• Journal of IKEEE
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• v.23 no.2
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• pp.716-721
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• 2019

A novel switching differentiator-based backstepping controller for uncertain pure-feedback nonlinear systems is proposed. Using asymptotically convergent switching differentiator, time-derivatives of the virtual controls are directly estimated in every backstepping design steps. As a result, the control law has an extremely simple form and asymptotical stability of the tracking error is guaranteed regardless of parametric or unstructured uncertainties and unmatched disturbances in the considered system. It is required no universal approximators such as neural networks or fuzzy logic systems that are adaptively tuned online to cope with system uncertainties. Simulation results show the simplicity and performance of the proposed controller.

• 제어로봇시스템학회:학술대회논문집
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• 1998.10a
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• pp.8-13
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• 1998

A tracking controller is presented for RLFJ(rigid link flexible joint) robot manipulators with only position measurements. The controller is developed based on the integrator backstepping design method and on the two observers: the first is simple linear form observer for the filtered link velocity errors and the other for the actuator velocities. The proposed controller achieves exponential tracking of link positions and velocities while keeping all internal signals bounded. It also guarantees exponential convergence of the estimated signals to their actual ones. Finally, simulation results are included to demonstrate the tracking performance.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.45 no.9
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• pp.711-723
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• 2017

This paper proposes a flight control system for an organic flight array(OFA) which has a new configuration to consist of multi modularized ducted-fan unmanned aerial vehicles (UAVs). The OFA is able to apply to various missions such as indoor reconnaissance, communication relay, and radar jamming by using capability of hover flight. The OFA has a distinguished advantage due to reconfigurable structure to assemble or separate with respect to its missions or operational conditions. A dynamic modelling of the OFA is derived based on equations of motion of the single ducted-fan modules. In order to apply nonlinear control method, an affine system of attitude dynamics is derived. Moreover, the control system is composed of a back-stepping controller for attitude control and a PID controller for position control. Then the performance of the proposed controller is verified via a numerical simulation under wind disturbance.

• Journal of the Institute of Convergence Signal Processing
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• v.8 no.2
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• pp.130-135
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• 2007

This paper deals with a controller design for a 2 dimensional aeroelatic model which has unknown parameters including polynomial type nonlinearity. Actually in case of state and acuator signal having magnitude, rate and bandwidth limitations, the controller can't be implemented and so in each case, a filter is used for implementation. First, error signals are defined upon the backstepping theory, and tracking error signals are also defined due to command signal and filter signals and then compensated tracking error signals are defined. Lastly, a Lyapunov function is defined for the stabilization and from this method, an adaptive law is derived. Simulations are done for the demonstrtion of the effectiveness of the algorithms.

• Journal of Institute of Control, Robotics and Systems
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• v.10 no.2
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• pp.112-124
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• 2004

A neural network based adaptive reconfigurable flight controller is presented for a class of discrete-time nonlinear flight systems in the presence of variations of aerodynamic coefficients and control effectiveness decrease caused by control surface damage. The proposed adaptive nonlinear controller is developed making use of the backstepping technique for the angle of attack, sideslip angle, and bank angle command following without two time separation assumption. Feedforward multilayer neural networks are implemented to guarantee reconfigurability for control surface damage as well as robustness to the aerodynamic uncertainties. The main feature of the proposed controller is that the adaptive controller is developed under the assumption that all of the nonlinear functions of the discrete-time flight system are not known accurately, whereas most previous works on flight system applications even in continuous time assume that only the nonlinear functions of fast dynamics are unknown. Neural networks learn through the recursive weight update rules that are derived from the discrete-time version of Lyapunov control theory. The boundness of the error states and neural networks weight estimation errors is also investigated by the discrete-time Lyapunov derivatives analysis. To show the effectiveness of the proposed control law, the approach is i]lustrated by applying to the nonlinear dynamic model of the high performance aircraft.

• Journal of the Korean Society for Precision Engineering
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• v.21 no.8
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• pp.73-82
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• 2004

In this paper, implementation of obstacle avoidance of a nonholonomic mobile robot in unstructured environment is introduced. To avoid obstacles, first, a reference collision-free path for the MR is generated off-line using HJB-based optimal path planning method. A controller is designed using integrator backstepping method for tracking the generated reference path. To implement the designed controller, a control system are needed and composed of camera system and PIC-based controller. The workspace is observed by a ceiling-mounted USB camera as part of an un-calibrated camera system. Thus the positional information of the MR is updated frequently and the MR can get the useful inputs for its tracking controller. The whole control system is realized by integrating a computer with PIC-based microprocessor using wireless communication: the image processing control module and path planning module serve as high level computer control while the device control serves as low level PIC microprocessor control. The simulation and experimental results show the effectiveness of the designed control system.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.11 no.3
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• pp.143-148
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• 2011

In this paper, a backstepping design is proposed to achieve stabilization and synchronization for the Lorenz-Stenflo (LS) chaotic system. The proposed method is a recursive Lyapunov-based scheme and provides a systematic procedure to design stabilizing controllers. The proposed controller enables stabilization of the chaotic motion and synchronization of two identical LS chaotic systems using only a single control input. Numerical simulations are presented to validate the proposed method.

• Journal of Power Electronics
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• v.15 no.6
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• pp.1584-1592
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• 2015

This paper presents a nonlinear method to control a DC-DC converter and track the Maximum Power Point (MPP) of a Photovoltaic (PV) system. A backstepping controller is proposed to regulate the voltage at the input of a buck-boost converter by means of Lyapunov functions. To make the control initially faster and avoid local maximum, a regression plane is used to estimate the reference voltages that must be obtained to achieve the MPP and guarantee the maximum power extraction, modifying the conventional Perturb and Observe (P&O) method. An experimental platform has been designed to verify the validity and performance of the proposed control method. In this platform, a buck-boost converter has been built to extract the maximum power of commercial solar modules under different environmental conditions.

• Proceedings of the KIEE Conference
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• 1999.07b
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• pp.779-781
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• 1999

In this paper we consider the TORA system and use backstepping to design active controllers for tracking; this problem is much more challenging than stabilization. We show that the control effort of the closed-loop system can be significantly improved by exploiting the backstepping design.

• Proceedings of the KIEE Conference
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• 2001.07d
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• pp.2087-2088
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• 2001

In this paper we presents a speed controller for permanent magnet synchronous motor using adaptive backstepping technique. The adaptive backstepping technique takes system nonlinearity into account in the control system design stage. The proposed control and adaptive law is proved to be asymptotically stable by the Lyapunov stability theory.