This paper proposes a novel method with pseudo-on-line scheme using the optimized look-up table based on the genetic algorithm which does not use the gradient and finds the global optimum of an un-constraint optimization problem. The technique is a pseudo-on-line method that optimally estimates the parameters of fuzzy PID(FPID) controller for systems with non-linearity, using the genetic algorithm. The proposed controller(GFPID) with the auto-tuning function is applied to the on-line and real-time control of speed at 3-phase induction motor, and its computer simulation is carried out. simulation results show that the proposed methodis more excellent that conventional FPID and PID controllers.

The Lyapunov stability theorem is used to derive a control law that can be used to control the spacing between vehicles in a platoon. A third order system is adopted to model the vehicle and power-train dynamics. In addition, the concept of

This paper is concerned with a delay-dependent sliding mode scheme for the robust stabilization of input-delay systems with bounded unknown uncertainties. A sliding surface based ona predictor is proposed to minimize the effect of the input delay. Then, a robust control law is derived to ensure the existence of a sliding mode on the surface. In input-delay systems, uncertainties given during te delayed time are not directly controlled by the switching control because of causality prolem of them. They can influence the stability of the system in the sliding mode. Hence, a delay-dependent stability analysis for reduced order dynamics is employed to estimate maximum delay bound such that the system is globally asymptotically stable in the sliding mode. A numerical example is given to illustrate the design procedure.

In this paper, the output feedback stabilizing problem is solved using any given state feedback control law. Compared to the linear systems is not so straightforward for nonlinear systems. We briefly explain the intrinsic obstructions for this problem and provide new output feedback scheme which achieves the semi-global stabilization with the high-gain state observer. THe overall uniform observability of the plant. Therefore, the result can be regarded as an extension of the separation principle for linear systems in some aspect.

A receding horizon FIR filter is suggested for discrete time-varying systems, combining the Kalman filter with the receding horizon strategy. The suggested filter is shown to be an FIR structure that has many good ingerent properties. The suggested filter is represented in an iterative form and also in a standard FIR form. The suggested filter turns out to be a remarkable deadbeat observer that is often robust against system and measurement noises. It is also shown that the suggested filter is an unbiased estimator irrespective of any horizon initial condition. For the amenability to parallel and systolic implementation as well as the numerical stability, a square-root algorithm for the suggested filter is presented. To evaluate performance, the suggested filter is applied to a problem of unknown input estimation and compared with the existing Kalman filter based approach.

This paper presents a method to assign robustly the closed loop system's poles in a specified disk by a state feedback for a linear time invariant system with structured or unstructured uncertainties. THe proposed robust design procedure includes two steps. Firstly, the perturbed closed loop matrix $A_{cl p}$ = $A_{cl}$ + Δ$A_{cl}$ is rearranged such that it is a function of the nominal closed loop matrix $A_{cl}$. Hence, we can control the positions of the perturbed closed loop poles by choosing $A_{cl}$ appropriately. Secondly, the feedback control law F that assigns the closed loop poles of the perturbed system in a specified disk is determined from the equation $A_{cl}$ = A + BF. A procedure for finding F is proposed based on partitioning every matrix of the equation $A_{cl}$ = A + BF in the horizontal direction.

In this paper, an optimal group control for elevator systems is proposed with timed Petri net based approach. Elevator system is modeled by time Petri nets and hall call response times are estimated with moment generating functions (MGFs) methos, which is applicable to real traffic patterns. Two assignment policies are proposed to satisfy the demands of passengers(i.e. hall/car calls) and to handle exceptional situations. In addition, optimal algorithms are implementated to minimize cost functions. THe performances of the elevator system employing the proposed algorithms are compared with each others in ways of several performance measures by a computer simulation.

A two parameter model of a single fictitious weak acid with unknown dissociation constant has been successfully applied to design a neutralization system for many multi-component acid streams. But there are some processes for which above two parameter model is not satisfactory due to poor approxmation of the nonlinearity of pH process. Here, for etter control of wide class of multi-component acid streams, a three parameter model of a strong acid and a weak acid with unknown dissociation constant is proposed. The model approximates effectively three types of largest gain variation nonlinearities. Based on this model a nonlinear pH control system is designed. Parameters can eeasily estimated since their combinations appear linearly in the model equations and nonlinear adaptive control system may also be constructed just as with the two parameter model.

A neural controller for process control is proposed that combines a conventional multi-loop PID controller with a neural network. The concept of target signal based on feedback error is used for on-line learning of the neural network. This controller is applied to distillation column control to illustrate its effectiveness. The result shows that the proposed neural controller can cope well with disturbance, strong interactions, time delays without any prior knowledge of the process.

This paper presents iterative schemes and continuation schemes for designing robust controllers which stabilize dynamic systems having bounded parametric uncertainties. Utilizing results of the cheap control problem, some existence conditions of the robust controller are obtained, which are different from the matching conditions. continuation schemes are used to overcome the divergence problem of iterative schemes. The roust controller design method is extended to nonlinear system ans easily implementable series solution is also obtained. Results are illustrated with simple examples.