• International Journal of Control, Automation, and Systems
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• v.2 no.3
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• pp.374-383
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• 2004

This paper presents a neural network adaptive controller for autonomous diving control of an autonomous underwater vehicle (AUV) using adaptive backstepping method. In general, the dynamics of underwater robotics vehicles (URVs) are highly nonlinear and the hydrodynamic coefficients of vehicles are difficult to be accurately determined a priori because of variations of these coefficients with different operating conditions. In this paper, the smooth unknown dynamics of a vehicle is approximated by a neural network, and the remaining unstructured uncertainties, such as disturbances and unmodeled dynamics, are assumed to be unbounded, although they still satisfy certain growth conditions characterized by 'bounding functions' composed of known functions multiplied by unknown constants. Under certain relaxed assumptions pertaining to the control gain functions, the proposed control scheme can guarantee that all the signals in the closed-loop system satisfy to be uniformly ultimately bounded (UUB). Simulation studies are included to illustrate the effectiveness of the proposed control scheme, and some practical features of the control laws are also discussed.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.59 no.7
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• pp.1289-1294
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• 2010

In this paper, a new discrete integral static output feedback variable structure controller based on the a new integral dynamic-type sliding surface and output feedback discrete version of the disturbance observer is suggested for the control of uncertain linear systems. The reaching phase is completely removed by introducing a new proposed integral dynamic-type sliding surface. The output feedback discrete version of disturbance observer is presented for effective compensation of uncertainties and disturbance. A corresponding control with disturbance compensation is selected to guarantee the quasi sliding mode on the predetermined integral dynamic-type sliding surface for guaranteeing the designed output in the integral dynamic-type sliding surface from any initial condition for all the parameter variations and disturbances. Using discrete Lyapunov function, the closed loop stability and the existence condition of the quasi sliding mode is proved. Finally, an illustrative example is presented to show the effectiveness of the algorithm.

• Journal of Mechanical Science and Technology
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• v.15 no.11
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• pp.1472-1481
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• 2001

In this paper, an advanced shift controller that supervises the shift transients with adaptive compensation is presented. Modern shift control systems for vehicle automatic transmission are designe d to provide smooth transients for passengers' comfort and better component durability. In the conventional methods, lots of testing and calibration works have been done to tune gains of the controller, but it does not assure optimum shift quality at all times owing to system variations often caused by uncertainties in shifting hydraulic systems and external disturbances. In the proposed control scheme, an adaptive compensation controller with intelligent supervisor is implemented to achieve improved shift quality over the system variations. The control input pattern which generates clutch pressure commands in hydraulic actuating systems, is updated through a learning process to adjust for each subsequent shift based on continuous monitoring of shifting performance and environmental changes. The proposed algorithm is implemented and evaluated on the experimental test setup. Results from the experimental studies for several operation modes show both improved performance and adaptability of the proposed shift controller to uncertain changes of the shifting environment in vehicle power transmission systems.

• Journal of Institute of Control, Robotics and Systems
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• v.7 no.12
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• pp.973-979
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• 2001

Sliding mode control guarantees robustness in the presence of modeling uncertainties and external disturbances. However, this can be obtained at the cost of high control activity that may lead to chattering As one way to alleviate this problem a boundary layer around sliding surface is typically used. In this case the selection of controller gain, control ban width and boundary layer thickness is a crucial problem for the trade-off between tracking error and chattering. The parameter tuning is usually done by trail-and-error in practice causing significant effort and time. An auto tuning method based on fuzzy rules is proposed in the paper in this method tracking error and chattering are monitored by performance indices and the controller tunes the design parameters intelligently in order to compromise both indices. To demonstrate the efficiency of the propose method a mass-spring translation system and a roboic control system are simulated and tested It is shown that the proposed algorithm is effective to facilitae the parameter tuning for sliding mode controllers.

• International Journal of Control, Automation, and Systems
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• v.5 no.3
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• pp.283-294
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• 2007

In this paper, a nonlinear controller based on adaptive sliding-mode method which has a sliding surface vector including new boundizing function is proposed and applied to a two-wheeled welding mobile robot (WMR). This controller makes the welding point of WMR achieve tracking a reference point which is moving on a smooth curved welding path with a desired constant velocity. The mobile robot is considered in view of a kinematic model and a dynamic model in Cartesian coordinates. The proposed controller can overcome uncertainties and external disturbances by adaptive sliding-mode technique. To design the controller, the tracking error vector is defined, and then the sliding surface vector including new boundizing function and the adaptation laws are chosen to guarantee that the error vector converges to zero asymptotically. The stability of the dynamic system is shown through the Lyapunov method. In addition, a simple way of measuring the errors by potentiometers is introduced. The simulations and experimental results are shown to prove the effectiveness of the proposed controller.

