed that multiple Helmholtz waves can be observed as a transient response by calculating the behavior of the string using the analytical model, and that the multiple Helmholtz waves can be separated into several Helmholtz waves approximately. The number of Helmholtz waves induced by bowing and the process from the transient response to the steady state are examined by separating the original multiple Helmholtz waves into several Helmholtz waves.

This paper discusses a trajectory tracking control problem for the development of autonomous vehicles. The reference trajectory is generated by a kinematic model which is nonholonomically constrained not to skid at the rear drive wheels. A nonlinear dynamical controller to follow the trajectory is proposed by applying backstepping (BS) method, together with Dynamic Surface Control (DSC) to solve the so called “problem of explosion of terms in the BS method”. Ultimate boundedness of the closed-loop system is investigated. Finally, simulation results illustrate the effectiveness of the proposed controller.

Recently, touch screens have been used to operate smartphones and personal computers. When touch panels are used to operate devices, somatosensory feedback cannot be enjoyed. This lack of somatosensory feedback increases the reliance on visual feedback to provide a sense of operation. This may reduce device operation performance. Therefore, it is necessary to gain a sense of operation through somatosensory feedback. However, the quantitative evaluation of the relationship between somatosensory feedback and the perception of button operation is still insufficient. The purpose of this study is development of a system to quantitatively investigate influence of the button press operation elements on its recognition by the somatic perception. In this paper, improvement of an experimental apparatus designed for the quantitative evaluation is reported. The apparatus consists of a voice coil motor, leaf springs, a displacement sensor, a force sensor and a key top and can control vertical displacement and force. The kinesthetic sensation of pressing a physical button can be emulated with the apparatus. The design of the voice coil motor was improved based on results of the numerical magnetic field analysis. Observation of improved response and additional improvement with feedback control are also mentioned. Trial presentation of button press sensation is described. To discuss influence of hysteresis characteristic in the profile, results of sensory test with thirty participants are also reported.

Preventing falls is crucial for the elderly, and as an initial step, accurately quantifying their current balance abilities is essential. In this regard, the Center of Pressure (COP) has gained attention. This study proposes a novel mechanical model to accurately reproduce the human COP. If the proposed model can reproduce the human COP with high accuracy, it would enable the quantitative representation of human balance motion characteristics using model parameters. In this study, we first measured the time series of COP in a standing position from six subjects and constructed the Probability Density Function (PDF) of human COP. To reproduce this PDF, we propose a mechanical model that considers the human body as an inverted pendulum and the human foot as a triangular rigid body supported by viscoelastic material. The model control involves PD control incorporating randomness and dead-band effects. As a result, the proposed model successfully reproduced the characteristics, such as unimodal-peak and bimodal-peak patterns, observed in the human PDF by adjusting the control parameters. Specifically, the reproduction accuracy, which represents the agreement between the human and model PDFs, was over 87%, with an average of 96%. Moreover, we investigated the effect of model parameters on the PDF shape and clarified that increasing the effects of the PD control gain led to the emergence of unimodal-peak characteristics, whereas decreasing the gains resulted in bimodal-peak characteristics. Based on these results, we confirm that our proposed model can effectively parameterize human balancing behavior as observed in the PDF of COP.

Active space debris removal is required for upper-stage rocket bodies, and removal satellites need to recognize the circular shape of the upper-stage rocket body as a visual marker and approach it by utilizing on-board visual sensors. However, the lighting conditions make it difficult to observe the target stably. Moreover, limited power resources of removal satellites is also a limitation. This study proposes a method to detect the circular shape of upper-stage rocket bodies using an event camera as a visual sensor, which is robust to lighting conditions and has low power consumption. The output of an event camera becomes sparse when the relative velocity to the target is low, making ellipse tracking challenging. To address this, this study proposes a method to accumulate events over a defined period and track ellipses based on the number of accumulated events. Additionally, a passivity-based control method utilizing ellipses tracked by the navigation system is proposed for guidance and control. Simulations were conducted to verify the robustness of the proposed method under varying sunlight conditions.

