佐藤 孝雄

This paper proposes an extended controller for generalized minimum variance control (GMVC) based on a full-order observer which has the equivalence to a controller by the polynomial approach. Although it has been proved that the controller using the reduced-order observer has the equivalence, it is difficult for the controller to be extended to Youla-Kucela generalized stabilizing controller. On the other hand, the controller using the full-order observer can be easily extended. Hence, the authors have already proposed a modified full-order observer so that the controller using the modified observer could be easily extended and has the equivalence with the controller by the polynomial approach. This paper extends the controller using the modified full-order observer to the generalized stabilizing controller and proves the equibalance to the extended controller by the polynomial approach mathematically. The equivalence gives the controller of polynomial approach to have the strong points of state-space based design. That is, the observer-based controller has a simple structure, which is state-feedback plus state estimator observer and it is easy to design the closed-loop poles. A numerical simulation is given to show the effectiveness of the proposed controller.

Cascade control structures are widely implemented in industries, due to the fact that they increase the performance of single-loop control. Nevertheless, their implementation requires a higher initial investment. Because of this, it is of great importance to be able to quantify their relative performance improvement. Very few studies handle this subject, and they do not obtain results which directly establish this quantification on a general basis. Therefore, the objective of this project is to conduct a study with help of computational tools, in order to determine the relative performance improvement of a cascade control structure with respect to a single-loop structure, for setpoint tracking and disturbance rejection. An overdamped second-order-plus-dead-time process, separable in two first-order-plus-dead-time subprocesses, was considered. The controllers were implemented using a PID algorithm. Simulations were conducted to obtain the ratio of the IAE performance indexes of each control structure, as a function of the time constant ratio, for different process parameters. The controllers were tuned by means of optimization routines, in order to guarantee that they provided the best IAE index. Finally, two general equations were obtained, which quantify the relative performance improvement of a cascade control structure with respect to a single-loop structure, as a function of the process parameters, for set point tracking and disturbance rejection.

The aim of the present study is to improve the understanding of the control engineering for university students through the experience of the control experiment, and hence an experimental device is developed. The students are educated using the device, and the educational effect is evaluated. In the present study, the students take examinations for the control engineering before and after the experiment, and the effect is evaluated objectively.

This paper proposes a model predictive controller for multivariable systems with time-delays. The design method is derived by the following way, first to consider a design for single input single output(SISO) systems and to modify the control problem for the SISO systems with no time-delays by shifting the outputs with time-delay steps and a design method with no time-delays is applied to the modified systems. Then the SISO case is extended to multi-input multi-output(MIMO) case by replacing time-delay steps in SISO case with an interactor matrix of MIMO plants.

Multi-agent systems (MASs) are used for distributed control purposes and substantial research attention has been directed to these systems because of their practical merits. In MASs, agents' information is shared through networks. In networked-control systems, the measured data is usually quantized because of sensor performance or specification, and its resolution is inadequate. Furthermore, because of network quality, the measurement interval is often longer than the control interval. Therefore, the present study introduces a design method for a dual-rate quantized control system, in which the measurement interval of agents is an integer multiple of the control interval.

This paper gives an optimal control law to eliminate ripples in inter-sample intervals of transient state of multi-rate sampled-control systems. As for ripples in steady state, there already exist several methods to remove the ripples. But to reduce the ripples in transient-state, so far there exists only trial and error method and there does not exist a systematic method. In this paper, first a reference model is defined which generates a reference output with no ripples and at sampled points, it has the same outputs with continuous time multi-rate control systems. Then the ripples in transient state are measured by the integrals of squared output errors. And equations to calculate the integrals are given by solving of Lyapunov equations. Finally the optimal control law is derived by differentiating the equations by the control input. The obtained optimal control input has a state feedback form and can be calculated at the short sampling time.

This study proposes a new design method for the consensus control of multi-agent systems with quantized signal communication. When the static quantizer used, the performance of the consensus control is deteriorated depending on the quantizing level. In a conventional method, the quantization is implemented the probability function. On the other hand, in the proposed method, the dynamic quantizer is introduced, and it is optimally designed. As a result, the consensus control performance is improved. Finally, the effectiveness of the proposed method is demonstrated through numerical examples.