• Proceedings of the KIEE Conference
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• 1996.11a
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• pp.383-385
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• 1996

In this paper, the dynamic path-following using the path-observer is proposed to improve the stability when initial position errors are considered. The dynamic path-following without the path-observer cannot follow reference path when initial position errors are large, so we propose the path-observer method. Finally, the results of simulation will be described.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.48 no.11
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• pp.1448-1456
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• 1999

In this paper, we propose a new technique for path-following of the wheeled mobile robot systems with nonholonomic constraints using a path-observer. We discuss the path-following problems of the nonholonomic mobile robot systems which have two nonsteerable, independently driven wheels with the various initial conditions such as a position, a heading angle, and a velocity. It is shown that the performance of dynamic path-following importantly is affected by the intial conditions. Particularly, if the initial conditions become more distant from the desired path and the desired velocity become faster, the system is shown to have worse performance and small time local stable. To find the controllable and stable control for path-following with various initial configuration, we propose the path-observer which can be used for control of the stable path-following of nonholonomic mobile robot system with the various initial conditions. The proposed scheme exhibits the efficient path-following properties for nonholonomic mobile robot in any intial conditions. The simulation results demonstrate the effectiveness of the proposed method for dynamic path-following tasks with the various initial conditions.

• Proceedings of the KIEE Conference
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• 2000.07d
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• pp.2901-2903
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• 2000

This thesis deals with study and implementation of Fuzzy controller with observer which can enhance the path-tracking performance of optically guided AGV(Automated Guided Vehicle). The AGV in this thesis is differential drive type and has front-side and rear-side optical sensors. which can identify the guiding path. This controller has excellent disturbance rejection and therefore is advantageous when it is instructed to follow straight paths. This fuzzy controller with observer enhances transient performance of the controller is demonstrated by simulation and is compared with that of individual loop controller

• 제어로봇시스템학회:학술대회논문집
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• 2002.10a
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• pp.48.3-48
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• 2002

1) Linear state feedback control design problem for plant with unknown deterministic disturbance is considered and a method to realize state feedback by using adaptive observer which estimates the unknown disturbance simultaneously is proposed. 2) From the viewpoint of practical application, we propose an extended adaptive observer with direct plant path from input to output, which is necessary to use the acceleration type sensors as plant output. 3) Theoretical result is confirmed by numerical simulation of 1-DOF vibration control system.

• Journal of Drive and Control
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• v.14 no.2
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• pp.9-15
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• 2017

The steering systems of all-terrain cranes have been developed with various control strategies for the stability and drivability. To optimally control the input steering angle, an accurate mathematical model that represents the actual crane dynamics is required. The derivation of an accurate mathematical model to optimally control the steering angle, however, is difficult since the steering-control strategy generally varies with the magnitude of the crane's longitudinal velocity, and the postures of the crane's working parts vary while it is being driven. To address this problem, this paper proposes an automatic steering-control algorithm that is based on the MPC (model predictive control) with a disturbance observer for all-terrain cranes. The designed disturbance observer of this study was used to estimate the error between the base steering model and the actual crane. A model predictive controller was used for the computation of the optimal steering angle, along with the use of the base steering model with an estimated uncertainty. Performance evaluations of the designed control algorithms were conducted based on a curved-path scenario in the Matlab/Simulink environment. The performance-evaluation results show a sound reference-path-tracking performance despite the large uncertainties.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.21 no.2
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• pp.265-276
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• 2017

In this paper, a robust and more accurate trajectory tracking control method for a mobile robot is proposed using WIPDC(Weighted Integral Parallel Distributed Compensation) and T-S Fuzzy disturbance observer. WIPDC reduces the steady state error by adding weighted integral term to PDC. And, T-S Fuzzy disturbance observer makes it possible to estimate and cancel disturbances for a T-S fuzzy model system. As a result, the trajectory tracking controller based on T-S Fuzzy disturbance observer shows robust tracking performance. When the initial postures of a mobile robot and the reference trajectory are different, the initial control inputs to the mobile robot become too large to apply them practically. In this study, also, the problem is solved by designing an initial approach path using a path planning method which employs $B\acute{e}zier$ curve with acceleration limits. Performances of the proposed method are proved from the simulation results.

