Shin Wakitani

Design and application of a data-driven PID controller

Research on database utilization has received much attention in recent years. This paper presents a data-driven proportional-integral-derivative (DD-PID) controller design method that uses a large database. In this method, a large data-set comprising input/output (I/O) data and control parameters is stored in a database in advance, and current control parameters are tuned by using the database in an online manner. The DD-PID controller design method utilizes the fictitious reference iterative tuning (FRIT) approach to learn control parameters in the database in an offline manner by utilizing initial experimental I/O data. This method is called the DD-FRIT method. In the study, the DD-FRIT method was applied to a nonlinear tank system to evaluate its effectiveness. This paper is structured as follows. First, the DD-PID controller design method is presented. Next, the offline learning algorithm that combines the design method with FRIT is explained. Finally, the results of a simulation and experiment are presented to demonstrate the effectiveness of the proposed method. These results showed that control parameters in the database were learned appropriately by the proposed method, and good control results were obtained.

A Cooling and Heat-retention System actuated by Peltier device considering fan-motor control

In this paper, operator-based nonlinear temperature control for Cooling and Heat-retention System actuated by Peltier device is proposed. The main purpose is to construct a system which can use energy effectively with waste heat from Peltier device. Moreover, temperature control about the executing cooling and heat-retention is conducted simultaneously. An operator based nonlinear control system is designed. In order to save energy, air flow rate control of fan-motor is considered. The effectiveness of the designed control system is shown by a simulation.

Operator based fault detection and isolation for microreactor actuated by Peltier devices

In this paper, the method of fault detection and isolation for microreactor units actuated by Peltier devices is proposed. Modeling and operator-based right coprime factorization of the nonlinear microreactor process are investigated. The effects of uncertainties and coupling effects of the process are controlled by the proposed design method, and the estimated output (sensorless part) is realized. Then using the proposed method of fault detection and isolation, desired output is obtained by comparing the sensor output and the estimated output. The effectiveness of the proposed design scheme is confirmed by the simulation results.

Operator-based robust non-linear control for a two-link robot arm

In this paper, a robust non-linear control scheme is proposed for a manipulator system by using the operator-based robust right coprime factorization approach. First the nonlinear feedback control scheme is proposed to eliminate effect of the uncertain plant. Second, robust stability of the present control system is discussed, and performance of output tracking is realized. Finally, effectiveness of the proposed method is confirmed by simulation results.

Operator theory based nonlinear fault tolerance control for MIMO microreactor

In this paper, an operator based robust nonlinear fault tolerance system design for fault signal to the sensor of MIMO microreactor system with Peltier devices is proposed by using robust right coprime factorization approach. In details, first, a mathematical model of the microreactor is described. Next, an operator based nonlinear feedback tracking control system is given. By compensating the effects of uncertainties and unknown interference of the controlled object, detection of the fault signal becomes more clearly. After finishing the compensation of the effects of uncertainties and unknown interferences, fault signal detection works. The fault signal of control system is analyzed by using two sorts of operators. The effectiveness of the proposed design scheme is confirmed by experimental results.

Design of a CMAC-FRIT controller for a magnetic levitation device

Proportional-integral-derivative (PID) control schemes have been widely used in most industrial control systems. However, it is difficult to determine a suitable set of PID gains because most industrial systems have nonlinearity. On the other hands, the cerebellar model articulation controller (CMAC) classified as neural networks has been proposed, and design scheme of an intelligent PID controller has been proposed. However, the CMAC-PID controller has a problem that CMACs used as PID tuners must be trained in an online manner to get their optimal weights. In order to train CMACs in an offline manner, a combination of CMAC learning and a fictitious reference iterative tuning (FRIT) scheme, which is called CMAC-FRIT scheme, has been proposed in our previous research, and an effectiveness of the method has been evaluated only by simulations. FRIT is a scheme to determine control parameters of linear controllers by using a set of experimental data. According to the CMAC-FRIT scheme, a CMAC-PID tuner can be trained in an offline manner by using a set of operating data. In this research, the proposed CMAC-PID controller is implemented and applied to a magnetic levitation device.