• 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.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2008.11a
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• pp.371-372
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• 2008

• 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.

• Journal of Navigation and Port Research
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• v.28 no.6
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• pp.469-474
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• 2004

In this paper, we study the posture control of an underwater vehicle with nonholonomic constraint. Generally, systems with nonholnomic constraints cannot be stabilized to an equilibrium points by smooth state feedback control. For the nonholonomic underwater vehicle system, we applied coordinate transformation to get multi-chained system We proposed non smooth feedback controller using backstepping method for stabilizing the multi chained form system Applying inverse input transformation to the non smooth feedback controller, we can get posture controller of the underwater vehicle with nonholonomic constraint. The proposed control scheme is applied to the posture control qf an underwater vehicle and verified the effectiveness of control strategy by numerical simulation.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.46 no.4
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• pp.1-6
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• 2009

In this paper, we design a dynamic state feedback smooth stabilizer for a nonlinear system whose Jacobian linearization may have uncontrollable mode because its eigenvalues are on the right half-plane. After designing an augmented system, a dynamic exponent scaling and backstepping enable one to explicitly design a smooth stabilizer and a continuously differentiable Lyapunov function which is positive definite and proper. The convergence of the designed controller is proved by the new notion 'degree indicator'.

• Nuclear Engineering and Technology
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• v.52 no.11
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• pp.2522-2534
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• 2020

It is well known that the model of nuclear reactors features natural nonlinearity, and variable parameters during power tracking operation. In this paper, a disturbance observer-based adaptive sliding mode control (DOB-ASMC) strategy is proposed for power tracking of the pressurized-water reactor (PWR) in the presence of lumped disturbances. The nuclear reactor model is firstly established based on point-reactor kinetics equations with six delayed neutron groups. Then, a new sliding mode disturbance observer is designed to estimate the lumped disturbance, and its stability is discussed. On the basis of the developed DOB, an adaptive sliding mode control scheme is proposed, which is a combination of backstepping technique and integral sliding mode control approach. In addition, an adaptive law is introduced to enhance the robustness of a PWR with disturbances. The asymptotic stability of the overall control system is verified by Lyapunov stability theory. Simulation results are provided to demonstrate that the proposed DOB-ASMC strategy has better power tracking performance than conventional sliding mode controller and PID control method as well as conventional backstepping controller.

• International Journal of Control, Automation, and Systems
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• v.2 no.3
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• pp.374-383
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• 2004

This paper presents a neural network adaptive controller for autonomous diving control of an autonomous underwater vehicle (AUV) using adaptive backstepping method. In general, the dynamics of underwater robotics vehicles (URVs) are highly nonlinear and the hydrodynamic coefficients of vehicles are difficult to be accurately determined a priori because of variations of these coefficients with different operating conditions. In this paper, the smooth unknown dynamics of a vehicle is approximated by a neural network, and the remaining unstructured uncertainties, such as disturbances and unmodeled dynamics, are assumed to be unbounded, although they still satisfy certain growth conditions characterized by 'bounding functions' composed of known functions multiplied by unknown constants. Under certain relaxed assumptions pertaining to the control gain functions, the proposed control scheme can guarantee that all the signals in the closed-loop system satisfy to be uniformly ultimately bounded (UUB). Simulation studies are included to illustrate the effectiveness of the proposed control scheme, and some practical features of the control laws are also discussed.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.62 no.6
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• pp.852-862
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• 2013

This paper proposes a target tracking control method for wheeled mobile robots with nonholonomic constraints by using a backstepping-like feedback linearization. For the target tracking, we apply a vision system to mobile robots to obtain the relative posture information between the mobile robot and the target. The robots do not use the sensors to obtain the velocity information in this paper and therefore assumed the unknown velocities of both mobile robot and target. Instead, the proposed method uses only the maximum velocity information of the mobile robot and target. First, the pseudo command for the forward linear velocity and the heading direction angle are designed based on the kinematics by using the obtained image information. Then, the actual control inputs are designed to make the actual forward linear velocity and the heading direction angle follow the pseudo commands. Through simulations and experiments for the mobile robot we have confirmed that the proposed control method is able to track target even when the velocity sensors are not used at all.

• Journal of Aerospace System Engineering
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• v.15 no.3
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• pp.1-10
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• 2021

The electro-hydrostatic actuators (EHA) are widely used in various industrial fields since they can independently execute the function of the hydraulic power source and have high efficiency. Particularly, in the aviation field, the EHA is mainly designed as dual redundant asymmetric tandem actuator to mitigate failure and minimize installation space. However, aviation EHAs designed in the form of dual redundant asymmetric tandem actuator have the disadvantage of decreased durability performance due to the occurrence of force fighting. In this paper, the controller is designed based on backstepping technique to improve control performance and reduce force fighting for aviation EHA. The augmented state observer is proposed to estimate the states required for control. Through simulation, it was verified that the proposed controller had superior control performance and significantly reduces the force fighting compared to the general PI controller.