佐藤 孝雄

In this study, we considered the backward path-tracking control of articulated vehicles such as a tractor-trailer. An effective method using the exact feedback linearization was previously proposed in this research area. However, this method has a singular condition that the control law cannot be defined. Because of this, the controller has a strong dependence on the initial condition of the vehicle’s position and behavior with respect to the desired path. Moreover, the range of application is too narrow for practical use. To solve this problem, we propose a performance improvement method for the exact feedback linearization-based controller. Our proposed method is obtained by adding a singular condition avoidance input, which is obtained heuristically, to the previous controller. The simulation results indicated that our proposed method is useful for controlling a tractor-trailer mobile robot.

This paper reports a project-based learning (PBL) program for graduate students to develop science communication skills. To achieve this, the program made graduate students majoring in control engineering designed about an educational experiment system to understand the concept of control technique for elementary and junior high school pupils. As a result, they designed an educational program using a single-degree-of-freedom helicopter model. This program was carried out in the "youngsters' science festival" which is regional science festival. In addition, they summarized the details of the system and the responses of participants and presented at a conference on control, measurement and system integration. Through this PBL program, the students could develop their science communication skills by themselves.

In recent years, numerous studies on motion classification using surface electromyography (sEMG) have been conducted to realize a myoelectric hand system. This study considered the practical issues in a motion classification method using sEMG, which will be used to control a myoelectric hand. One such issue is the change in the sEMG characteristics that is caused by a change in the position of the sEMG electrode, owing to the replacement of the electrode. Because such changes influence the performance of a motion classifier, it is generally necessary to be relearn the classifier that the position of the electrode may change. To solve this problem, we propose a new classifier update method using a semi-supervised learning technique. In this method, the data measured under electrode position change is categorized into each motion by a semi-supervised learning technique using the relationship between the unsupervised data and the known categorized supervised data measured at a reference position; the classifier is then recalculated using categorized data. The experimental result shows that the performance of our proposed method is maintained even if the position of the electrode is changed.

The present paper discusses the design of a discrete-time proportional-integral-derivative (PID) control system for a first-order plus dead-time model. The optimal parameters for the desired robustness of the PID control system are determined by using the maximum value of the sensitivity function. We optimized the load-disturbance or the set-point performance in order to achieve the specified robustness. Finally, the effectiveness of the proposed design method is demonstrated through a numerical simulation.

The present study discusses a design method for controlling a weigh feeder. In the present study, a designed control system is assessed, and the control parameters are updated such that the control performance is improved. The proportional-integral (PI) control law is used to obtain a practical control system in industry. In the control system of a weigh feeder, since the steady-state response is more important than the transient response, the PI parameters of the PI control law are decided based on generalized minimum variance control with steady-state prediction (GMVCS). In the design of GMVCS, steady-state prediction is used instead of dead-time ahead prediction, and hence the steady-state control performance is superior to that of conventional methods. Finally, the effectiveness of the proposed method is demonstrated through experimental results.

This paper proposes a method for diagnosing a fault in the actuator of a mechanical system based on the log-likelihood of a discrete linear model describing the system. To detect the fault, we use the fact that the system characteristics change when a mechanical system is faulty. Our method detects changes in characteristics using the log-likelihood of the nominal model. After fault detection, comparing the log-likelihood of all possible fault models identifies the faulty actuator. The efficacy of our proposed method was confirmed through computer simulations.

This paper discusses a design method for a Generalized Minimum Variance Control (GMVC)-based Proportional-Integral-Derivative (PID) control system. In order to achieve the control performance of GMVC using a PID compensator, a GMVC compensator has to be replaced by a PID compensator, but a GMVC law cannot be replaced straightforwardly by a PID control law because the order of the coefficient polynomials of a GMVC law is higher than that of a PID control law. Therefore, in conventional methods, the GMVC compensator is approximated by the PID compensator. Most conventional GMVC-based PID control laws are designed in a one-degree-of-freedom (1DOF) system. On the other hand, we discuss a design method for a GMVC-based PID control law in a two-degree-of-freedom (2DOF) system. In particular, two 2DOF PID control laws are designed based on GMVC with a feed-forward compensator (abbreviated as FF-type GMVC) or with a pre-compensator (PC-type GMVC), and the approximation error caused by the structure of a 2DOF PID system is investigated. It is clarified that the FF-type and PC-type GMVC-based PID control laws are not same even if the PC-type and FF-type GMVC laws can be designed equivalently.

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.

