• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.173.4-173
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• 2001

This paper presents a stable nonlinear adaptive control for AUV(Autonomous Underwater Vehicle) by using neural network. AUV's dynamics are highly nonlinear, and their hydrodynamic coefficients vary with different operational conditions. In this paper, the nonlinear uncertainties of the AUV's dynamics are approximated by using LPNN(Linearly parameterized Neural Network). The presented controller is consist of three parallel terms; linear feedback control, sliding mode control, and adaptive control(LPNN). Lyapunov theory is used to guarantee the stability of tracking errors and neural network´s weights errors. Numerical simulations for nonlinear control of the AUV show the effectiveness of the proposed techniques.

• Proceedings of the KIEE Conference
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• 2008.07a
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• pp.1509-1510
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• 2008

In this paper, we propose a robust adaptive controller for induction motors with uncertainties using nonlinear disturbance observer(NDO). The proposed NDO is applied to estimate the time varying lumped uncertainty which are derived from unknown motor parameters and load torque, but NDO error does not converge to zero since the derivate of lumped uncertainty is not zero. Then the high order neural networks(HONN) is presented to estimate the NDO error such that the rotor speed to converge to a small neighborhood of the desired trajectory. Rotor flux and inverse time constant are estimated by the sliding mode adaptive flux observer. Simulation results are provided to verify the effectiveness of the proposed approach.

• Journal of Electrical Engineering and Technology
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• v.2 no.2
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• pp.280-285
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• 2007

This paper presents a robustly adaptive flux observer for speed-sensorless induction motor control. The proposed approach employs additional robustifying signals to cope with the parametric uncertainties instead of designing an estimator, which has been normally used in power electronic drives. For that, the sliding-mode like adaptive controls are designed and their gain parameters are determined so that the observer dynamics are stable in the sense of Lyapunov, and furthermore they can guarantee the robustness against parametric uncertainties in induction motor systems. Estimated rotor speed is to be used to generate feedback control signal for the speed sensorless vector control system. To show the validity and efficiency of the proposed system, simulation results are presented.

• Journal of Power Electronics
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• v.13 no.6
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• pp.955-963
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• 2013

To acquire a performed and practical solution that is free from chattering, this study proposes the use of an adaptive super-twisting algorithm to drive a single-phase induction motor. Partial feedback linearization is applied before using a super-twisting algorithm to control the speed and stator currents. The load torque is considered an unknown but bounded disturbance. Therefore, a time-varying switching gain that does not require prior knowledge of the disturbance boundary is proposed. A simple sliding surface is formulated as the difference between the real and desired trajectories obtained from the indirect rotor flux oriented control strategy. To illustrate the effectiveness of the proposed control structure, an experimental setup around a digital signal processor (dS1104) is developed and several tests are performed.

• Proceedings of the IEEK Conference
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• 2004.08c
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• pp.616-621
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• 2004

This paper investigated the speed sensorless indirect vector control of a two-phase induction motor to implement adjustable-speed drive for low-power applications. The sliding mode observer estimates rotor speed. The convergence of the nonlinear time-varying observer along with the asymptotic stability of the controller was analyzed. To define the control action which maintains the motion on the sliding manifold, an 'equivalent control' concept was used. It was simulated and implemented on a sensorless indirect vector drive for 150W two-phase induction motor. The simulation and experimental results demonstrated effectiveness of the estimation method.

• Proceedings of the KIEE Conference
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• 2003.07b
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• pp.1138-1141
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• 2003

This paper proposes a new speed and flux estimation method which has the robustness against the variation of the electrical parameters of the motor and the superiority in the dynamic characteristics compared with the conventional sensorless schemes. In the proposed method, the stator currents and the rotor fluxes are observed on the stationary reference frame using the sliding mode concept. And the rotor speed is estimated using the current estimation errors and the observed rotor fluxes based on the Lyapunov stability theory. Also a design method of the observer gain is proposed to minimize the effect of the speed estimation error on the rotor flux observation. The experimental results verified that the proposed method shows more robust and improved performances than the previous estimation method under the variations of motor resistance and inductance.

