• Journal of Institute of Control, Robotics and Systems
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• v.13 no.5
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• pp.452-461
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• 2007

Adaptive anti-sway and trajectory tracking control of overhead crane is presented, which utilizes Fuzzy Uncertainty Observer(FUO) and Fuzzy based Variable Structure Control(FVSC). We consider an overhead crane system which can be decoupled into the actuated and unactuated subsystems with its own lumped uncertainty such as parameter uncertainties and external disturbance. First, a new method for anti-sway control using FVSC is proposed to improve the conventional method based on Lyapunov direct method, while a conventional trajectory tracking control law using feedback linearization is directly adopted. Second, FUO is designed to estimate one of the two lumped uncertainties which can compensate both of them, based on the fact that two lumped uncertainties are coupled with each other. Then, an adaptive anti-sway control is proposed by incorporating the proposed FVSC and FUO. Under the condition that the observation error is Uniformly Ultimately Bounded(UUB) within an arbitrarily shrinkable region, the overall closed-loop system is shown to be Globally Uniformly Ultimately Bounded(GUUB). In addition, the Global Asymptotic Stability(GAS) of it is shown under the vanishing disturbance assumption. Finally, the effectiveness of the proposed scheme has been confirmed by numerical simulations.

• Proceedings of the KIEE Conference
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• 1988.07a
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• pp.898-901
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• 1988

Up to now, using adaptive control method, Identification deals with system whose entire state variables and prameters are accessible for measurement. In practical situations, all the state variables cannot be measured and it is impossible to directly apply since the parameters of the system are unknown. Therefore, in this paper, using only input-output data, such a model of the system is not available since the parameters of the system are unknown. this leads to the concept of an adptive observer in which both the parameters and the state variable of the system are identified simultaniously. Lyapunov's direct method and Kalman-Yakubovich (K-Y) lemma are employed to ensure the stability of this schemes. The feature is that the signal and adaptive gain which is generated from filter is imposed upon feedback vector and then state variables and the unknown parameters can be identified. To show the usefulness of the proposed schemes, computer simulation result of unknown second-order system shows the effectiveness of the proposed schems.

• Journal of Power Electronics
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• v.14 no.5
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• pp.980-988
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• 2014

This paper proposes an online gain tuning algorithm for a robust sliding mode speed controller of surface-mounted permanent magnet synchronous motor (SPMSM) drives. The proposed controller is constructed by a fuzzy neural network control (FNNC) term and a sliding mode control (SMC) term. Based on a fuzzy neural network, the first term is designed to approximate the nonlinear factors while the second term is used to stabilize the system dynamics by employing an online tuning rule. Therefore, unlike conventional speed controllers, the proposed control scheme does not require any knowledge of the system parameters. As a result, it is very robust to system parameter variations. The stability evaluation of the proposed control system is fully described based on the Lyapunov theory and related lemmas. For comparison purposes, a conventional sliding mode control (SMC) scheme is also tested under the same conditions as the proposed control method. It can be seen from the experimental results that the proposed SMC scheme exhibits better control performance (i.e., faster and more robust dynamic behavior, and a smaller steady-state error) than the conventional SMC method.

• Journal of Electrical Engineering and Technology
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• v.12 no.6
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• pp.2365-2377
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• 2017

This paper addresses two interrelated problems concerning the tracking control of pod propulsion unmanned surface vessel (USV), namely, the modeling of pod propulsion USV, and tracking controller design. First, based on MMG modeling theory, the model of pod propulsion USV is derived. Furthermore, a practical adaptive neural tracking controller is proposed by backstepping technique, neural network approximation and adaptive method. Meanwhile, unlike some existing tracking methods for surface vessel whose control algorithms suffer from "explosion of complexity", a novel neural shunting model is introduced to solve the problem. Using a Lyapunov functional, it is proven that all error signals in the system are uniformly ultimately bounded. The advantages of the paper are that first, the underactuated characteristic of pod propulsion USV is proved; second, the neural shunting model is used to solve the problem of "explosion of complexity", and this is a combination of knowledge in the field of biology and engineering; third, the developed controller is able to capture the uncertainties without the exact information of hydrodynamic damping structure and the sea disturbances. Numerical examples have been given to illustrate the performance and effectiveness of the proposed scheme.

