• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.1278-1282
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• 2003

A new interacting multiple model (IMM) method using intelligent input estimation (IIE) is proposed to track a maneuvering target. In the proposed method, the acceleration level for each sub-model is determined by IIE-the estimation of the unknown acceleration input by a fuzzy system using the relation between maneuvering filter residual and non-maneuvering one. The genetic algorithm (GA) is utilized to optimize a fuzzy system for a sub-model within a fixed range of acceleration input. Then, multiple models are composed of these fuzzy systems, which are optimized for different ranges of acceleration input. In computer simulation for an incoming ballistic missile, the tracking performance of the proposed method is compared with those of the input estimation (IE) technique and the adaptive interacting multiple model (AIMM) method.

• 제어로봇시스템학회:학술대회논문집
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• 1997.10a
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• pp.426-429
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• 1997

This paper proposes a robust H$_{\infty}$ tracking filter to improve the unacceptable target tracking performance for systems with parameter uncertainties. Also, we use here the input estimation approach to account for the possibility of maneuver. Simulation results show that the robust H$_{\infty}$ tracking filter which is proposed here to solve the systems with all system parameter uncertainties, has a good tracking performance for a maneuvering target tracking problem.m.

• 제어로봇시스템학회:학술대회논문집
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• 1991.10a
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• pp.108-113
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• 1991

In this paper, an improved method for tracking maneuvering target is proposed. The proposed tracking filter is constructed by combining the input estimation approach with the variable dimension filtering approach. In this approach, the filter also provides the estimated time instant at which target starts maneuver, when the target maneuver is detected. Using this estimated maneuvering time, the maneuver input is estimated and the tracking system changes to the maneuver model. Simulations are performed to demonstrate the efficiency of the proposed tracking filter.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.51 no.5
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• pp.182-189
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• 2002

This paper presents a framework of hybrid dynamic control systems for the motion control of wheeled mobile robot systems with nonholonomic constraints. The hybrid control system has the 3-layered hierarchical structure: digital automata for the higher process, mobile robot system for the lower process, and the interface as the interaction process between the continuous dynamics and the discrete dynamics. In the hybrid control architecture of mobile robot, the continuous dynamics of mobile robots are modeled by the switched systems. The abstract model and digital automata for the motion control are developed. In high level, the discrete states are defined by using the sensor-based search windows and the reference motions of a mobile robot in low level are specified in the abstracted motions. The mobile robots can perform both the motion planning and autonomous maneuvering with obstacle avoidance in indoor navigation problem. Simulation and experimental results show that hybrid system approach is an effective method for the autonomous maneuvering in indoor environments

• International Journal of Control, Automation, and Systems
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• v.5 no.5
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• pp.539-546
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• 2007

The important field of research in ship operation is related to the high efficiency of transportation, the convenience of maneuvering ships and the safety of navigation. For these purposes, many intelligent technologies for ship automation have been required and studied. In this paper, we propose an intelligent voice instruction-based learning (VIBL) method and discuss the building of a ship's steering control system based on this method. The VIBL system concretely consists of two functions: a text conversion function where an instructor's inputted voice is recognized and converted to text, and a linguistic instruction based learning function where the text instruction is understood through a searching process of given meaning elements. As a study method, the fuzzy theory is adopted to build maneuvering models of steersmen and then the existing LIBL is improved and combined with the voice recognition technology to propose the VIBL. The ship steering control system combined with VIBL is tested in a ship maneuvering simulator and its validity is shown.

• Journal of Advanced Marine Engineering and Technology
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• v.28 no.2
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• pp.192-199
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• 2004

Navigation simulators have been used in many marine schools and manne training centers since the early 1960's. But these simulators were very expens~ve and were almost limited only in one engine system. In this paper, a catamaran with twin engine system. controlled by two remote control levers and its economic simulator based on a personal computer shall be introduced. One of the main features of catamaran is to control variously its progressing direction. In the static state, a catamaran can move into all the directions and in the dynamic state, ship can change immediately the heading and speed. Although a good navigator can skillfully operate one engine system, it is difficult to control smoothly the catamaran of twin engine system without any threat for the safety of passengers. Thus. in order to bring up the expert navigators. the development of a simulator which makes the training effective is necessary, Therefore, in this paper, a Fuzzy Inference Technique based Maneuvering Simulator for catamaran with twin engine system was developed. In general. in order to develop a catamaran simulator for effective training, first of all. its mathematical model must be acquired. According to the acquired system modeling. the dynamics of simulator is determined, But the proposed technique can omit a complex and tedious mathematical modeling procedures by using the fuzzy inference, which dependent upon only experiences of an expert and can design an efficient training program for unskillful navigators. This developed simulator was consisted of two fuzzy inference routines and two remote control levers, and was focused on effective training of navigators for the safe maneuvering to avoid a collision in a harbor.

• 제어로봇시스템학회:학술대회논문집
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• 1986.10a
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• pp.510-513
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• 1986

In recent years the Kalman filter(extended Kalman filter) have been applied to a wide variety of tracking moving targets, because of its properties. For such a reason, in this paper we attempt to study on adaptive filter algorithms which estimate unknown bias maneuvering inputs.

• International Journal of Control, Automation, and Systems
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• v.5 no.4
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• pp.397-409
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• 2007

In this paper, we propose a nonlinear guidance law for missiles against maneuvering targets. First, we derive the equations of motion described in the line-of-sight reference frame and then we define the equilibrium subspace of the nonlinear system to guarantee target interception within a finite time. Using Sontag's formula, we derive a nonlinear guidance law that always delivers the state to the equilibrium subspace. If the speed of the missile is greater than that of the target, the proposed law has global capturability in that, under any initial launch conditions, the missile can intercept the maneuvering target. The proposed law also minimizes the integral cost of the control energy and the weighted square of the state. The performance of the proposed law is compared with the augmented proportional navigation guidance law by means of numerical simulations of various initial conditions and target maneuvers.

• 제어로봇시스템학회:학술대회논문집
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• 2004.08a
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• pp.1669-1674
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• 2004

In this paper, a nonlinear information filter (IF) for curvilinear motions in an interacting multiple model (IMM) algorithm to track a maneuvering vehicle on a road is investigated. Driving patterns of vehicles on a road are modeled as stochastic hybrid systems. In order to track the maneuvering vehicles, two kinematic models are derived: A constant velocity model for linear motions and a constant-speed turn model for curvilinear motions. For the constant-speed turn model, a nonlinear IF is used in place of the extended Kalman filter in nonlinear systems. The suggested algorithm reduces the root mean squares error for linear motions and rapidly detects possible turning motions.

• Proceedings of the Acoustical Society of Korea Conference
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• autumn
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• pp.479-482
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• 2004

In this article we consider a single maneuvering target Tracking algorithm in the presence of missing measurements and high clutter environments for multi-sensor target tracking problem. The tracking algorithm is based on the Particle filtering method to predict and update target states. Proposed is the AMM-PF(Auxiliary Multiple Model Particle Filter)[2] method for maneuvering target tracking to improve performance in track estimate and maintenance with a high level of uncertainty. The algorithm we propose is compared to the Extended Kalman Filter(EKF). A simulation study is included.