指定するロバスト性を達成しつつ，制御性能を最適にするPID制御器のパラメータ選定法について検討する．制御対象のモデルが一時遅れ系と仮定し，任意のプラントパラメータに対して最適なPIDパラメータの選定方法を示す．従来は，連続時間系として提案されていたが，本研究では離散時間系における設計方法を新たに提案する．

This study discusses a design method for controlling a weigh feeder which has been employed to dispense material at a specified rate. In this study, a proportional-integral (PI) control law is designed based on a generalized minimum variance control (GMVC) law. The control performance of the designed control system is evaluated using a minimum variance index. Based on the evaluated control performance, one of the design parameters in GMVC is automatically updated such that the control performance is enhanced. In the proposed method, unknown plant parameters are estimated, and the GMVC-based PI control law is adaptively updated using the estimated plant parameters. The effectiveness of the proposed method is demonstrated through both a numerical example and an experiment.

In this study, a nonlinear system is controlled using a linear adaptive method. A nonlinear system is approximated a linear model at each operating point, and a control law is designed based on the approximated linear model. To obtain a suitable linear model at each operating point, many linear models are simultaneously identified. However, the computation load for identifying many models is considerably heavy. Hence, many linear models are identified using General-Purpose computing on Graphics Processing Units (GPGPU). In this study, the assessment of modeling performance is newly introduced. As a result, the control system is updated only when modeling performance is degraded, and frequent update of a control law can be avoided. Finally, numerical results are shown to demonstrate the effectiveness of the proposed method.

This study aimed to develop a method for estimating indoor human locomotion to confirm safety of an elderly person. To achieve this, we considered a method using a microwave sensor. Microwaves are reflected by the human body, and pass through obstructions such as glass windows and walls. There have been some previous researches on this topic. However, in these researches, human locomotion was estimated using distances from sensor to human measured by multiple microwave sensors. Since typical microwave sensors are velocity sensors using Doppler effect, their use for measurement or calculation of distance causes cumulative errors. Thus, this paper proposes a new indoor human locomotion estimation method using a human's velocity data, which can be directly measured by the sensor. The method was realized using an Unscented Kalman filter, and is known as a state estimation method. A human locomotion estimation experiment was carried out to confirm its feasibility. © 2014 ICIC International.

This paper proposes a new design method for a drum boiler system, which is a benchmark problem for proportional-integral-derivative (PID) control. In this study, the boiler is divided into two single-input single-output (SISO) systems, and two control systems are designed, even though the boiler is a multi-input multi-output (MIMO) system with interference. As a result, the control system design for a SISO system is simpler than that of a MIMO system. In the proposed method, interference is considered a disturbance, and a controller is designed for each SISO system. Because the plant models are time-varying systems, the proposed control system is automatically updated based on generalized minimum variance control (GMVC) such that the user-specified control performance is achieved. © 2014 ICIC International.

In recent years, multirate control has been evaluated for various nonlinear models. This paper presents a multirate control method for a twin-rotor type model helicopter. It is known that a twin-rotor type model helicopter is not easily controlled because of its strong nonlinearity. Although a multirate control method for nonlinear models has already been proposed, a significant number of calculations are required. Thus, nonlinear theory is not practical for built-in computers with low computing power. Therefore, this paper proposes a new control method for a nonlinear plant. In the proposed method, a linear control law is designed based on a linearized nonlinear plant model. The experimental results show that the control objective can be achieved by 2DOF (degree-of-freedom) integral compensation, even if there is a modeling error, and the effectiveness of the proposed method is verified. © 2014 ISSN 1881-803X.

In this study, we design a Fault-Tolerant Control (FTC) system based on estimation of fault signals, using a discrete linear multi-input multi-output (MIMO) system model. The FTC system can maintain nominal performance if a fault occurs in one of its components. The existing FTC method has the following 3 steps: Fault-Diagnosis, Estimation of fault magnitude, and Generation a new control law to compensate for the fault effect. The existing FTC method assumes that actuator and sensor faults correspond to a loss of actuator effectiveness or fault sensor measurements. Therefore, it cannot maintain nominal tracking control performance when an actuator has a failure that suggests complete breakdown of function. In this paper, we present a new FTC method that is extended to deal with the failure of an actuator. We confirm the feasibility of the presented FTC method by FTC simulation by comparison with the existing method. © 2014 ISSN 1881-803X.

