• Proceedings of the KIEE Conference
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• 2001.07d
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• pp.2057-2059
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• 2001

A nonlinear adaptive speed controller is designed for induction motors. Only the measurement of the stator current is used to design the controller and the observers. The sliding mode cascade observer is introduced to estimate the stator current and its time derivatives. The open-loop observer are designed to estimate the rotor flux and its time derivatives. The adaptive observer is also designed to estimate the rotor resistance. Sequentially, the rotor speed can be calculated using these estimated values. It is shown that the estimation errors of the corresponding states and the parameter converge to the specified residual set. It is also shown that the speed controller using these estimates is performed well. The experimental results are represented to investigate the validity of the proposed observer and controller.

• International Journal of Precision Engineering and Manufacturing
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• v.6 no.4
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• pp.37-43
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• 2005

This paper presents a hybrid control algorithm for the active noise control in the rectangular enclosure using an active/passive foam actuator. The hybrid control composes of the adaptive feedforward with feedback loop in which the adaptive feedforward control uses the well-known filtered-x LMS(least mean square) algorithm and the feedback loop consists of the sliding mode controller and observer. The hybrid control has its robustness for both transient and persistent external disturbances and increases the convergence speed due to the reduced variance of the jiltered-x signal by adding the feedback loop. The sliding mode control (SMC) is used to incorporate insensitivity to parameter variations and rejection of disturbances and the observer is used to get the state information in the controller deign. An active/passive smart foam actuator is used to minimize noise actively using an embedded PVDF film driven by an electrical input and passively using an absorption-foam. The error path dynamics is experimentally identified in the form of the auto-regressive and moving-average using the frequency domain identification technique. Experimental results demonstrate the effectiveness of the hybrid control and the feasibility of the smart foam actuator.

• The Transactions of the Korean Institute of Electrical Engineers
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• v.45 no.2
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• pp.175-184
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• 1996

In this paper the newly developed discrete-time adaptive sliding mode control method is proposed and applied to the power system stabilization problem. In contrast to the conventional continuous-time sliding mode controller, the proposed method is developed in the discrete-time domain and based on the input/output measurements instead of the continuous-time and the full-states feedback, respectively. Because the proposed control method has the adaptivity property in addition to the natural robustness property of the sliding mode control, it is possible to design the power system stabilizer which can overcome both the minor variations of the parameters of the power system and the diverse operating conditions and faults of the power system. Mathematical proof and the various computer simulations are done to verify the performance and stability of the proposed method.

• Proceedings of the KIEE Conference
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• 2008.07a
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• pp.1505-1506
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• 2008

In this paper, a robust adaptive backstepping control is developed for efficiency optimization of induction motors with uncertainties. The proposed control scheme consists of efficiency flux control(EFC) using a sliding mode adaptive flux observer and robust speed control(RSC) using a function approximation for mechanical uncertainties. In EFC, it is important to find the flux reference to minimize power losses of induction motors. Therefore, we proposed the optimal flux reference using the electrical power loss function. The sliding mode flux observer is designed to estimate rotor fluxes and variation of inverse rotor time constant. In RSC, the unknown function approximation technique employs nonlinear disturbance observer(NDO) using fuzzy neural networks(FNNs). The proposed controller guarantees both speed tracking and flux tracking. Simulation results are presented to illustrate the effectiveness of the approaches proposed.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.52 no.1
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• pp.1-8
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• 2003

In this paper, an observer-based adaptive controller is proposed to control the longitudinal motion of vehicles. The standard gradient method is used to estimate the vehicle parameters, mass, time constant, etc. The inter-vehicle spacing and its derivatives are estimated by using the sliding mode cascade observer introduced in this paper. It is shown that the proposed adaptive controller is uniformly ultimately bounded. It is also shown that the errors of the relative distance, the relative velocity and the relative acceleration asymptotically converge to zero. The simulation results are presented to investigate the effectiveness of the proposed method.

