• Proceedings of the KIEE Conference
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• 2000.07d
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• pp.2729-2731
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• 2000

In this paper, we propose an adaptive controller using RBFN(radial basis function network) for robot manipulators. The structure of the proposed controller consists of a RBFN and a fixed gain PD controller. On the basis of the Lyapunov stability theorem, we guarantee the UUB (uniformly ultimately boundedness) for the total system. And the learning law of RBFN is established by the Lyapunov method. Finally, we apply the proposed controller to tracking control for the 2 link SCARA type robot manipulator.

• Nuclear Engineering and Technology
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• v.50 no.6
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• pp.877-885
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• 2018

Various controllers such as proportional-integral-derivative (PID) controllers have been designed and optimized for load-following issues in nuclear reactors. To achieve high performance, gain tuning is of great importance in PID controllers. In this work, gains of a PID controller are optimized for power-level control of a typical pressurized water reactor using particle swarm optimization (PSO) algorithm. The point kinetic is used as a reactor power model. In PSO, the objective (cost) function defined by decision variables including overshoot, settling time, and stabilization time (stability condition) must be minimized (optimized). Stability condition is guaranteed by Lyapunov synthesis. The simulation results demonstrated good stability and high performance of the closed-loop PSO-PID controller to response power demand.

• Journal of Mechanical Science and Technology
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• v.18 no.11
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• pp.1916-1922
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• 2004

A robust position control with the bound function of neural network structure is proposed for uncertain robot manipulators. The uncertain factors come from imperfect knowledge of system parameters, payload change, friction, external disturbance, and etc. Therefore, uncertainties are often nonlinear and time-varying. The neural network structure presents the bound function and does not need the concave property of the bound function. The robust approach is to solve this problem as uncertainties are included in a model and the controller can achieve the desired properties in spite of the imperfect modeling. Simulation is performed to validate this law for four-axis SCARA type robot manipulator.

• Journal of Power Electronics
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• v.7 no.1
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• pp.1-12
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• 2007

Novel nonlinear backstepping control with integrated adaptive control function is developed for high-performance positioning control systems. The proposed schemes are synthesized by a systematic approach and implemented based on a modern low-cost DSP controller, TMS320C32. A baseline backstepping control scheme is derived first, and is then extended to include a nonlinear adaptive control against the system parameter changes and load variations. The backstepping control utilizes Lyapunov function to guarantee the convergence of the position tracking error. The final control algorithm is a convenient in the implementation of a practical 32-bit DSP controller. The new control system can achieve superior performance over the conventional nested PI controllers, with improved position tracking, control bandwidth, and robustness against external disturbances, which is demonstrated by experimental results.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.20 no.2
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• pp.147-155
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• 2007

In this study, the performance of the modified sliding mode control proposed in the previous study is evaluated for seismic response control of nonlinear hysteretic structures. Modified sliding mode control(MSMC) utilizes the target derivative of Lyapunov function in order to calculate control force, and its performance was evaluated only lot linear structures in the previous study. However, considering that most structures subject to strong earthquake show nonlinear hysteretic behivior, the results from the previous study have limitations in practical application. The results from numerical analyses of single degree of freedom systems and base isolated system, which were described using Bouc-Wen model, indicate that the proposed MSMC algorithm shows better control performance than the existing sliding mode controller.

• Journal of Mechanical Science and Technology
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• v.18 no.8
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• pp.1288-1296
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• 2004

Wall-following control problem for a mobile robot is to move it along a wall at a constant speed and keep a specified distance to the wall. This paper proposes wall-following controllers based on Lyapunov function candidate for a two-wheeled mobile robot (MR) to follow an unknown wall. The mobile robot is considered in terms of kinematic model in Cartesian coordinate system. Two wall-following feedback controllers are designed: full state feedback controller and observer-based controller. To design the former controller, the errors of distance and orientation of the mobile robot to the wall are defined, and the feedback controller based on Lyapunov function candidate is designed to guarantee that the errors converge to zero asymptotically. The latter controller is designed based on Busawon's observer as only the distance error is measured. Additionally, the simulation and experimental results are included to illustrate the effectiveness of the proposed controllers.

• Nuclear Engineering and Technology
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• v.54 no.3
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• pp.940-947
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• 2022

Meta-heuristic algorithms have found their place in optimization problems. Henry gas solubility optimization (HGSO) is one of the newest population-based algorithms. This algorithm is inspired by Henry's law of physics. To evaluate the performance of a new algorithm, it must be used in various problems. On the other hand, the optimization of the proportional-integral-derivative (PID) gains for load-following of a nuclear power plant (NPP) is a good challenge to assess the performance of HGSO. Accordingly, the power control of a pressurized water reactor (PWR) is targeted, based on the point kinetics model with six groups of delayed-neutron precursors. In any optimization problem based on meta-heuristic algorithms, an efficient objective function is required. Therefore, the integral of the time-weighted square error (ITSE) performance index is utilized as the objective (cost) function of HGSO, which is constrained by a stability criterion in steady-state operations. A Lyapunov approach guarantees this stability. The results show that this method provides superior results compared to an empirically tuned PID controller with the least error. It also achieves good accuracy compared to an established GA-tuned PID controller.

• Proceedings of the KIEE Conference
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• 1992.07a
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• pp.344-346
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• 1992

In this paper a robust hybrid control algorithm for n-link nonredundant robot manipulators is proposed. This scheme includes an estimation law for the upper bound on the uncertainty such that robust control input is updated as a function of the estimated upper bound. The uniform ultimate boundedness of the tracking error is generated by the Lyapunov based theory.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.129.6-129
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• 2001

In this paper, we consider a class of time-varying systems with time-varying state delay. Generally, this system is affected by many uncertainties and we assume that the information of the upper bound(time-delay, uncertainty) is known. In this work, we propose a robust control for system with state delay. The stability based on Lyapunov function is presented. Finally, a numberical example is given to demonstrate the validity of the result.

• International Journal of Aeronautical and Space Sciences
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• v.5 no.1
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• pp.19-29
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• 2004