• International Journal of Automotive Technology
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• v.8 no.5
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• pp.555-562
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• 2007

The Variable Valve Timing(VVT) system for high performance is a key technology used in newly developed engines. The system realizes higher torque, better fuel economy, and lower emissions by allowing an additional degree of freedom in valve timing during engine operation. In this study, a model-based control method is proposed to enable a fast and precise VVT control system that is robust with respect to manufacturing tolerances and aging. The VVT system is modeled by a third-order nonlinear state equation intended to account for nonlinearities of the system. Based on the model, a controller is designed for position control of the VVT system. The sliding mode theory is applied to controller design to overcome model uncertainties and unknown disturbances. The experimental results suggest that the proposed sliding mode controller is capable of improving tracking performance. In addition, the sliding mode controller is robust to battery voltage disturbance.

• Journal of Electrical Engineering and Technology
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• v.8 no.4
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• pp.899-910
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• 2013

This paper presents a novel lateral stability control system for electric vehicle based on sideslip angle estimation through Kalman filter using the integration of a single antenna GPS receiver and yaw rate sensor. Using multi-rate measurements including yaw rate and course angle, time-varying parameters disappear from the measurement equation of the proposed Kalman filter. Accurate sideslip angle estimation is achieved by treating the combination of model uncertainties and external disturbances as extended states. Active front steering and direct yaw moment are integrated to manipulate sideslip angle and yaw rate of the vehicle. Instead of decoupling control design method, a new control scheme, "two-input two-output controller", is proposed. The extended states are utilized for disturbance rejection that improves the robustness of lateral stability control system. The effectiveness of the proposed methods is verified by computer simulations and experiments.

• International Journal of Naval Architecture and Ocean Engineering
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• v.12 no.1
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• pp.314-324
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• 2020

Due to the nonlinearity and environmental uncertainties, the design of the ship's steering controller is a long-term challenge. The purpose of this study is to design an intelligent autopilot based on Extended Kalman Filter (EKF) trained Radial Basis Function Neural Network (RBFNN) control algorithm. The newly developed free running model scaled surface vessel was employed to execute the motion control experiments. After describing the design of the EKF trained RBFNN autopilot, the performances of the proposed control system were investigated by conducting experiments using the physical model on lake and simulations using the corresponding mathematical model. The results demonstrate that the developed control system is feasible to be used for the ship's motion control in the presences of environmental disturbances. Moreover, in comparison with the Back-Propagation (BP) neural networks and Proportional-Derivative (PD) based control methods, the EKF RBFNN based control method shows better performance regarding course keeping and trajectory tracking.

• IEMEK Journal of Embedded Systems and Applications
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• v.16 no.4
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• pp.137-143
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• 2021

We propose an adaptive non-singular terminal sliding-mode control for the fast finite-time convergence (FANTSMC) in robot manipulator. The proposed FANTSMC approach is developed to be applied without singularity in robot manipulator, which has a new pole-placement control with the non-singular terminal sliding variable while generating the desirable control torque. Moreover, the switching gain is designed to suppress the time-delayed estimation error appropriately, which aims at providing the high robust tracking performance. Also, the proposed one employs one-sample delayed information to cancel out the system uncertainties and disturbances. For these reasons, it offers strong attraction within the finite time. It is shown that the tracking performance of the proposed FANTSMC approach is guaranteed to be uniformly ultimately bounded through the Lyapunov stability. The effectiveness of the proposed FANTSMC approach is illustrated in simulations, which is compared with that of the up-to-date control approach.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.20 no.11
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• pp.43-51
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• 2021

A robust tracking controller design was developed for a rotary motion control system. The friction force versus the angular velocity was measured and modeled as a combination of linear and nonlinear components. By adding a model-based friction compensator to a nominal proportional-integral-derivative controller, it was possible to build a simulated control system model that agreed well with the experimental results. A zero-phase error tracking controller was selected as the feedforward tracking controller and implemented based on the estimated closed-loop transfer function. To provide robustness against external disturbances and modeling uncertainties, a disturbance observer was added in the position feedback loop. The performance improvement of the overall tracking controller structure was verified through simulations and experiments.