• Journal of the Korean Institute of Intelligent Systems
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• v.24 no.4
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• pp.385-391
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• 2014

This paper proposes fuzzy disturbance observer based multiple sliding surface control scheme for nonlinear systems with mismatched disturbance. In order to stabilize nonlinear systems with mismatched disturbance, a controller based on multiple sliding surface control scheme is designed. In addition, a fuzzy disturbance observer is used to estimate the disturbance. Using the fuzzy disturbance observer, "explosion of terms" problem and chattering problem were solved. The stability of the proposed control scheme is analyzed by Lyapunov stability theory. For the verification, we apply the proposed method to numerical examples and compare its result with that of the applied nonlinear disturbance observer based sliding mode control.

• The Journal of the Korea institute of electronic communication sciences
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• v.7 no.5
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• pp.1139-1144
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• 2012

The ration of payload to weight of industrial robot amounts form 1:10 to 1:30. Compared with man who have a ration of 3:1, it is very low. One of the goals for the next generation of robots will be a ration. This might be possible only by developing lightweight robots. When two-link flexible arm is rotated about an joint axis, transverse vibration may occur. In this paper, vibration dynamics of flexible arm is modeled by using Bernoulli-Euler beam theory and Lagrange equation. Using the fact that matrix $\dot{D}-2C$ is skew symmetric, new controllers which have a simplified structure with less computational burden is proposed by using Lyapunov stability theory. We propose deterministic and adaptive control laws for two link flexible arm, and the validity of the proposed control scheme is shown in computer simulation for two-link flexible arm.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.38 no.3
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• pp.228-235
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• 2010

This paper deals with an autonomous flight controller design problem for a tilt-rotor aircraft in rotary-wing mode. The inner-loop algorithm is designed using the output-based approximate feedback linearization. The model error originated from the feedback linearization is cancelled within allowable tolerance by using single-hidden-layer neural network. According to Lyapunov direct stability theory, the adaptive update law is derived to run the neural network on-line, which is based on the linear observer dynamics. Moreover, the outer-loop algorithm is designed to track the trajectory generated from way-point guidance. Especially, heading and flight-path angle line-of-sight guidance are applied to the outer-loop to improve accuracy of the landing tracking performance. The 6-DOF nonlinear simulation shows that the overall performance of the flight control algorithm is satisfactory even though the collective input response shows instantaneous actuator saturation for a short time due to the lack of the neural network and the saturation protection logic in that loop.

• International Journal of Control, Automation, and Systems
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• v.4 no.4
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• pp.414-427
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• 2006

This paper presents an adaptive feedback linearization control scheme for induction motors with simultaneous variation of rotor and stator resistances. Two typical modeling techniques, rotor flux model and stator flux model, have been developed and successfully applied to the controller design and adaptive observer design, respectively. By using stator fluxes as states, over-parametrization in adaptive control can be prevented and control strategy can be developed without the need of nonlinear transformation. It also decrease the relative degree for the flux modulus by one, thereby, yielding, a simple control algorithm. However, when this method is used for flux observer, it cannot guarantee the convergence of flux. Similarly, the rotor flux model may be appropriate for observers, but it is not so for adaptive controllers. In addition, if these two existing methods are merged into overall adaptive control system, it brings about structural complexies. In this paper, we did not use these two modeling methods, and opted for the airgap flux model which takes on only the positive aspects of the existing rotor flux model and stator flux model and prevents structural complexity from occuring. Through theoretical analysis by using Lyapunov's direct method, simulations, and actual experiments, it is shown that stator and rotor resistances converge to their actual values, flux is well estimated, and torque and flux are controlled independently with the measurements of rotor speed, stator currents, and stator voltages. These results were achieved under the persistent excitation condition, which is shown to hold in the simulation.

• Journal of the Korean Institute of Intelligent Systems
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• v.22 no.1
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• pp.56-61
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• 2012

This paper propose the robust stability algorithm for controlling a variable speed wind power system which based on doubly-fed induction generator (DFIG). The control object in the wind power system enables the rotor to rotate without any physical contact by using magnetic force. Generally, the system dynamics of the wind power system has severe nonlinearity and uncertainty so that it is not easy to obtain the control objective. For solving these problems, we propose the fuzzy modelling and robust control algorithm for wind power system. The sufficient conditions for robust controller are obtained in terms of solutions to linear matrix inequalities (LMIs). Simulation results for wind power system based on DFIG are demonstrated to visualize the feasibility of the proposed method.

