Kou Miyamoto

Bio: Kou Miyamoto is an academic researcher from Shimizu Corporation. The author has contributed to research in topics: Control system & Computer science. The author has an hindex of 4, co-authored 11 publications receiving 58 citations. Previous affiliations of Kou Miyamoto include Japan Society for the Promotion of Science & Tokyo Institute of Technology.

Equivalent-input-disturbance approach to active structural control for seismically excited buildings

Abstract: A new method of active structural control, which suppresses vibrations in civil structures due to seismic shocks, has been developed. It is based on the equivalent-input-disturbance (EID) approach, which estimates the effect of a seismic shock and produces an equivalent control signal on the control input channel to compensate for it. A system designed by this method can be viewed as a conventional state-feedback control system with an EID estimator plugged in. Unlike conventional control systems, this one has two degrees of freedom, which yields better control performance. Simulations on a model of a ten-degree-of-freedom building demonstrated the validity of the method. In addition, the effect of the parameters of the low-pass filter in the EID estimator on the vibration suppression performance was examined. A comparison revealed that this method is superior to a linear-quadratic regulator and sliding-mode control.

A new performance index of LQR for combination of passive base isolation and active structural control

Abstract: This paper considers the problem of designing a state-feedback controller with both passive base isolation (PBI) and active structural control (ASC). In order to improve control performance, state-feedback gains are designed based on the linear quadratic regulator (LQR) method that optimizes a new performance index containing absolute acceleration, and inter-story drifts and velocity. Simulations on a model of an eleven degree-of-freedom shear building for four earthquake accelerograms are used to verify this method. Comparison studies show that, compared with PBI, the combination of PBI and ASC improves control performance; and this method yields better control results than the conventional ASC, which considers relative displacement and relative velocity of each story. The results are also discussed from the viewpoint of control system structure regarding the location of system zeros. In addition, the effect of weights in the LQR on control performance is discussed. A method for selecting the weights is presented by using the infinity norm of a system as a criterion to visualize their effect.

Automatic determination of LQR weighting matrices for active structural control

Abstract: This paper presents a method for the automatic selection of weighting matrices for a linear-quadratic regulator (LQR) in order to design an optimal active structural control system. The weighting matrices of a control performance index, which are used to design optimal state-feedback gains, are usually determined by rule of thumb or exhaustive search approaches. To explore an easy way to select optimal parameters, this paper presents a method based on Bayesian optimization (BO). A 10-degree-of-freedom (DOF) shear building model that has passive-base isolation (PBI) under the building is used as an example to explain the method. A control performance index that contains the absolute acceleration, along with the inter-story drift and velocity of each story, is chosen for the design of the controller. An objective function that contains the maximum absolute acceleration of the building is chosen for BO to produce optimal weighting matrices. In the numerical example, a restriction on the displacement of the PBI is used as a constraint for the selection of weighting matrices. First, the BO method is compared to the exhaustive search method using two parameters in the weighting matrices to illustrate the validity of the BO method. Then, thirty-three parameters (which are automatically optimized by the BO method) in the weighting matrices are used to elaborately tune the controller. The control results are compared to those for the exhaustive search method and conventional optimal control, in terms of the control performance of the relative displacement, absolute acceleration, inter-story-drift angle, and the story-shear coefficient of each story. The damping ratio for each mode, and the control energy and power are also compared. The comparison demonstrates the validity of the method.

A spectrum for estimating the maximum control force for passive-base-isolated buildings with LQR control

Abstract: The combination of passive-base-isolated (PBI) and active structural control (ASC) has been employed in many buildings globally to improve control performance. Controllers are mainly designed using the linear-quadratic-regulator (LQR) method, which minimizes the response and control force by using their weights. While the estimation of the required control force is important to select an appropriate actuator to perform ASC, previous approaches utilized trial-and-error because the dependency of the maximum control force on the natural period and the passive damper has not been expressed theoretically. To solve this problem, this paper presents a spectrum, namely a control-force spectrum, to estimate the maximum control force while considering the combination of PBI and ASC. An equivalent model of an ASC system is derived to describe the relationship between the vibration characteristics and the LQR weighting matrices. Using the equivalent model and the control-force spectrum, the maximum control force of an ASC system designed by the LQR method is estimated, and the appropriate maximum control force, natural period, and damping ratio are theoretically determined. This study also develops a design method for PBI construction with ASC that selects the natural period, passive damper, and maximum control force by using spectra without requiring trial-and-error and numerical simulations. A numerical design example validates the design method.