• Journal of Institute of Control, Robotics and Systems
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• v.22 no.5
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• pp.320-325
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• 2016

This paper presents a robust finite-time sliding mode control (SMC) scheme for unknown disturbance and unmodeled nonlinear friction and dynamics in the robotic manipulator. A finite-time SMC (FSMC) surface and finite-time sliding mode controller are constructed to obtain faster error convergence than the conventional infinite-time based SMC. By adding prescribed constraint control term to a finite-time SMC to compensate for unknown disturbance and uncertainties, a robust control scheme can be designed as well as faster convergence control. In addition, simpler controller structure is built by using feed-forwarding upper bound coefficients of each manipulator dynamic parameters instead of model-based control or adaptive observer to estimate unknown manipulator parameters. Simulation and experimental evaluations highlight the efficacy of the proposed control scheme for an articulated robotic manipulator.

• 제어로봇시스템학회:학술대회논문집
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• 1999.10a
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• pp.133-136
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• 1999

Many researches on the identification of a system have been carried out using a least square method, an adaptive filter, and so on. However, it is difficult to apply these methods in a nonlinear system. In the case of a nonlinear system, it is known that the signal compression method is able to estimate uncertain parameters of linear element in a nonlinear system because it is able to separate linear element and nonlinear element in a nonlinear system. However, the signal compression method cannot be applied to a motion simulator because actuators of the simulator is single-rod cylinders which includes expansion and compression dynamic properties. Therefore, this paper proposes a modified signal compression method which is able to estimate uncertain parameters of the motion simulator dynamics. The dynamic properties of this system are identified by separating expansion and compression properties when applying the signal compression method. And then, the identified parameters are applied to design a sliding mode controller for the simulator. The performance of the designed sliding mode controller is evaluated experimentally.

• International Journal of Computer Science & Network Security
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• v.24 no.2
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• pp.169-177
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• 2024

Interacting Spherical tank has maximum storage capacity is broadly utilized in industries because of its high storage capacity. This two tank level system has the nonlinear characteristics due to its varying surface area of cross section of tank. The challenging tasks in industries is to manage the flow rate of liquid. This proposed work plays a major role in controlling the liquid level in avoidance of time delay and error. Several researchers studied and investigated about reducing the nonlinearity problem and their approaches do not provide better result. Different types of controllers with various techniques are implemented by the proposed system. Intelligent Adaptive Neuro Fuzzy Inference System (ANFIS) based Sliding Mode Controller (SMC) with Fractional order PID controller is a novel technique which is developed for a liquid level control in a interacting spherical tank system to avoid the external disturbances perform better result in terms of rise time, settling time and overshoot reduction. The performance of the proposed system is obtained by analyzing the simulation result obtained from the controller. The simulation results are obtained with the help of FOMCON toolbox with MATLAB 2018. Finally, the performance of the conventional controller (FOPID, PID-SMC) and proposed ANFIS based SMC-FOPID controllers are compared and analyzed the performance indices.

• Journal of the Korean Institute of Intelligent Systems
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• v.13 no.1
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• pp.63-69
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• 2003

The main property of VSC is that the system response is robust and insensitive to parameter variations and external disturbances in the sliding mode if their bounds are known to the designer of the system control. But sometimes these bounds may not be easily obtained. However, fuzzy control provides an effective way to design the controller of the system with the disturbances and parameter variations. Therefore, combination of the best feature of fuzzy control and sliding mode control is considered. When using the conventional VSC, generally the reaching phase problem occurs, which cause the system response to be sensitive to parameter variations and external disturbances. In order to overcome these problems, a robust position control method of the BLDC motor using an adaptive fuzzy VSC without leaching phase is presented.