• Smart Structures and Systems
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• v.11 no.3
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• pp.315-329
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• 2013

The construction of an experimental nonlinear structural model with little cost and unlimited repeatability for vibration control study represents a challenging task, especially for material nonlinearity. This paper reports the design, analysis and vibration control of a nonlinear structural experiment platform with adjustable hinges. In our approach, magnetorheological rotary brakes are substituted for the joints of a frame structure to simulate the nonlinear material behaviors of plastic hinges. For vibration control, a separate magnetorheological damper was employed to provide semi-active damping force to the nonlinear structure. A dynamic neural network was designed as a state observer to enable the feedback based semi-active vibration control. Based on the dynamic neural network observer, an adaptive fuzzy sliding mode based output control was developed for the magnetorheological damper to suppress the vibrations of the structure. The performance of the intelligent control algorithm was studied by subjecting the structure to shake table experiments. Experimental results show that the magnetorheological rotary brake can simulate the nonlinearity of the structural model with good repeatability. Moreover, different nonlinear behaviors can be achieved by controlling the input voltage of magnetorheological rotary damper. Different levels of nonlinearity in the vibration response of the structure can be achieved with the above adaptive fuzzy sliding mode control algorithm using a dynamic neural network observer.

• Proceedings of the KIEE Conference
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• 1999.07f
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• pp.2540-2542
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• 1999

This paper presents a new speed and position sensorless control method of permanent magnet synchronous motors based on the sliding mode observer. The sliding mode observer structure and its design method are described. Also, Lyapunov functions are chosen for determining the adaptive law for the speed and the stator resistance estimator. The effectiveness of the proposed observer is confirmed by the experimental results.

• Journal of Electrical Engineering and Technology
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• v.8 no.3
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• pp.516-523
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• 2013

This paper investigates an improved stator flux linkage observer for sensorless permanent magnet synchronous motor (PMSM) drives using a voltage-based flux linkage model and an adaptive sliding mode variable structure. We propose a new observer design that employs an improved sliding mode reaching law to achieve better estimation accuracy. The design includes two models and two adaptive estimating laws, and we illustrate that the design is stable using the Popov hyper-stability theory. Simulation and experimental results demonstrate that the proposed estimator accurately calculates the speed, the stator flux linkage, and the resistance while overcoming the shortcomings of traditional estimators.

• Journal of Auto-vehicle Safety Association
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• v.13 no.1
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• pp.14-25
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• 2021

This paper presents a RLS based adaptive sliding mode observer (A-SMO) for unknown fault reconstruction in longitudinal autonomous driving. Securing the functional safety of autonomous vehicles from unexpected faults of sensors is essential for avoidance of fatal accidents. Because the magnitude and type of the faults cannot be known exactly, the RLS based A-SMO for unknown acceleration fault reconstruction has been designed with relationship function in this study. It is assumed that longitudinal acceleration of preceding vehicle can be obtained by using the V2V (Vehicle to Vehicle) communication. The kinematic model that represents relative relation between subject and preceding vehicles has been used for fault reconstruction. In order to reconstruct fault signal in acceleration, the magnitude of the injection term has been adjusted by adaptation rule designed based on MIT rule. The proposed A-SMO in this study was developed in Matlab/Simulink environment. Performance evaluation has been conducted using the commercial software (CarMaker) with car-following scenario and evaluation results show that maximum reconstruction error ratios exist within range of ±10%.

• Proceedings of the KIPE Conference
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• 1998.10a
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• pp.774-779
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• 1998

For the speed control of motors, the position or speed sensors are necessary to obtain the position information of the rotor. Specially, SRM(Switched Reluctance Motor) needs an accurate rotor position data because both the rotor and the stator have a salient pole structure. High functional sensors like resolver or encoder are expensive and have complex connecting lines to the controller so the pure signals are apt to be mixed with noised. In the sight of SRM drives, the high temperature, heavy dust, and the EMI surroundings reduce the reliability of speed and position sensors. Therefore, the speed and position sensorless control algorithms using observer have been accepted widely. In this paper An adaptive sliding observer is described to control the SRM without speed or position sensors. The adaptive sliding observer is set on the basis of variable structure control theory. The sliding surface is constructed by current error terms and this surface guarantees the errors converge to "zero". The stability of observer is affirmed by Lyapunov stability analysis and popov's hyper stability theory.ty theory.