• International Journal of Ocean System Engineering
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• v.3 no.2
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• pp.50-60
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• 2013

This paper presents a novel approach to the design of an adaptive fuzzy sliding mode controller for depth control of an autonomous underwater vehicle (AUV). So far, AUV's dynamics are highly nonlinear and the hydrodynamic coefficients of the vehicles are difficult to estimate, because of the variations of these coefficients with different operating conditions. These kinds of difficulties cause modeling inaccuracies of AUV's dynamics. Hence, we propose an adaptive fuzzy sliding mode control with novel fuzzy adaptation technique for regulating vertical positioning in presence of parametric uncertainty and disturbances. In this approach, two fuzzy approximator are employed in such a way that slope of the linear sliding surface is updated by first fuzzy approximator, to shape tracking error dynamics in the sliding regime, while second fuzzy approximator change the supports of the output fuzzy membership function in the defuzzification inference module of fuzzy sliding mode control (FSMC) algorithm. Simulation results shows that, the reaching time and tracking error in the approaching phase can be significantly reduced with chattering problem can also be eliminated. The effectiveness of proposed control strategy and its advantages are indicated in comparison with conventional sliding mode control FSMC technique.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.50 no.8
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• pp.367-375
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• 2001

In Underwater Flight Vehicle depth control system, the followings must be required. First, it needs robust performance which can get over modeling error, parameter variation and disturbance. Second, it needs accurate performance which have small overshoot phenomenon and steady state error to avoid colliding with ground surface or obstacles. Third, it needs continuous control input to reduce the acoustic noise and propulsion energy consumption. Finally, it needs interpolation method which can sole the speed dependency problem of controller parameters. To solve these problems, we propose a depth control method using Fuzzy Sliding Mode Controller with feedforward control-plane bias term and Neural Network Interpolator. Simulation results show the proposed method has robust and accurate control performance by the continuous control input and has no speed dependency problem.

• Journal of Institute of Control, Robotics and Systems
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• v.16 no.7
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• pp.661-667
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• 2010

This paper presents a failure diagnosis and accommodation strategy which is capable of tolerating faulty actuators of a submersible vehicle. The proposed method is mainly based on a sliding mode control technique. The primary ideas include a performance index to describe the effectiveness of actuators, and a controller reconfiguration strategy using the actuator effectiveness index. The actuator effectiveness proposed in this work is defined as the relationship between the sliding surface and the controlled system behavior. The resulting actuator effectiveness is then used in reconfiguring the controller in order to counteract for the deteriorated control performance in the presence of a faulty actuator. The effectiveness of the proposed method is demonstrated by means of numerical simulations with a submersible vehicle.

• International Journal of Automotive Technology
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• v.5 no.2
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• pp.109-114
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• 2004

This paper presents a closed-loop evaluation of the Vehicle Stability Control (VSC) system using a vehicle simulator. Human driver-VSC interactions have been investigated under realistic operating conditions in the laboratory. Braking control inputs for vehicle stability enhancement have been directly derived from the sliding control law based on vehicle planar motion equations with differential braking. A driving simulator has been validated using actual vehicle driving test data. Real-time human-in-the loop simulation results in realistic driving situations have shown that the proposed controller reduces driving effort and enhances vehicle stability.

• Journal of Electrical Engineering and Technology
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• v.6 no.1
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• pp.67-75
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• 2011

The development of electric vehicle power electronics system control, composed of DC-AC inverters and DC-DC converters, attract much research interest in the modern industry. A DC-AC inverter supplies the high-power motor torques of the propulsion system and utility loads of electric vehicles, whereas a DC-DC converter supplies the conventional low-power and low-voltage loads. However, the need for high-power bidirectional DC-DC converters in future electric vehicles has led to the development of many new topologies of DC-DC converters. The nonlinear control of power converters is an active research area in the field of power electronics. This paper focuses on the use of the fuzzy sliding mode strategy as a control strategy for buck-boost DC-DC converter power supplies in electric vehicles. The proposed fuzzy controller specifies changes in control signals based on the surface and knowledge on surface changes to satisfy the sliding mode stability and attraction conditions. The performance of the proposed fuzzy sliding controller is compared to that of the classical sliding mode controller. The satisfactory simulation results show the efficiency of the proposed control law, which reduces the chattering phenomenon. Moreover, the obtained results prove the robustness of the proposed control law against variations in load resistance and input voltage in the studied converter.

