Takao Sato

A data-driven design method for a cascade control system is proposed. The cascade control system consists of inner and outer loops, where the control interval of the outer loop is an integer multiple of the inner loop; hence, the system is a dual-rate system. In the proposed method, controllers in the inner and outer loops are designed based on one-shot data. In such a dual-rate cascade system, since the controllers are designed using different data-rate signals, the lifting technique is applied to align the dual-rate data. To show its effectiveness, the proposed method is compared with a conventional single-rate cascade control method, and numerical simulations and experiments are presented to examine servo and regulation performance.

For the next generation of manufacturing, represented by Industrie 4.0, a multi-input controller is designed directly from controlled data, without using the mathematical plant model, where the ratio between the D/A conversion of multiple inputs and the A/D conversion of a single output is non-uniquely. With the proposed method, the fixed-structured controller is optimally designed by solving a model reference problem using one-shot data. Furthermore, to eliminate inter-sample ripples emerged by input oscillation, the deviation of the control inputs is also evaluated using the proposed method. As a result, a non-ripple data-driven controller is achieved. Numerical examples show that the proposed multi-rate data-driven method is superior than the conventional single-rate method.

In this study, a data-driven design method is proposed for a dual-rate system, where the sampling interval of a plant output is restricted and is an integer multiple of the holding interval of a control input. In our proposed method, single-rate virtual reference feedback tuning (S-VRFT), where the holding interval is the same as the sampling interval, is extended to the dual-rate virtual reference feedback tuning (D-VRFT) system. In D-VRFT, a controller is decided using a set of input/output data used in S-VRFT, and it is easy to extend S-VRFT to D-VRFT and implement D-VRFT. In this study, intersample oscillations caused in such a dual-rate control system is prevented because a weighting filter is introduced for penalizing the control input deviation between the sampling instants. The filter is designed as an integrator for weighting the low-frequency domain. The improvement in fast-tracking performance as well as the ripple-free property are demonstrated through both the numerical and experimental results.

The present study discusses the design method for controlling a single-input/single-output linear time-invariant dual-rate system, where the sampling interval of the plant output is longer than the holding interval of the control input. In such a dual-rate system, the intersample output might oscillate even when the sampled output converges to the reference input in the steady state. In a conventional ripple-free method, an existing control law is extended by introducing an exogenous variable, which is independent of the discrete-time sampled response, and the exogenous variable is designed for eliminating the steady-state intersample ripples without changing the existing sampled response. In another method, since a control law is designed such that the intersample performance is optimized, the intersample ripples are eliminated in the transient as well as steady states. However, the preservation of an existing sampled response is not taken into account. The present study proposes a new design method for eliminating the intersample ripples subject to the existing sampled response. In the proposed method, the continuous-time index is optimized subject to the existing discrete-time response. As a result, the intersample ripples are eliminated in the transient as well as steady states, and the existing discrete-time sampled response is maintained. The proposed method is compared to the conventional dual-rate design methods in numerical examples, and the effectiveness of the method is demonstrated.

This study proposes a data-driven approach for controlling a dual-rate sampled-data system using the lifting technique, where the sampling interval of the plant output is longer than the holding interval of the control input. In the proposed method, the structure of the dual-rate controller is linearized to its controller parameter, and the controller parameter is optimized using noniterative correlation-based tuning. Furthermore, intersample ripples are eliminated because the difference in the control inputs between sampled outputs is weighted. The effectiveness of the proposed method is demonstrated through numerical and experimental examples.

In the design of simple adaptive control (SAC) using almost strictly positive real (ASPR), the feedback control system is stabilized by the output feedback with a high gain. Although ASPR is not, however, generally satisfied, it is achieved by introducing a parallel feedforward compensator (PFC). When SAC is designed for the augmented system which consists of an actual plant and PFC, not the actual plant output but the augmented system output converges to the reference input because of the influence of PFC. To resolve the problem, an extension method of the conventional SAC is proposed. In the proposed method, based on the null-space of an augmented plant, an exogenous input, which is independent of the augmented system output, is newly introduced. Because the exogenous input is designed so that PFC output is to be 0, the actual plant output is the same as the augmented system output in the steady state, and as a result, the actual plant output converges to the reference input. From a practical application point of view, the proposed method can easily improve the control performance of the conventional SAC with a PFC. In the proposed method, an exogenous input generated as the feedback signal of PFC output is only added to the conventional SAC control input. Therefore, the proposed method can be applied to various field in which the SAC method has been implemented, e.g., process control, mechanical systems, power systems, robotics, and others. In the present study, the effectiveness of the proposed method is also demonstrated through experiments for a motor control.

The present study discusses the consensus control of dual-rate multi-agent systems, where the sampling/communication interval of quantized data is an integer multiple of the control interval. A conventional multi-agent system uses a dynamic quantizer which is designed in a single-rate system where the intervals are equal, i.e., the control interval length is the same as the communication interval length. However, a dynamic quantizer designed in a dual-rate system is expected to have improved control performance. In the present study, an objective function is divided into a quantization term, which is related to the quantization error, and the remaining term. The proposed dual-rate dynamic quantizer is designed such that the quantization term is minimized. Finally, in numerical examples, the proposed dual-rate method is quantitatively evaluated by comparing with the conventional single-rate method, and the effectiveness of the proposed method is demonstrated.

The present study discusses an optimal design method of a proportional integral derivative (PID) control system for a continuous-time second-order plus dead-time system (SOPDT) that includes an under-damping system. The proposed PID control system is designed to minimize the performance index defined as the tracking performance for the set-point or the regulation performance for the disturbance, where the assigned stability margin is also achieved in order to attain robust stability for the modeling error. Because of the relationship between tracking performance and robust stability, the PID parameters are decided such that the tracking performance is optimized subject to the user-specified stability margin. In the proposed design method, in order to obtain the most general optimal PID possible parameters for controlled plants, we discuss a design method based on a normalized plant model. As a result, the PID parameters are seamlessly optimized between over-damping, critical-damping, and under-damping systems. The effectiveness of the proposed method is demonstrated through numerical examples.

In the present paper, we discuss a new design method for a proportional-integral-derivative (PID) control system using a model predictive approach. The PID compensator is designed based on generalized predictive control (GPC). The PID parameters are adaptively updated such that the control performance is improved because the design parameters of GPC are selected automatically in order to attain a user-specified control performance. In the proposed scheme, the estimated plant parameters are updated only when the prediction error increases. Therefore, the control system is not updated frequently. The control system is updated only when the control performance is sufficiently improved. The effectiveness of the proposed method is demonstrated numerically. Finally, the proposed method is applied to a weigh feeder, and experimental results are presented. © 2014 by ASME.

Most weigh feeders are controlled by a PID control method, and it is desirable to achieve high performance with this PID control. The present paper discusses the application of a generalized predictive control (GPC)-based PID controller to a weigh feeder. In conventional methods, GPC-based PID controllers are designed using a step-type reference signal, but in control of a weigh feeder, a reference input to be followed by a measured signal is a ramp-type signal because the measured signal is discharged mass. Hence, control of a weigh feeder using a GPC-based PID controller is enhanced for tracking a ramp-type signal. Because GPC can be expressed by PID parameters, the proposed method can be easily adopted in various industries. Experimental results show that a weigh feeder is well controlled using the enhanced GPC-based PID controller. (C) 2009 Elsevier Ltd. All rights reserved.