• Journal of Ocean Engineering and Technology
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• v.20 no.6 s.73
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• pp.24-34
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• 2006

Hydrodynamic coefficients strongly affect the dynamic performance of an AUV. Thus, it is important to know the true values of these coefficients, in order to accurately simulate the AUV's dynamic performance. Although these coefficients are generally obtained experimentally, such as through the PMM test, the measured values are not completely reliable because of experimental difficulties and errors. Another approach, by which these coefficients can be obtained, is the observer method, in which a model-based estimation algorithm estimates the coefficients. In this paper, the hydrodynamic coefficients are estimated using two nonlinear observers: a sliding mode observer and an extended Kalman filter. Their performances are evaluated in Matlab simulations, by comparing the estimated coefficients obtained from the two observer methods, with the experimental values as determined from the PMM test. A sliding mode controller is constructed for the diving and steering maneuver by using the estimated coefficients. It is demonstrated that the controller, applied with the estimated values, maintains the desired depth and path with sufficient accuracy.

• Journal of the Korea Institute of Military Science and Technology
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• v.27 no.4
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• pp.495-506
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• 2024

In this study, we propose the terrain following algorithm using model predictive control and nonlinear disturbance observer-based backstepping sliding mode controller for an aircraft system. Terrain following is important for military missions because it helps the aircraft avoid detection by the enemy radar. The model predictive control is used to replace the generating trajectory and guidance with the flight path angle constraint. In addition, the aircraft is affected to the parameter uncertainty and unknown disturbance such as wind near the mountainous terrain. Therefore, we suggest the nonlinear disturbance-based backstepping sliding mode control method for the aircraft that has highly nonlinearity to enhance flight path angle tracking performance. Through the numerical simulation, the proposed method showed the better tracking performance than the traditional backstepping method. Furthermore, the proposed method presented the terrain following maneuver maintaining the desired altitude.

• Journal of Drive and Control
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• v.14 no.2
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• pp.30-36
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• 2017

This paper presents a sliding mode observer-based fault detection algorithm for steering inputs of an all-terrain crane. All-terrain cranes with multi-axles have several steering modes for various working purposes. Since steering angles at the other axles except the first wheel are controlled by using the information of steering angle at the first wheel, a reliable signal of the first axle's steering angle should be secured for the driving safety of cranes. For the fault detection of steering input signal, a simplified crane model-based sliding mode observer has been used. Using a sliding mode observer with an equivalent output injection signal that represents an actual fault signal, a fault signal in steering input was reconstructed. The road steering mode of the crane's steering system was used to conduct performance evaluations of a proposed algorithm, and an arbitrary fault signal was applied to the steering angle at the first wheel. Since the road steering mode has different steering strategies according to different speed intervals, performance evaluations were conducted based on the curved path scenario with various speed conditions. The design of algorithms and performance evaluations were conducted on Matlab/Simulink environment, and evaluation results reveal that the proposed algorithm is capable of detecting and reconstructing a fault signal reasonably well.

• International Journal of Precision Engineering and Manufacturing
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• v.6 no.4
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• pp.37-43
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• 2005

This paper presents a hybrid control algorithm for the active noise control in the rectangular enclosure using an active/passive foam actuator. The hybrid control composes of the adaptive feedforward with feedback loop in which the adaptive feedforward control uses the well-known filtered-x LMS(least mean square) algorithm and the feedback loop consists of the sliding mode controller and observer. The hybrid control has its robustness for both transient and persistent external disturbances and increases the convergence speed due to the reduced variance of the jiltered-x signal by adding the feedback loop. The sliding mode control (SMC) is used to incorporate insensitivity to parameter variations and rejection of disturbances and the observer is used to get the state information in the controller deign. An active/passive smart foam actuator is used to minimize noise actively using an embedded PVDF film driven by an electrical input and passively using an absorption-foam. The error path dynamics is experimentally identified in the form of the auto-regressive and moving-average using the frequency domain identification technique. Experimental results demonstrate the effectiveness of the hybrid control and the feasibility of the smart foam actuator.