• The Transactions of the Korean Institute of Power Electronics
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• v.12 no.4
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• pp.324-331
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• 2007

This paper studies new estimation method for state of charge (SOC) of the hybrid electric vehicle lithium battery using sliding mode observer. A simple R-C Lithium battery modeling technique is established and the errors caused by simple modeling was compensated by the sliding mode observer. The structure of the sliding mode observer is simple, but it shows robust control property against modeling errors and uncertainties. The performance of the system has been verified by the UUDS test. The test results of the proposed observer system shows robust tracking performance under real driving environments.

• International Journal of Control, Automation, and Systems
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• v.3 no.2
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• pp.217-224
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• 2005

Generally, the underwater flight vehicle (UFV) depth control system operates with the following problems: it is a multi-input multi-output (MIMO) system because the UFV contains both pitch and depth angle variables as well as multiple control planes, it requires robustness because of the possibility that it may encounter uncertainties such as parameter variations and disturbances, it requires a continuous control input because the system that has reduced power consumption and acoustic noise is more practical, and further, it has the speed dependency of controller parameters because the control forces of control planes depend on the operating speed. To solve these problems, an adaptive fuzzy sliding mode controller (AFSMC), which is based on the decomposition method using expert knowledge in the UFV depth control and utilizes a fuzzy basis function expansion (FBFE) and a proportional integral augmented sliding signal, is proposed. To verify the performance of the AFSMC, UFV depth control is performed. Simulation results show that the AFSMC solves all problems experienced in the UFV depth control system online.

• Journal of Ocean Engineering and Technology
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• v.20 no.6 s.73
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• pp.7-17
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• 2006

Depth and heading control of an AUV are considered to follow the predetermined depth and heading angle. The proposed control algorithm is designed. based on a sliding mode control using estimated hydrodynamic coefficients. The hydrodynamic coefficients are estimated with conventional nonlinear observer techniques, such as sliding mode observer and extended Kalman filter. By using the estimated coefficients, a sliding mode controller is constructed for the combined diving and steering maneuver. The simulation results of the proposed control system are compared with those of control system with true coefficients. This paper demonstrates the proposed control system, discusses the mechanisms that make the system stable and follows the desired depth and heading angle, accurately, in the presence of parameter uncertainty.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.57 no.5
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• pp.839-844
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• 2008

A novel state of health estimation method for hybrid electric vehicle lithium battery using sliding mode observer has been presented. A simple R-C circuit method has been used for the lithium battery modeling for the reduced calculation time and system resources due to the simple matrix operations. The modeling errors of simple model are compensated by the sliding mode observer. The design methodology for state of health estimation using dual sliding mode observer has been presented in step by step. The structure of the proposed system is simple and easy to implement, but it shows robust control property against modeling errors and temperature variations. The convergence of proposed observer system has been proved by the Lyapunov inequality equation and the performance of system has been verified by the sequence of urban dynamometer driving schedule test. The test results show the proposed observer system has superior tracking performance with reduced calculation time under the real driving environments.

• Transactions of the Korean Society of Automotive Engineers
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• v.13 no.1
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• pp.83-89
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• 2005

This paper presents vehicle stability control algorithm based on 3-DOF vehicle model. The brake control inputs have been directly derived from the sliding control law based on a three degree of freedom plane vehicle model with differential braking. The simulation has performed using a full nonlinear 3-dimensional vehicle model and the performance of the controller has been compared to that of a direct yaw moment controller. Simulation results show that the proposed controller can provide a vehicle with better performance than conventional controller with respect to brake actuation without compromising stability at critical driving conditions.