In inspection of structural members of buildings using the ultrasonic time-of-flight computed tomography (TOF CT) system previously developed by the authors, the reconstructed images did not always reflect their internal states appropriately, since no consistent technique for determination of TOF of ultrasonic signals had been clearly established yet. Hence, the authors have proposed the “squared amplitude integral method” for determination of the TOF now. In numerical simulations of wave propagation in circular cross sections of 24 cm in diameter, the TOF values have been obtained with the use of the proposed method, and fine CT images which well reflect the insides have successfully been reconstructed from the data in accordance with the filtered back projection algorithm. To verify the effectiveness of this method experimentally, the authors have tried to reconstruct the cross-sectional image of cylindrical mortal specimens of 25 cm in diameter with their ultrasonic TOF CT system. As the result, the artifacts of low sound-speed region near the circumference have been well suppressed and the size and position of the anomaly have been more precisely represented in the image compared with the previously obtained ones.
As the size of systems to be controlled gets larger, distributed optimization with Event-Triggered messaging is becoming one of the significant topics, where each local optimization problem is solved by an individual computer in parallel and in a synchronize manner to derive a global optimal solution more quickly and robustly than centralized methods while passing messages when certain events are triggered to keep communication costs low. However, most distributed optimization techniques require a supervisor system which monitors the progress of the optimization algorithms and stops them when an optimum solution is reached. In this paper, the authors propose a diffusion based stopping criterion for distributed optimization algorithms with event triggered messaging. The authors then compare the standard supervised criterion and the proposed diffusion based criterion by numerical simulations to show that the latter method does not add any overhead.
The objective for this article is to control a vehicle that is nearing rollover to return back to its original state using nonlinear model predictive control (NMPC). The continuation/generalized minimal residual (C/GMRES) is used to solve the optimal control problem to make NMPC possible in real-time. A suspension vehicle during rollover is represented by a double inverted pendulum with a nonlinear suspension system. The ground or road surface dynamics must be taken into consideration during the calculation of NMPC to smoothly control the vehicle back to the ground surface. A dissipated spring is used to represent the road surface behavior. The input force to return the vehicle back to its normal state is determined based on the surface friction coefficient and the location of the vehicle's center of gravity. The results obtained from our simulations indicate that NMPC with C/GMRES can swing the vehicle down to the normal position on the ground surface fast or smoothly depending on the problem setup.
This study provides a comparison of three methods, i.e., standard locally weighted averaging (LWA), least-norm solutions, and l1-minimization, for model-free predictive control based on Just-In-Time modeling and database maintenance for an unstable system. In contrast to conventional model predictive control, the model-free predictive control method does not use any mathematical model; rather, it uses the past input/output data stored in a database. Although conventional stabilizing feedback is used to obtain the input/output data of an unstable system, model-free predictive control is assumed to be used without it. Three methods based on standard LWA, least-norm solutions, and l1-minimization are statistically compared using a simple model. The results show that the methods of least-norm solutions and l1-minimization are superior to that of LWA. The method by l1-minimization yields tracking errors smaller than that by least-norm solutions; however, the method by l1-minimization requires a long computational time. In addition, the effectiveness of a method of database maintenance is illustrated by numerical simulations.
This paper concerns stable stabilizing controllers for a remotely driven acrobot (RDA) moving in a vertical plane, which is a 2-link planar underactuated robot whose second link is remotely driven by an actuator mounted at a fixed base through a timing belt. When only the angle of each link is measurable, first, this paper proves that stable controllers exist for a local stabilization of the upright equilibrium point (with two links in the upright position) of the RDA by using an output with an adjustable parameter. This paper shows the range of the adjustable parameter for the existence of the stable stabilizing controllers for the RDA. Second, this paper presents a second-order (reduced-order) stable controller for stabilizing the upright equilibrium point of the RDA by showing how to choose the adjustable parameter, and provides a third-order (reduced-order) stable stabilizing controller by using an existing design approach. This paper carries out simulation investigations to validate the presented theoretical results and to compare the performance of a second-order stable stabilizing controller with those of a third-order stable stabilizing controller and a fourth-order observer-based stabilizing controller from the perspectives of the attractive region for the local stabilization and the ability against the unmodelled friction dynamics.