The present paper proposes a simple design method for a multirate sampleddata system, where the sampling interval of the plant output is an integer multiple of the hold interval of the control input. In the proposed method, a proportional-derivative (PD) compensator is based on a multirate generalized predictive control (GPC) law. Since the proposed control law can be designed independently of the sample response, intersample ripples are eliminated without changing the sample response. Therefore, in the proposed method, even if integral compensation is not used, the ripples between sampled plant outputs can be eliminated. Simulation results have revealed the effectiveness of the proposed method. © 2014 ISSN 1881-803X.

This paper proposes a new design method for a drum boiler system, which is a benchmark problem for PID control. The boiler is a multi-input multi-output (MIMO) system with interference, but it is divided into independent single-input single-output (SISO) systems. In the proposed method, interference is considered a disturbance, and a controller is designed for each system. Because the controlled plants are time-varying systems, the control system is adaptively updated based on generalized minimum variance control (GMVC). © 2013 IEEE.

This paper discusses a design method for a Generalized Minimum Variance Control (GMVC)-based Proportional-Integral-Derivative (PID) control law in a two-degree-of-freedom (2DOF) system. The PID parameters of a PID control law are designed based on GMVC and are updated using the self-tuning method. In the conventional method, a 2DOF PID control law is based on GMVC with a feed-forward compensator (abbreviated as FF-type GMVC), and the feed-forward compensator is approximated by a PID compensator, but the structure of the PID compensator is restricted and the order of the feed-forward compensator is decided by the length of a dead-time. Therefore, the approximation accuracy deteriorates if the dead-time is long In this study, a 2DOF PID control law is newly designed based on a PC-type GMVC that 2DOF GMVC is designed using a pre-compensator, and the approximation error caused by the structure of a 2DOF system is investigated. Furthermore, it is clarified that the FF-type and PC-type GMVC-based PID control laws are not same although the PC-type and FF-type GMVC laws can be designed equivalently.

The present study discusses a model-free design method for control systems using fictitious reference input tuning (FRIT), which was originally designed based on one-shot control data. Moreover, FRIT has been extended to an online tuning method to cope with plant fluctuation. In the present study, the control quality is monitored using online FRIT. In the conventional online FRIT, the control system is always updated. In the proposed method, performance evaluation is introduced to the online FRIT. Consequently, quality monitoring can be implemented by online FRIT, and a control system can be updated only when a controlled plant fluctuates or the control performance deteriorates. The effectiveness of the proposed method is demonstrated through numerical examples.

The present paper discusses a new design method for a PID control system using 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 automatically selected to attain a user-specified control performance. In the proposed scheme, estimated plant parameters are updated only when the estimation error increases. Therefore, the control system is not updated frequently, The control system is updated only when the control performance is sufficiently improved. Numerical examples demonstrate the effectiveness of the proposed method.

The present paper proposes a new design method for a multirate system, in which the continuous-time plant is controlled by updating the discrete-time control input, in which the sampling interval of the plant output is an integer multiple of the hold interval of the control input. In the multirate system, the intersample response might oscillate even if the sample response converges to the reference response because the control input can vary between sampling instants. In the present paper, a multirate proportional-derivative control system is enhanced such that the steady-state intersample ripples are eliminated. In the proposed method, the intersample response can be improved independently of the sample response because an existing closed-loop response is maintained. Moreover, the control performance is not affected by the phase lag caused by the integral compensation because the integral compensation is not used for the elimination of the intersample ripples. Finally, in order to control a plant with unknown or time-varying parameters, the designed multirate control system is extended to a self-tuning controller. As a result, an unknown or time-varying plant can be controlled using the proposed method. © 2013 Inderscience Enterprises Ltd.

This paper discusses a design method of self-tuning control. In order to control a nonlinear system by using the linear control theory, a controlled plant assumed to be locally linear. Because the dynamic characteristics of an approximated linear model vary widely in response to operating environment, a plant model must be modified according to the changed environment. To obtain an accurate model, a lot of linear models are simultaneously identified, and a control system is designed based on one local linear model. To decide one local linear model from many linear models at sampling interval, the plant parameters of local linear model candidates are estimated using GPGPU (General-Purpose computing on Graphics Processing Units). © 2012 Intl Jrnal Advanced Mech.

This paper discusses a design method for a sampled-data control system, in which the sampling interval of the plant output is an integer multiple of the hold interval of the control input. To control such a control system, an adaptive multirate Proportional-Derivative(PD) control method is proposed. It is assumed that the sample response can stably follow its reference input by a multirate PD control law without the steady-state error, and the multirate PD control law is extended independently of the sample response such that intersample ripples are eliminated in the steady state. Furthermore, the extended multirate PD control system is enhanced with an adaptive law in order to achieve the control objective even if plant parameters are unknown or changed. In the proposed method, the transient response is not deteriorated by the integral compensation because the steady-state error and intersample ripples can be eliminated without the integral compensation. © 2012 Intl Jrnal Advanced Mech.