In this study, we proposed a control method for an active mass damper (AMD) based on model predictive control (MPC) using mode response in super high-rise or mid-to-high-rise buildings. MPC derives the optimal control input within defined constraints, such as the stroke, speed, and thrust of the AMD device, by predicting the future behavior of the controlled object using a mathematical model for each control cycle. When MPC is applied to control building vibrations, first-order modes with large responses dominate as control targets because building responses, such as displacement and velocity, are directly fed back to the control system. However, in super- and mid-to-high-rise buildings, the acceleration response increases owing to the effects of higher-order modes during earthquakes. In such cases, controlling higher-order modes is challenging. The proposed AMD control method controls multiple modes, including higher-order modes, while considering constraints such as the stroke and thrust of the AMD by estimating the modal response using a linear Kalman filter based on the observed building response observed during earthquakes and using the modal response for model predictive control. We verified the effectiveness of the proposed method in reducing the response to seismic disturbance through numerical analysis and shaking table tests using a six-story shear model.

In order to maintain good track condition, and to keep safety and ride-comfort, managing wheel load variation is important especially for high-speed railway. And wheel load variation is strongly affected by vehicle’s unsprung mass, so reducing unsprung mass is very effective in reduction of wheel load variation. However, reducing unsprung mass drastically is not easy. This is because unsprung parts support the weight of the vehicle and are the most important safety components. Therefore, in this paper, the effects of track and vehicle factors on wheel load variation were evaluated in order to investigate methods to suppress wheel load variation effectively, other than reducing unsprung mass. In evaluating wheel load variations, we focused on wheel load variations when the vehicle runs over short-wavelength longitudinal irregularities of about 5 m wavelengths on the ballast truck. This is because 5 m wavelength longitudinal irregularities are outstanding on the Tokaido Shinkansen recently and large wheel loads are often observed at 5 m wavelength longitudinal irregularities. Therefore, it is considered important to suppress wheel load variations at short wavelengths longitudinal irregularities of about 5 m in order to maintain good track conditions. First, we modeled track and vehicle as a multibody dynamic simulation that can run over a set of rail irregularities. Next, by simulating hanging sleepers, it was shown that the characteristic wheel load waveform and peak values on longitudinal irregularities of about 5 m could be reproduced. This indicates that the hanging sleeper is the cause of the large wheel load variations on longitudinal irregularities of about 5 m. Finally, we changed track and vehicle factors and estimated the effect of those changes on wheel load variation. And we have shown that it is important to increase the bending stiffness of the rails and reduce the track support stiffness in order to reduce wheel load variations, not only to reduce unsprung mass weight on the longitudinal irregularities of about 5 m.

Actuators capable of performing both rotational and vertical movements are being developed in the manufacturing industry to enhance the area productivity. These actuators exhibit nonlinear characteristics in which the torsional stiffness of the rotational axis changes with the vertical displacement, causing variations in the mechanical resonance frequency. Applying final-state control (FSC) to such nonlinear systems typically requires repeated calculations, resulting in a high computational load. However, if a system with a torsional stiffness that is dependent on the vertical displacement can be modeled as a time-varying system, repeated calculations become unnecessary. This study investigates the effectiveness of time-varying final-state control (TVFSC) for such actuators. An experimental setup simulating the actuator is constructed, and its performance is evaluated through simulations and experiments. First, FSC and frequency-shaped FSC (FFSC) inputs are designed based on a rigid-body model, demonstrating that while FFSC effectively suppresses residual vibrations, it increases the feedforward (FF) input amplitude compared to FSC. Furthermore, when the FFSC input is designed to have the same amplitude as the FSC input, the positioning time increases, revealing a trade-off between vibration suppression and FF input amplitude. In contrast, the TVFSC input maintains a waveform nearly identical to that of the FSC input while avoiding an increase in amplitude. Experimental results confirm that, although the TVFSC input does not completely eliminate residual vibrations as in simulations, it achieves vibration suppression comparable to FFSC. Moreover, TVFSC eliminates the need for trial-and-error tuning for frequency shaping, making it more practical for implementation. These findings suggest that TVFSC provides an effective and computationally efficient alternative to vibration-suppressed positioning control in actuators with displacement-dependent stiffness.