Active Structural Control of Base-Isolated Building Using Equivalent-Input-Disturbance Approach with Reduced-Order State Observer

Abstract: Active base isolation has been studied in the last few decades to improve the control performance of base isolation. As a two-degree-of-freedom active disturbance-rejection method, the equivalent-input-disturbance (EID) approach shows its validity for structural control. It uses a state observer to estimate the effect of disturbances on a control input channel. However, since the model of a base-isolated building has high degrees-of-freedom, a resulting control system has a high order. Thus, the use of a full-order state observer results in the complexity of a control-system implementation. To solve this problem, this paper presents an EID control system that uses a reduced-order state observer (ROSO) to reduce the expense of control-system implementation and ensure system reliability. First, the condition of using an ROSO in an EID control system is derived, and the configuration of an ROSO-based EID control system is presented. Next, the concept of perfect regulation is used to design the gain of the state observer. A stability condition of the system with prescribed control performance is derived in the form of a linear matrix inequality (LMI) that is used to design the gain of the state feedback. Finally, the seismic control of a base-isolated building demonstrates the validity of the method.

Novel metaheuristic-based tuning of PID controllers for seismic structures and verification of robustness

Abstract: In the present study, an active structural control using metaheuristic tuned Proportional-Integral-Derivative (PID) type controllers is presented. The aim of the study is to propose a feasible active control application considering time delay and a feasible control force. In the optimum control methodology, near-fault directivity pulse was considered for ground motion. Three different metaheuristic algorithms are separately employed in the optimum tuning of PID parameters such as proportional gain, integral time and derivative time. The employed algorithms are Flower Pollination Algorithm, Teaching Learning Based Optimization and Jaya algorithm. The maximum control force limit is considered as a design constraint. The methodology contains the time delay consideration and a process to avoid the stability problem on the trial results during the optimization process. The method is explained in three stages as The Pre-Optimization Stage, The Dynamic Analysis Stage and The Optimization Stage. The optimum PID parameters of different algorithms are very different, but the performance of active control is similar since a similar control signal can be generated by different proportion of controller gains such as proportion, integral and derivative processes. As the conclusion of the study, the amount of control force must be chosen carefully since big control forces may resulted with stability problems if the control system has long delay.

Active disturbance rejection vibration control for an all-clamped piezoelectric plate with delay

Abstract: All-clamped plate structures are usually subject to strong coupling, model uncertainties and system time-delay. To address these challenges, this work proposes a novel vibration control method based on a linear active disturbance rejection controller (LADRC) with time-delay compensation (TDC-LADRC). The mathematical model of the piezoelectric plate is first established based on system identification with an auxiliary variable method. Then ADRC is designed for the delay-free part by a smith predictor with a novel differentiator. An extended state observer (ESO) is drawn to estimate the internal and external disturbances, such as mode errors, higher harmonics and external environmental excitations. Then, real-time compensation is introduced via feed-forward mechanism to attenuate their adverse effects, so that optimal vibration suppression performance can be achieved by the proposed controller. Finally, based on NI-PCIe6343 acquisition card, an experimental set-up is designed to verify and compare the performance of the proposed TDC-LADRC against the traditional LADRC and the traditional predictor based LADRC (PLADRC). Comparative experimental results show that the proposed TDCLADRC possesses the best disturbance rejection and vibration suppression performance.

A new performance index of LQR for combination of passive base isolation and active structural control

Abstract: This paper considers the problem of designing a state-feedback controller with both passive base isolation (PBI) and active structural control (ASC). In order to improve control performance, state-feedback gains are designed based on the linear quadratic regulator (LQR) method that optimizes a new performance index containing absolute acceleration, and inter-story drifts and velocity. Simulations on a model of an eleven degree-of-freedom shear building for four earthquake accelerograms are used to verify this method. Comparison studies show that, compared with PBI, the combination of PBI and ASC improves control performance; and this method yields better control results than the conventional ASC, which considers relative displacement and relative velocity of each story. The results are also discussed from the viewpoint of control system structure regarding the location of system zeros. In addition, the effect of weights in the LQR on control performance is discussed. A method for selecting the weights is presented by using the infinity norm of a system as a criterion to visualize their effect.

Contour Tracking Control of Networked Motion Control System Using Improved Equivalent-Input-Disturbance Approach

Abstract: This article deals with contour tracking control of a networked multiaxis motion control system with repetitive tasks. To improve the control performance of the system under the overall effects of aperiodic time-varying delays and exogenous disturbances, a network-induced delay is first modeled to be a disturbance. Next, an improved equivalent-input-disturbance (IEID) approach is devised to suppress the overall effect. Then, an iterative learning controller is designed in combination with the IEID estimator to perform individual-axis tracking control. The stability of the system is analyzed using the separation theorem. After that, a cross-coupled controller is used to further improve the contour-tracking performance. Finally, simulations and experiments are carried out to verify the feasibility and effectiveness of the new approach.