Showing papers by "Ching-Chih Tsai published in 2005"
TL;DR: Extended Kalman filtering (EKF)-based algorithm for integrating both the subsystems is proposed to obtain reliable attitude and position estimates of the vehicle and to eliminate the accumulation errors caused by wheel slippage and surface roughness.
Abstract: This paper presents methodologies and techniques for fusing inertial and ultrasonic sensors to estimate the current posture of a mobile robot navigating over indoor uneven terrain. This new type of pose tracking system is developed by means of fusing an inertial navigation subsystem (INS) and an ultrasonic localization subsystem. Extended Kalman filtering (EKF)-based algorithm for integrating both the subsystems is proposed to obtain reliable attitude and position estimates of the vehicle and to eliminate the accumulation errors caused by wheel slippage and surface roughness. Experimental results are conducted to illustrate feasibility and effectiveness of the proposed system and method.
20 citations
TL;DR: In this article, an adaptive backstepping flight control law was developed to bestow good flying qualities in longitudinal axis for all flight conditions using the back-stepping procedure, a new type of controller was synthesized in order to accomplish desired responses under a wide range of flight envelope Model-reference tuning of the back stepping controller is employed to achieve the desired responses for allflight conditions Simulation results demonstrate that the proposed method is capable of giving desired closed-loop dynamic performance and robustness against uncertainties within the subsonic and supersonic flight conditions
20 citations
10 Jul 2005
TL;DR: In this article, the authors developed a methodology for trajectory tracking control of a nonholonomic wheeled mobile manipulator with uncertainties and external load changes, and a hybrid robust tracking control system was presented to ensure the velocity tracking ability in spite of the uncertainties.
Abstract: This paper develops a methodology for trajectory tracking control of a nonholonomic wheeled mobile manipulator with uncertainties and external load changes. The proposed control law consists of two levels: kinematics and dynamic levels. First, the auxiliary kinematic velocity control laws for the mobile platform and the onboard manipulator are separately proposed via backstepping. Then, a hybrid robust tracking control system is presented to ensure the velocity tracking ability in spite of the uncertainties. To achieve the goal, a neural network controller is developed to mimic an equivalent control law in the sliding-mode control, a robust controller is designed to incorporate the system dynamics into the sliding surface for guaranteeing the asymptotical stability, and the proportional controller is designed to improve the transient performance for randomly initializing neural network. All the adaptive learning algorithms for sliding-mode neural networks (SMNN) are derived from the Lyapunov stability theory so that the system tracking ability can be guaranteed in the close-loop system no matter the uncertainties occur or not. Simulation results illustrate the feasibility as well as efficacy of the proposed control strategy in comparison with the backstepping method.
17 citations
TL;DR: In this paper, a robust kinematics control law is developed to steer the vehicle to asymptotically follow the desired trajectories, and an adaptive backstepping path tracking control law with robustness is designed to ensure the path tracking for the vehicle with unknown dynamic parameters and changeable time-varying payload.
7 citations
10 Jul 2005
TL;DR: In this paper, the authors developed the flight path angle control for the glide-slope tracking via backstepping design, which is much simpler and easier to construct with localizer controller.
Abstract: This paper develops the flight path angle control for the glide-slope tracking via backstepping design. A candidate controller structure for an aircraft glide-slope tracking is presented. Using the backstepping procedure to synthesize a glide-slope tracking control law is different from designing the guidance and control loops separately in autopilot. The derived glide-slope control law is much simpler and easier to construct with localizer controller. Nonlinear 6DOF simulation results demonstrate that the backstepping tracking law can effectively guide the aircraft along the glide-slope centerline until the flare control before touchdown.
7 citations
10 Jul 2005
TL;DR: In this paper, a new tubular linear induction motor is designed for propelling the elevator to move up and down, in order to overcome the parameter variations caused by the TLIM, a robust PID is used.
Abstract: This paper presents techniques for system design and control of a vertical linear motion system driven by a tubular linear induction motor (TLIM). A new tubular linear induction motor is designed for propelling the elevator to move up and down. With the motor a control system for the motion system is presented. In order to overcome the parameter variations caused by the TLIM, a robust PID is used. Experimental results have shown that the proposed system together with the control is capable of giving desirable performance.
6 citations
TL;DR: A novel path tracking control method is proposed to achieve reference path following missions on a global scale except for an arbitrary small region around the origin; in particular, two special path tracking examples are analyzed with large initial tracking errors.
