• Journal of Institute of Control, Robotics and Systems
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• v.9 no.3
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• pp.218-226
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• 2003

Due to the friction characteristics of pump, cylinder packing and passenger car, in the elevation system actuated with hydraulic inverter, there exist dead zones. which cannot be controlled by a PID controller. To overcome the drawbacks, in this paper, we propose a new hybrid fuzzy-sliding mode control scheme, which controls the controller output between a sliding mode control output and a PID control output by fuzzy control method. The proposed hybrid control scheme achieves an improved control performance by using both controllers. We first propose a design method of the hybrid controller far a hydraulic system controlled by inverters, then propose a design method of a hybrid fuzzy-sliding mode centre] scheme. The effectiveness of the proposed control scheme is shown by simulation results, in which the proposed hybrid control method yields better control performance then the PID controlled scheme, not only in the zero-crossing speed region but also in the overall control region including steady-state region.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1998.10a
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• pp.111-116
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• 1998

This paper proposes a robust control using a sliding mode controller and a fuzzy controller. Having the excellent transient response, the sliding mode controller has the poor steady state response, but the fuzzy controller has a good steady state reponse. A proposed controller combined these controllers has the quick response at the initial condition without the errors. The proposed robust nonlinear controller takes the advantage of the fuzzy controller and is the rapid and the stable response in conditions that the sliding mode controller keeps the errors at the steady state. The performance of proposed method is proved by simulation of the inverted pendulum.

• Journal of Institute of Control, Robotics and Systems
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• v.16 no.8
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• pp.735-743
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• 2010

A new Fuzzy sliding mode controller is proposed to improve the cornering performance of the four wheel hybrid vehicles. The Fuzzy sliding mode control is applied for the control of rear motor and EHB (Electro-Hydraulic Brake) to improve the cornering performance. The modeling of the automobile is simplified that each of the two wheels is modeled as two degrees of freedom object and the friction coefficient between the wheel and the ground is assumed to be constant. The output of the Fuzzy sliding mode algorithm is the direct yaw moment for the rear wheels, which compensates for the slip angle. Through the simulations using ADAMS and MATLAB Simulink, the cornering performance of the proposed algorithm is compared to the conventional PID to show the superiority of the proposed algorithm. In the simulation experiments, the J-Turn and single lane change are used for each of the Fuzzy sliding mode algorithm and PID controller with the optimal gains which are tuned empirically.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.999-1004
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• 2005

An algorithm for a hybrid controller consists of a sliding mode control part and a fuzzy logic part which ar purposely for nonlinear systems. The sliding mode part of the solution is based on "eigenvalue/vector"-type controller is used as the backstepping approach for tracking errors. The fuzzy logic part is a Mamdani fuzzy model. This is designed by applying sliding mode control (SMC) method to the dynamic model. The main objective is to keep the update dynamics in a stable region by used SMC. After that the plant behavior is presented to train procedure of adaptive neuro-fuzzy inference systems (ANFIS). ANFIS architecture is determined and the relevant formulation for the approach is given. Using the error (e) and rate of error (de), occur due to the difference between the desired output value (yd) and the actual output value (y) of the system. A dynamic adaptation law is proposed and proved the particularly chosen form of the adaptation strategy. Subsequently VSC creates a sliding mode in the plant behavior while the parameters of the controller are also in a sliding mode (stable trainer). This study considers the ANFIS structure with first order Sugeno model containing nine rules. Bell shaped membership functions with product inference rule are used at the fuzzification level. Finally the Mamdani fuzzy logic which is depends on adaptive neuro-fuzzy inference systems structure designed. At the transferable stage from ANFIS to Mamdani fuzzy model is adjusted for the membership function of the input value (e, de) and the actual output value (y) of the system could be changed to trapezoidal and triangular functions through tuning the parameters of the membership functions and rules base. These help adjust the contributions of both fuzzy control and variable structure control to the entire control value. The application example, control of a mass-damper system is considered. The simulation has been done using MATLAB. Three cases of the controller will be considered: for backstepping sliding-mode controller, for hybrid controller, and for adaptive backstepping sliding-mode controller. A numerical example is simulated to verify the performances of the proposed control strategy, and the simulation results show that the controller designed is more effective than the adaptive backstepping sliding mode controller.

