• Journal of the Korean Institute of Intelligent Systems
• /
• v.25 no.2
• /
• pp.139-146
• /
• 2015

This paper presents the solution to model matching of switched asynchronous sequential machines by corrective control. We propose a model of switched asynchronous sequential machines, in which the system can have different dynamics of asynchronous machines governed by a pre-determined sequence of switching. The control objective is to derive a corrective control law so that the stable state behavior of the closed-loop system can match that of a prescribed model. A new skeleton matrix is defined to represent the reachability of the switched asynchronous machine, and a novel control scheme is presented that interweaves the switching signal and the corrective control procedure. A design algorithm for the proposed controller is illustrated in a case study.

• The Transactions of The Korean Institute of Electrical Engineers
• /
• v.57 no.1
• /
• pp.109-116
• /
• 2008

Model matching problem of asynchronous sequential machines is addressed in this paper. The main topic is to design a corrective controller such that the closed-loop behavior of the asynchronous sequential machine can follow a given model, i.e., their models can be "matched" in stable states. In particular, we assume that the considered asynchronous machine suffers from the presence of an input disturbance that can cause undesirable state transitions. The proposed controller can realize both model matching and elimination of the adverse effect of the input disturbance. Necessary and sufficient condition for the existence of a corrective controller that solves model matching problem is presented. Whenever controller exists, algorithms for their design are outlined and demonstrated in a case study.

• 제어로봇시스템학회:학술대회논문집
• /
• 2005.06a
• /
• pp.994-998
• /
• 2005

A new control method, called a simple model matching, has been recently developed by the author. This is very simple and be applied for linear and nonlinear discrete time systems with/without time lag. Based on this formulation, identification is examined in this paper using an interconnected neural network with the EBP-EWLS learning algorithm. With this result, a control method is also presented for a nonlinear discrete time system.

• Journal of Navigation and Port Research
• /
• v.31 no.6
• /
• pp.523-530
• /
• 2007

Crane systems are very important in industrial fields to carry heavy objects such that many investigations about control of the systems are actively conducted for enhancing its control performance. This paper presents an adaptive control approach using the model matching for a complex 3-DOF nonlinear crane system. First, the system model is linearized through feedback linearization method and then PD control is applied in the approximated model. This linear model is considered as nominal to derive corrective control law for a perturbed crane model using Lyapunov theory. This corrective control is primitively aimed to compensate real-time control deviation due to partially known perturbation. We additionally study stability analysis of the crane control system using Lyapunov perturbation theory. Evaluation of our control approach is numerically carried out through computer simulation and its superiority is demonstrated comparing with the classical control.

• Journal of Advanced Marine Engineering and Technology
• /
• v.20 no.4
• /
• pp.20-26
• /
• 1996

Recently, for the speed control of a diesel engine, some methods using the modern control theory such as LQ control technique, or $\textit{H}_{\infty}$control theory etc., have been reported. However, most of speed controlers of a diesel engine ever developed are still using the PID control algorithm. And, as another approach to the speed control of a diesel engine, the authors proposed already a new method to adjust the parameters of the PID controller by a model matching method. In the previous paper, the authors confirmed that the proposed new method is superior to Ziegler & Nichols's method through the analysis of results of the digital simulations under the assumption that the parameters of a diesel engine are known exactly. But, actually, it is very difficult to find out the value of parameters of a diesel engine accurately. And the parameters of a diesel engine are changigng according to the operating condition of a diesel engine. So, in this paper, a method to estimate the parameters of the PID controller for the speed control of a diesel engine by means of the model matching method are proposed. Also, the digital simulations are carried out in cases either with or without measurement noise. And this paper confirms that the proposed method here is superior to Ziegler & Nichols's method through the analysis of the characteristics of indicial responses.

• Journal of Institute of Control, Robotics and Systems
• /
• v.17 no.5
• /
• pp.451-459
• /
• 2011

Fundamentally, there are 5 systems are needed for autonomous navigation of unmanned ground vehicle: Localization, environment perception, path planning, motion planning and vehicle control. Path planning and motion planning are accomplished based on result of the environment perception process. Thus, high reliability of localization and the environment perception will be a criterion that makes a judgment overall autonomous navigation. In this paper, via map matching using vehicle dynamic model and LIDAR sensors, replace high price localization system to new one, and have researched an algorithm that lead to robust autonomous navigation. Finally, all results are verified via actual unmanned ground vehicle tests.

• 제어로봇시스템학회:학술대회논문집
• /
• 1996.10a
• /
• pp.165-168
• /
• 1996

In this paper, we propose a design method of PID adaptive controller based on frequency domain analysis. The method is based on the estimation of a nonparametric process model in the frequency domain and the determination of the PID controller parameters by achieving partial model matching so as to minimize a performance function concerning to relative model error between the loop transfer function of the control system and the desired system. In the design method the process is represented only by a discrete set of points on the Nyquist curve of the process. Therefore it is not necessary to estimate a full order parameterized process model.

• International Journal of Automotive Technology
• /
• v.5 no.2
• /
• pp.69-76
• /
• 2004

This paper evaluates the effectiveness of four-wheel-steering system from the viewpoint of lane-keeping control theory. In this paper, the lane-keeping control system is designed on the basis of the four-wheel-steering automobiles whose desired steering response is realized with the application of model matching control. Two types of desired steering responses are presented in this paper. One is zero-sideslip response, the other one is steering response which realizes zero-phase-delay of lateral acceleration. Using simplified linear two degree-of-freedom bicycle model, simulation study and theoretical analysis are conducted to evaluate the lane-keeping control performance of active four-wheel-steering automobiles which have different desired steering responses. Finally, the evaluation is conducted on straight and curved roadway tracking maneuvers.

• Journal of Advanced Marine Engineering and Technology
• /
• v.31 no.3
• /
• pp.293-300
• /
• 2007

The aim of this paper is to design a speed controller of a DC motor by selection of a PID parameters using genetic algorithm. The model of a DC motor is considered as a typical non-oscillatory, second-order system, And this paper compares three kinds of tuning methods of parameter for PID controller. One is the controller design by the genetic algorithm. second is the controller design by the model matching method third is the controller design by Ziegler and Nichols method. It was found that the proposed PID parameters adjustment by the genetic algorithm is better than the Ziegler & Nickels' method. And also found that the results of the method by the genetic algorithm is nearly same as the model matching method which is analytical method. The proposed method could be applied to the higher order system which is not easy to use the model matching method.

• Journal of Institute of Control, Robotics and Systems
• /
• v.3 no.5
• /
• pp.520-525
• /
• 1997

This paper presents a fault detection and diagnosis methodology based on weighted symptom model and pattern matching between the coming fault propagation trend and the simulated one. In the first step, backward chaining is used to find the possible cause candidates for the faults. The weighted symptom model is used to generate those candidates. The weight is determined from dynamic simulation. Using WSM, the methodology can generate the cause candidates and rank them according to the probability. Second, the fault propagation trends identified from the partial or complete sequence of measurements are compared with the standard fault propagation trends stored a priori. A pattern matching algorithm based on a number of triangular episodes is used to effectively match those trends. The standard trends have been generated using dynamic simulation and stored a priori. The proposed methodology has been illustrated using two case studies, and the results showed satisfactory diagnostic resolution.