Abstract: This paper presents regulation and path tracking control methods for wheeled mobile robots (WMRs) associated with kinematic models in two‐dimensional polar coordinates. The proposed two regulation control laws are designed via the Lyapunov indirect and direct stability theorems in order to asymptotically achieve nonlinear regulation. With the Lyapunov‐based stabilization law, a novel path tracking control method is proposed to achieve reference path following missions on a global scale except for an arbitrary small region around the origin; in particular, two special path tracking examples are analyzed with large initial tracking errors. Computer simulations and experimental results are described to confirm the efficacy of these proposed control approaches.
4 citations
24 Oct 2005
TL;DR: Experimental results for the temperature control of a variable-frequency oil-cooling machine have shown the efficacy of the proposed controller under the condition of set-points changes and external disturbances.
Abstract: A model-reference predictive control using recurrent neural network is presented for a class of nonlinear industrial processes. The neural control law is developed to minimize a cost function based on the predictive performance criterion and model reference scheme. A real-time adaptive control algorithm, including a neural predictor and model-reference neural predictive controller, is proposed. The adaptive learning rates for both the neural predictor and controller are chosen based on Lyapunov stability theory. Numerical simulations reveal that the proposed control method gives satisfactory tracking and disturbance rejection performance for two illustrate nonlinear discrete time systems. Experimental results for the temperature control of a variable-frequency oil-cooling machine have shown the efficacy of the proposed controller under the condition of set-points changes and external disturbances.
3 citations
10 Jul 2005
TL;DR: In this paper, the authors developed techniques for position recovery of a free-ranging automatic guided vehicle using a dead-reckoning device and a laser scanner using a simple rectangular model and a 2D laser scanner.
Abstract: This paper develops techniques for position recovery of a free-ranging automatic guided vehicle using a dead-reckoning device and a laser scanner. Extended information filtering (ElF) scheme is presented using a simple rectangular model and a 2-D laser scanner. By continuously updating the robot's pose and matching the laser data with the environmental model, we find that the outliers can be filtered out effectively by validation gate. Moreover, a range-weighted Hough transform (RWHT) is used to extract the modeled lines from the clutter data. Computer simulations and experimental results are performed to illustrate the feasibility and efficacy of the proposed position recovery methods.
3 citations
TL;DR: In this paper, a methodology and technique for 3D posture determination of a mobile robot over uneven terrain is developed by means of integrating a 3D dead-reckoning (DR) subsystem together with a novel ultrasonic localization subsystem for indoor navigation.
Abstract: This paper develops a methodology and technique for three‐dimensional (3D) posture determination of a mobile robot over uneven terrain. The proposed self localization system is developed by means of integrating a 3D dead‐reckoning (DR) subsystem together with a novel ultrasonic localization subsystem for indoor navigation. The extended‐Kalman‐filter (EKF)‐based mutilsensory fusion method is proposed to obtain reliable attitude and position estimates of the vehicle and to eliminate the accumulation errors caused by wheel slippage, surface roughness and wheel misalignment. Experimental results are performed to illustrate the feasibility and effectiveness of the proposed system and method.
3 citations
10 Jul 2005
TL;DR: In this paper, the authors developed methodologies and techniques for semi-autonomous control of a wheeled service robot with a gyro rate and a CCD camera using a joystick.
Abstract: This paper develops methodologies and techniques for semi-autonomous control of a wheeled service robot with a gyro rate and a CCD camera. A mechatronic design approach is used to construct a wheeled service robot vehicle that performs missions at any indoor flat environments. A remote manual control technique is developed using a joystick. Using a rate gyro and a CCD camera, four user-friendly semi-autonomous control operations are proposed to steer the vehicle easily and effectively. Several experiments results are conducted to illustrate the efficacy of the proposed methods.
10 Oct 2005
TL;DR: Experimental results for a variable frequency oil-cooling control process are performed which have shown effectiveness of the proposed method under the conditions of setpoint and load changes.
Abstract: This paper presents a recurrent neural network based predictive control for a class of nonlinear discrete time systems The neural predictive control law is developed from the minimization of a generalized predictive performance criterion A real time adaptive control algorithm, including a neural predictor and a neural predictive controller, is proposed; the adaptive learning rates for both the neural predictor and controller are determined based on Lyapunov stability theory Simulation results reveal that the proposed control gives satisfactory tracking and disturbance rejection performance for two illustrative nonlinear systems Experimental results for a variable frequency oil-cooling control process are performed which have shown effectiveness of the proposed method under the conditions of setpoint and load changes
TL;DR: In this paper, a low-complexity and accurate pose-tracking EKF-based algorithm is proposed using a simple rectangular model and a 2D laser scanner, by continuously updating the robot's pose and matching the laser data with the environmental model, the outliers can be filtered out effectively by validation gate.