• 제어로봇시스템학회:학술대회논문집
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• 1997.10a
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• pp.732-735
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• 1997

Variable Structure Controller(VSC) is usually known to have robustness to bounded exogenous disturbances. The robustness is attributed to the discontinuous term in the control input. However, this discontinuous term also causes an undesirable effect called chattering. To alleviate chattering, a hybrid controller consisting of VSC and Fuzzy Logic Controller(FLC) is proposed, which belongs to the category of Fuzzy Sliding Mode Controller(FSMC). The role of FLC in FSMC is to replace a fixed gain of a discontinuous term with a time-varying one based on a specified rule base. The characteristics of proposed controller are shown to be similar to those of VSC with a saturation function instead of sign function. The only remarkable difference is the nonlinearity whose form can be adjusted by free parameters, normalize gain, denormalize gain, and membership functions. Applied to AC servo motor, the proposed controller is compared with VSC in a regulation problem as well as a speed tracking problem. The simulation results show a substantial chatter reduction.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.23 no.7
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• pp.29-40
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• 2009

This paper proposes a modeling and controller design approach for a hybrid wind power generation system that considers a fixed wind-turbine and a dump load. Since operating conditions are kept changing, it is challenge to design a control for reliable operation of the overall system To consider variable operating conditions, Takagi-Sugeno (TS) fuzzy model is taken into account to represent time-varying system by expressing the local dynamics of a nonlinear system through sub-systems, partitioned by linguistic rules. Also, each fuzzy model has uncertainty. Thus, in this paper, a modem nonlinear control design technique, the sliding mode nonlinear control design, is utilized for robust control mechanism In the simulation study, the proposed controller is compared with a proportional-integral (PI) controller. Simulation results show that the proposed controller is more effective against disturbances caused by wind speed and load variation than the PI controller, and thus it contributes to a better quality wind-hybrid power generation system.

• Proceedings of the KIEE Conference
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• 1995.07b
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• pp.992-994
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• 1995

FLC has a good performance for complication system or unknown model by using human linguistic method but many part control design are based on expert knowledge or trial-error method and it is difficult to prove stability and robustness of controller. In this paper we improve this problem by setting fuzzy rules by dividing phase plane of error and rate of error change by switching surface. We can guarantee the stability in nonlinear system, and also in fuzzy PID type controller the complexity of controller design is increased by increasing the number of input variables and defining more range of operation if we want performance of more specific rules, thus we need to fine the method to decrease the number of control rules used in FLC design. In this paper the algorithm is validated by simulation using conventional FLC and proposed method.

• Transactions of the Korean Society of Machine Tool Engineers
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• v.18 no.1
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• pp.90-102
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• 2009

In this paper, a tracking control problem for a mechanical servo system with nonlinear dynamic friction is treated. The nonlinear friction model contains directly immeasurable friction state and the uncertainty caused by incomplete modeling and variations of its parameter. In order to provide the efficient solution to these control problems, we propose a hybrid control scheme, which consists of a robust friction state observer, a RFNN estimator and an approximation error estimator with sliding mode control. A sliding mode controller and a robust friction state observer is firstly designed to estimate the unknown infernal state of the LuGre friction model. Next, a RFNN estimator is introduced to approximate the unknown lumped friction uncertainty. Finally, an adaptive approximation error estimator is designed to compensate the approximation error of the RFNN estimator. Some simulations and experiments on the mechanical servo system composed of ball-screw and DC servo motor are presented. Results demonstrate the remarkable performance of the proposed control scheme.

• International Journal of Automotive Technology
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• v.7 no.6
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• pp.729-739
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• 2006

This paper describes an active fault-tolerant control system for an induction motor drive that propels an Electrical Vehicle(EV) or a Hybrid one(HEV). The proposed system adaptively reorganizes itself in the event of sensor loss or sensor recovery to sustain the best control performance given the complement of remaining sensors. Moreover, the developed system takes into account the controller transition smoothness in terms of speed and torque transients. In this paper which is the sequel of (Diallo et al., 2004), we propose to introduce more advanced and intelligent control techniques to improve the global performance of the fault-tolerant drive for automotive applications(e.g. EVs or HEVs). In fact, two control techniques are chosen to illustrate the consistency of the proposed approach: sliding mode for encoder-based control; and fuzzy logics for sensorless control. Moreover, the system control reorganization is now managed by a fuzzy decision system to improve the transitions smoothness. Simulations tests, in terms of speed and torque responses, have been carried out on a 4-kW induction motor drive to evaluate the consistency and the performance of the proposed fault-tolerant control approach.