Ballistocardiogram (BCG) is the repetitive body movements related to cardiac cycle. By using non-invasive sensor embedded in a car seat, the sensor reads the vibration caused by the BCG as minute voltage at any time while driving, making it possible to measure heartbeats without being restrained and to obtain the occupant's biological information. However, BCG motion measurement while driving is difficult due to the incorporation of road noise whose magnitude is usually larger than the undisturbed BCG signal. In this study, we propose a method to extract a BCG signal from a mixture of the BCG and road noise contained in a piezoelectric film sensor using online auxiliary-function-based independent vector analysis with iterative source steering (online-AuxIVA-ISS). A device simulating BCG was placed on a seating surface, while two sensors were embedded in a seat cushion. A shaker was used to reproduce road noise disturbance on estimating the BCG. Data from the two sensors were separated into two independent signals using the online-AuxIVA-ISS. We confirmed the effectiveness of the proposed method through dynamic experiments and that the BCG-simulated signal and road noise could be separated under a moderate load on the piezoelectric film sensor.

Residual stresses generated by machining operations affect the dimensional accuracy and fatigue strength. However, fatigue strength can be improved by applying compressive residual stress through surface modification such as peening and carburising. If the three-dimensional residual stress of various surface finished materials can be identified, it will be possible to evaluate the quality and consider the optimal surface-finishing method. Currently, methods for identifying residual stress include repeated surface measurement using X-ray diffraction and electropolishing. However, since electropolishing releases residual stress, the original residual stress cannot be accurately measured. In addition, neutron diffraction is only available at specialized facilities and cannot be used on-site. Therefore, a three-dimensional residual stress estimation method using eigenstrain theory and X-ray diffraction has been proposed. This method uses an inverse analysis to estimate the eigenstrain, which is the source of residual stress, from the surface elastic strain measured non-destructively by the X-ray diffraction method. The three-dimensional residual stress distribution can be obtained by inputting the estimated eigenstrain into a finite element model. The purpose of this study is to propose an inverse analysis method that enables relatively accurate estimation of the three-dimensional residual stress in peened materials using X-ray diffraction and the eigenstrain theory. In order to demonstrate the effectiveness of this method, numerical simulations and demonstrations were carried out. The application of the method to a model assuming a laser shock-peened residual stress field showed that the three-dimensional residual stresses could be estimated with relatively high accuracy using this method, even when measurement errors were taken into account. The method was also applied to an actual laser shock-peened material, and the estimated residual stresses were compared with those measured by the X-ray diffraction method. As a result, although further improvement in the estimation accuracy is needed, the residual stresses estimated by this method show a rough distribution trend with respect to the measured residual stresses.

A modified perturbation method (MPM) is applied to obtain the solution of the heat transfer equation for convective fins with temperature-dependent thermal conductivity. In this method, the nonlinear term is split into linear and nonlinear terms to obtain the perturbation solution. The solution of a convective fin with linearly temperature-dependent thermal conductivity by the MPM is simple to use and very accurate. Calculated results show that the solution by the MPM agrees well with the FDM (Finite Difference Method) solution in a wide range of the small parameter ε (thermal conductivity parameter), whereas the solution by the conventional perturbation method (CPM) is accurate only in a small range of ε. For example, the RMS error δ_RMS of the MPM solution with respect to the FDM solution is less than 10^-4 for N (fin parameter) = 1 and -0.505 ≤ ε ≤ 10, on the other hand the RMS error of the CPM solution is less than 10^-4 for N = 1 and -0.141 ≤ ε ≤ 0.142. The fin efficiencies obtained by the CPM, MPM and FDM are examined. The modification of the perturbation method by splitting the nonlinear term helps reduce the contribution of the nonlinear term upon the solution, which drastically improves the convergence characteristics of the solution.

In the realm of human-robot collaboration, impedance and admittance control are widely utilized techniques to regulate the interaction dynamics between humans and robots. This study proposes a novel approach to enhance the performance of human-robot collaboration by adapting the damping profile used in admittance control. The proposed method employs Bayesian optimization to appropriately adjust the damping profile, even when the cost function and unknown constraints are computationally expensive to evaluate, which is a common scenario in human-robot collaboration. Furthermore, the proposed approach can accommodate diverse types of constraints, enabling the incorporation of prior knowledge as constraints and accelerating the learning process. Specifically, constrained Bayesian optimization, which utilizes both Gaussian process regression and classification models, was implemented to learn damping profiles while considering task success rates. Additionally, a dynamic time warping technique was employed to handle task failure evaluations during the learning process, effectively mitigating the influence of outlying observations. Furthermore, prior knowledge regarding the damping profile is incorporated as a constraint to improve the learning performance. Extensive simulations and real-world experimental evaluations with a 7-DOF robot arm demonstrate that the proposed method can generate appropriate impedance parameters, exhibiting a substantial advantage over conventional impedance-learning methods in terms of learning performance.