This paper deals with a multirate control system, where the sampling interval of the plant output is an integer multiple of the hold interval of the control input. In that multirate system, the intersample output may oscillate in steady state even if a sampled output converges to a set point. The oscillation is called ripple, and it causes a deterioration of the control performance. This paper proposes a new design method to suppress the ripple in the multirate system using the integral compensation. In the proposed control system, the integral compensation is revealed only when there is a modeling error or a disturbance. Therefore, the transient response is not deteriorated by the integrator if neither a modeling error nor a disturbance exists. A numerical example demonstrates the effectiveness of the proposed method. © 2012 Intl Jrnal Advanced Mech.

This paper proposes a new design method for a sampled-data multirate control system, in which the sampling interval of the plant output is an integer multiple of the hold interval of the control input. An existing control law which stabilizes a closed-loop system is extended such that the sample response is maintained and integral compensation is revealed only when there is a modeling error or a disturbance. The transient response is not deteriorated by the integral compensation when neither a modeling error nor a disturbance exists because the proposed method is designed as a two-degree-of-freedom system.

In the present paper, we discuss a new design method of a PI control system for controlling a weigh feeder. The PI parameters of a PI controller are based on generalized predictive control (GPC). Since the design parameters of GPC are selected in order to achieve a user-specified control performance, the PI parameters are adaptively updated such that the control performance is improved. In the proposed method, estimated plant parameters of a weigh feeder are updated only when the estimation error increases. Therefore, the control system is not updated frequently, and the control system is updated only when the control performance is sufficiently improved. The effectiveness of the proposed method is demonstrated through numerical examples and experimental results.

In the present paper, we discuss a design method for controlling a weigh feeder that has been widely used in industry. Since a control system is designed using a performance-adaptive method, the control parameters are adaptively updated based on user-specified control performance. In conventional performance-adaptive methods, control systems are designed such that the variance of the control error is less than or equal to a specified value and the variance of the differences in the control input is minimized without changing the acceptable variance value of the control error. On the other hand, since the design objective of the present study is to reduce energy consumption, the variance of the differences in the control input is first set, and then the variance of the control error is minimized without changing the acceptable variance value of the differences in the control input. Consequently, the variation of the control input can be substantially reduced. In the proposed method, a proportional-integral controller is designed based on generalized minimum variance control (GMVC) with steady-state predictive output (GMVCS). One of the design parameters in GMVCS is automatically decided such that a desired control performance can be attained, and the PI parameters of a PI control law are calculated based on a GMVCS law.

Proportional-Integral-Derivative (PID) control is the most widely used control method. Since, PID control performance can be adjusted by tuning the PID parameters, the selection of the PID parameters is very important, but optimal PID parameters are not easily obtained. Advanced control has high potential, but on-site engineers prefer PID control to advanced control. Hence, advanced control needs to be achieved by PID control. In this chapter, generalized predictive control (GPC) is attained by PID control. First, the technique that GPC law is approximated by a PID control law is introduced. Next, the obtained GPC-based PID control is applied to a weigh feeder. Finally, the design method of a GPC-based PID control system is extended to a multirate system in which the sampling interval is an integer multiple of the update interval.

The decision of sampling and hold intervals is an important issue in the design of sampled-data control systems, in which a continuous-time plant is controlled using a digital computer in discrete time, and the selection of intervals greatly influences the control quality. However, it is not easy to set these intervals arbitrarily because of hardware constraints. This paper proposes a new method for the design of a multi-rate single-input single-output sampled-data control system under the constraint that the sampling interval of the plant output in continuous time is an integer multiple of the hold interval of the control input, which is updated in discrete time. In the design of the multi-rate control system, the intersample plant output can possibly oscillate even if the sampled plant output converges to its reference input. In conventional design methods, to improve intersample ripples, both the sample and the intersample responses are simultaneously designed, and then, the original sample response might be deteriorated even though the intersample response is improved. In this study, a multi-rate control law, which stabilizes a closed-loop system, is extended on the basis of state-space representation, and the multi-rate control system is redesigned such that the steady-state intersample response is improved independently of the sample response. As a result, the sample response is maintained and the intersample response is improved in the steady state. Numerical examples demonstrate the effectiveness of the proposed method. © 2012 The Institute of Electrical Engineers of Japan.