• International Journal of Aeronautical and Space Sciences
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• v.13 no.3
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• pp.369-376
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• 2012

A nonlinear robust guidance law is designed for missiles against a maneuvering target by incorporating sliding-mode and optimal control theories based on the state dependent Riccati equation (SDRE) to achieve robustness against target accelerations. The guidance law is derived based on three-dimensional nonlinear engagement kinematics and its robustness against disturbances is proved by the second method of Lyapunov. A new switching surface is considered in the sliding-mode control design. The proposed guidance law requires the maximum value of the target maneuver, and therefore opposed to the conventional augmented proportional navigation guidance (APNG) law, complete information about the target maneuver is not necessary, and hence it is simple to implement in practical applications. Considering different types of target maneuvers, several scenario simulations are performed. Simulation results confirm that the proposed guidance law has much better robustness, faster convergence, and smaller final time and control effort in comparison to the sliding-mode guidance (SMG) and APNG laws.

• Journal of Electrical Engineering and Technology
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• v.1 no.1
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• pp.63-72
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• 2006

The purpose of this raper is to address the negative impedance instability in DC/DC converters. We present the negative impedance instability of PWM DC/DC converters loaded by constant power loads (CPLs). An approach to design digital controllers for DC/DC converters Is presented. The proposed method, called Power Alignment control technique, is applied to DC/DC step-down choppers operating in continuous conduction or discontinuous conduction modes with CPLs. This approach uses two predefined state variables instead of conventional pulse width modulation (PWM) to regulate the output voltage. A comparator compares actual output voltage with the reference and then switches between the appropriate states. It needs few logic gates and comparators to be implemented thus, making it extremely simple and easy to develop using a low-cost application specific integrated circuit (ASIC) for converters with CPLs. Furthermore, stability of the proposed controllers using the small signal analysis as well as the second theorem of Lyapunov is verified. Finally, simulation and analytical results are presented to describe and verify the proposed technique.

• Journal of the Korean Society of Industry Convergence
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• v.18 no.3
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• pp.181-190
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• 2015

This paper presents a new approach to control the position of robot arm in workspace a robot manipulator under unknown system parameters and bounded disturbance inputs. To control the motion of the manipulator, an inverse dynamics control scheme was applied. Since parameters of the robot arm such as mass and inertia are not perfectly known, the difference between the actual and estimated parameters was considered as a external disturbance force. To identify the known parameters, an improved robust control algorithm is directly derived from the Lyapunov's Second Method. A robust control algorithm is devised to counteract the bounded disturbance inputs such as contact forces and disturbing forces coming from the difference between the actual and the estimated system parameters. Numerical examples are shown using SCARA arm with four joints.

• Journal of the Korean Society for Precision Engineering
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• v.13 no.10
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• pp.94-104
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• 1996

This paper presents a new approach to the design of adaptive control system using DSPs(TMS320C31) for robotic manpulators to achieve accurate trajectory tracking by the joint angles Digital signal processors are used in implementing real time adaptive control algorithms to provide an enhanced motion control for robotic manipulators. In the proposed contorl scheme, adaptation laws are derived from the improved Lyapunov second stability analysis method based on the adaptive model reference control theory. The adaptive controller consists of an adaptive feedforward controller, feedback controller, and PID type time varying auxillary control elements. The proposed adaptive control scheme is simple in structure, fast in computation, and suitable for implementation of real-time control. Morever, this scheme does not require an accurate dynamic modeling nor values of manpipulator parameters and payload. Performance of the adaptive controller is illustated by simulation and experimental results for a SCARA robot.

• Journal of Navigation and Port Research
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• v.29 no.8 s.104
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• pp.747-753
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• 2005

In this paper, as an anti-sway control strategy of container cranes, we investigate a variable structure control in which the moving load follows a given trajectory, whereas both the trolley and hoist controllers achieve their positioning problems. It is crucial, in an automated container terminal, that collisions should be avoided during the transference of containers from one place to another. It is also necessary, in the case of a quay crane, to select suitable loading and unloading trajectories of containers, so that possible collisions with surrounding obstacles are avoided. After a brief introduction of the mathematical model, a robust control scheme (i.e., a second-order sliding mode control that guarantees a fast and precise transference and a suppression of the resulted swing) is presented. Despite model uncertainties and unmodeled actuators dynamics, the swing suppression from the given trajectory is obtained by constraining the system motion on suitable sliding surfaces, which include both the desired path and the swing angle. The proposed controller has been tested with a laboratory-size pilot crane. Experimental results are provided.