A person capable of using more than one of four limbs simultaneously for manipulation can also be expected to be capable of performing concurrent and complex tasks and improving work efficiency. However, to our knowledge, no studies have investigated simultaneous tasks that require multi-degree-of-freedom manipulation, particularly those in which the lower limb engages in the same task as the upper limb. In this study, we developed a system to evaluate work performance and subjective mental workload using reaching movements with multiple limbs. To foster comparisons among various manipulations, experiments were conducted with single manipulation by a hand or a foot, simultaneous manipulation by the homologous limbs (left-hand_right-hand, left-foot_right-foot), simultaneous manipulation by the ipsilateral heterologous limbs (left-hand_left-foot, right-hand_right-foot), and simultaneous manipulation by the contralateral heterologous limbs (left-hand_right-foot, right-hand_left-foot). The processing time and accuracy of each limb were lower during two-than one-limb manipulation. In other words, a bilateral deficit tended to be seen. When manipulating with two limbs, manipulation with the homologous limbs was significantly superior to that with the heterologous limbs in terms of processing time, accuracy, and mental workload. Because the work performance of a foot tended to be worse than that of a hand in the one-limb manipulation, the work performance of the two-limb manipulation using both feet was expected to be the worst in the two-limb manipulations. However, the experimental results showed that the work performance of the heterologous limbs was worse than that of both feet. Manipulation with the contralateral heterologous limbs tended to be superior to that with the ipsilateral heterologous limbs in terms of processing time, accuracy, and mental workload. Regarding two-limb manipulation, the homologous limbs tended to perform best, followed by the contralateral and ipsilateral heterologous limbs.

Driver assistance and automated driving systems on general roads are crucial for reducing traffic accidents and ensuring the freedom of mobility in aging societies. To foster trust in these systems, it’s essential to achieve vehicle movements that people perceive as natural. This paper aims to incorporate human driving characteristics, such as jerk minimization and coupled longitudinal and lateral motions, into path and speed planning for natural driving assistance and automated driving. To simplify the complex equations typically required when implementing these characteristics in a vehicle-fixed moving coordinate system without compromising rigor, we propose using a local fixed coordinate system along the road geometry. Our approach sets longitudinal and lateral motions as time polynomials within a predetermined time horizon. This allows coupling conditions to be transformed into polynomial parameter equilibrium equations, enabling the comprehensive application of optimization requirements like jerk minimization. Consequently, optimal path and speed plans can be derived by solving a system of linear equations at each time step. We also develop a strategy for coupling gain management to suppress transient vehicle jerk fluctuations caused by lateral acceleration sign reversals. The resulting path and speed plans demonstrate features similar to experienced drivers’ “out-in-out” driving paths. This method enables smooth path and speed planning for various road geometries while minimizing jerk and maintaining coupled longitudinal and lateral motion. Future work will involve verifying the system’s effectiveness using prototype vehicles and/or driving simulators.

The purpose of this study is to discuss the feasibility of utilizing active suspension systems to stabilize vehicle behavior during earthquakes, thereby preventing derailments. The vehicle is modeled as a quarter-car system represented by a model that possesses a total of ten degrees of freedom, accounting for the lateral, vertical, and roll motion of each vehicle component. Each rigid body of the vehicle is connected by springs and dampers. The characteristics of the stopper mechanism and secondary spring, located between the car body and the bogie frame, are modeled as nonlinear force elements. Actuators are installed in the lateral direction between the car body and the bogie frame, and control inputs are determined based on the optimal control theory. The control model has been designed to minimize the relative lateral displacement between the wheelset and the rail. Vehicle behavior simulations have been conducted using a model that incorporates only the passive mechanism, in addition to the controlled models. For the passive model, simulations are conducted not only with a standard damping coefficient but also with an increased damping coefficient. Comparisons of the passive model and the active controlled model reveal a tendency to prevent derailment in low frequency while inducing derailment in high frequency region. On the other hand, increasing the passive damping coefficient is expected to have a derailment prevention effect in the high-frequency region, whereas no such effect is observed in the low frequency. Therefore, the effectiveness in preventing derailment in the low frequency region is a characteristic of the active control. These findings indicate the feasibility of derailment prevention control using active suspension.