• 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.

• Journal of the Korean Institute of Intelligent Systems
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• v.19 no.3
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• pp.337-342
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• 2009

This paper concerns delay-range-dependent robust stability and stabilization for time-delay nonliner system via T-S fuzzy model approach. The time delay is assumed to be a time-varying continuous function belonging to a given range. On the basis of a novel Lyapunov-Krasovskii functional, which includes the information of the range, delay-range-dependent stability criteria are established in terms of linear matrix inequality. It is shown that the new criteria can provide less conservative results than some existing ones. Moreover, the stability criteria are also used to design the stabilizing state-feedback controllers. Numerical examples are given to demonstrate the applicability of the proposed approach.

• Journal of the Institute of Convergence Signal Processing
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• v.19 no.2
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• pp.77-88
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• 2018

This paper proposes a RBFNN(Radial Basis Function Neural Network) based decentralized adaptive tracking control scheme using PSO(Particle Swarm Optimization) for an uncertain electrically driven robot system with input saturation. Practically, the magnitudes of input voltage and current signals are limited due to the saturation of actuators in robot systems. The proposed controller overcomes this input saturation and does not require any robot link and actuator model parameters. The fitness function used in the presented PSO scheme is expressed as a multi-objective function including the magnitudes of voltages and currents as well as the tracking errors. Using a PSO scheme, the control gains and the number of the RBFs are tuned automatically and thus the performance of the control system is improved. The stability of the total control system is guaranteed by the Lyapunov stability analysis. The validity and robustness of the proposed control scheme are verified through simulation results.

• Journal of Electrical Engineering and Technology
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• v.13 no.1
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• pp.168-180
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• 2018

In order to achieve the high quality output voltage of single-phase voltage source inverters, in this paper an Adaptive Complementary Sliding Mode Control (ACSMC) is proposed. Firstly, the dynamics model of the single-phase inverter with lumped uncertainty including parameter variations and external disturbances is derived. Then, the conventional Sliding Mode Control (SMC) and Complementary Sliding Mode Control (CSMC) are introduced separately. However, when system parameters vary or external disturbance occurs, the controlling performance such as tracking error, response speed et al. always could not satisfy the requirements based on the SMC and CSMC methods. Consequently, an ACSMC is developed. The ACSMC is composed of a CSMC term, a compensating control term and a filter parameters estimator. The compensating control term is applied to compensate for the system uncertainties, the filter parameters estimator is used for on-line LC parameter estimation by the proposed adaptive law. The adaptive law is derived using the Lyapunov theorem to guarantee the closed-loop stability. In order to decrease the control system cost, an inductor current estimator is developed. Finally, the effectiveness of the proposed controller is validated through Matlab/Simulink and experiments on a prototype single-phase inverter test bed with a TMS320LF28335 DSP. The simulation and experimental results show that compared to the conventional SMC and CSMC, the proposed ACSMC control strategy achieves more excellent performance such as fast transient response, small steady-state error, and low total harmonic distortion no matter under load step change, nonlinear load with inductor parameter variation or external disturbance.

• Advances in concrete construction
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• v.13 no.5
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• pp.385-394
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• 2022

Recently, an increasing number of cutting-edged studies have shown that designing a smart active control for real-time implementation requires piles of hard-work criteria in the design process, including performance controllers to reduce the tracking errors and tolerance to external interference and measure system disturbed perturbations. This article proposes an effective artificial-intelligence method using these rigorous criteria, which can be translated into general control plants for the management of civil engineering installations. To facilitate the calculation, an efficient solution process based on linear matrix (LMI) inequality has been introduced to verify the relevance of the proposed method, and extensive simulators have been carried out for the numerical constructive model in the seismic stimulation of the active rigidity. Additionally, a fuzzy model of the neural network based system (NN) is developed using an interconnected method for LDI (linear differential) representation determined for arbitrary dynamics. This expression is constructed with a nonlinear sector which converts the nonlinear model into a multiple linear deformation of the linear model and a new state sufficient to guarantee the asymptomatic stability of the Lyapunov function of the linear matrix inequality. In the control design, we incorporated H Infinity optimized development algorithm and performance analysis stability. Finally, there is a numerical practical example with simulations to show the results. The implication results in the RMS response with as well as without tuned mass damper (TMD) of the benchmark building under the external excitation, the El-Centro Earthquake, in which it also showed the simulation using evolved bat algorithmic LMI fuzzy controllers in term of RMS in acceleration and displacement of the building.