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This paper presents a backstepping-based model reference adaptive controller for a multi-axial system in the presence of external disturbance and saturated input. The proposed controller synthesizes the backstepping technique and the model reference adaptive control method to construct control inputs for recursive structure and uncertain modelling of the multi-axial system. To cope with the limit of saturated input, an auxiliary system is adopted. A dead-zone modification is introduced to avoid the drift phenomenon of adjusted adaptive parameters. The stability of the proposed controller is proven by Lyapunov’s theory while considering the effect of the auxiliary system and the dead-zone modification in the design stage. The effectiveness and performance of the proposed controller are evaluated by experiment on a transformer winding system.

This paper presents a new type of four wheel independent steering automatic guided vehicle (4WIS-AGV) for carrying heavy baggage and proposes a controller for the 4WIS-AGV to track reference trajectories. To do this task, the followings are done. Firstly, a 4WIS-AGV is designed and manufactured for experimental purpose. Secondly, a kinematic modeling for the 4WIS-AGV is introduced based on a single track vehicle model. Thirdly, based on the modeling, a controller is designed based on Backstepping method for the 4WIS-AGV to track reference trajectories. Fourthly, a control system is developed using industrial PC and AVR ATmega128 microcontrollers to implement the designed controller. Finally, simulations and experiments are conducted to verify the effectiveness and performances of the proposed controller in tracking two types of reference trajectories: a trajectory with sharp edges for parallel steering maneuver and a circular trajectory for zero-sideslip maneuver. The results show that the proposed controller can make the 4WIS-AGV track the trajectory with sharp edges and the circular trajectory very well.

This paper presents an implementation and experimental validation of trajectory tracking and fault detection algorithm for sensors and actuators of Automatic Guided Vehicle (AGV) system based on multiple positioning modules. Firstly, the system description and the mathematical modeling of the differential drive AGV system are described. Secondly, a trajectory tracking controller based on the backstepping method is proposed to track the given trajectory. Thirdly, a fault detection algorithm based on the multiple positioning modules is proposed. The AGV uses encoders, laser scanner, and laser navigation system to obtain the position information. To understand the characteristics of each positioning module, their modeling are explained. The fault detection method uses two or more positioning systems and compares them using Extended Kalman Filter (EKF) to detect an unexpected deviation effected by fault. The pairwise differences between the estimated positions obtained from the sensors are called as residue. When the faults occur, the residue value is greater than the threshold value. Fault isolation is obtained by examining the biggest residue. Finally, to demonstrate the capability of the proposed algorithm, it is applied to the differential drive AGV system. The simulation and experimental results show that the proposed algorithm successfully detects the faults when the faults occur.

This paper presents a backstepping-based modified model reference adaptive velocity tracking controller design method to track a trapezoidal reference type of rotational velocity for a winding spindle system (WSS). To design the proposed controller, the following are done. Firstly, the system modeling of the WSS is obtained as a combined form of direct current motor and mechanical parts. Secondly, a modified model reference system with known parameters is chosen according to the dimension of the given system such that its rotational velocity output tracks the trapezoidal reference input of the winding spindle system. Then, the rotational velocity output of the winding spindle system is controlled to track the rotational velocity output of the modified model reference system by designing update laws for updating the adaptive controller parameters. Thirdly, since the system modeling of the winding spindle system is constructed as a recursive structure system, the modified model reference adaptive controller is developed based on backstepping approach. Finally, the effectiveness and performance of the proposed controller are evaluated with comparison to those of a conventional PID controller by experimental results.

This paper proposes a tracking controller for omni-directional automated guided vehicle using backstepping and model reference adaptive control. To design the proposed controller, the followings are done. Firstly, a system modeling is obtained by analyzing a dynamic modeling of an OAGV. Secondly, a backstepping technique is utilized to design the proposed controller since a system modeling has a recursive structure. Moreover, there exist uncertain parameters in the system modeling, a known reference model is utilized so that the output of the reference model tracks a virtual control input. Thirdly, uncertain parameters are estimated by update laws in order that the velocity vector of the OAGV tracks the output vector of the reference model control input. Finally, the stability of the proposed controller is analyzed by Lyapunov theory and the effectiveness of the proposed controller are verified by simulation results.

This paper proposes an obstacle avoidance algorithm for translational and rotational motions of four wheels independent steering (4WIS) automatic guided vehicles (AGV) based on fuzzy potential method (FPM) and backstepping control method. Firstly, the system is described and mathematical modeling is introduced. The AGV consists of 4 wheels driving system, laser measurement system, laser navigation system and industrial PC. Secondly, the Fuzzy Potential Field (FPM) is proposed to obtain an optimal path for an AGV. The shape and the size of the vehicle are considered when the FPM generates the optimal path from the current position to the goal position. This method allows the rectangular shape AGV to avoid unknown obstacles safely and efficiently. Backstepping controller is proposed to track the optimal path generated by FPM. Finally, the simulations are conducted to verify the effectiveness of the proposed algorithm. The simulation results show that the proposed algorithm can make the 4WIS-AGV avoid the obstacles in cluttered environment.

This paper is to design an adaptive trajectory tracking controller for an Automatic Guided Vehicle (AGV) to track the desired reference trajectory with unknown slip. To do this task, the followings are done. Firstly, system description and mathematical modelings of a differential drive AGV system are presented. Kinematic model of AGV is derived based on the wheel configuration and the nonholonomic constraint. Dynamic model of AGV is obtained from the Lagrangian formula. Secondly, an adaptive backstepping trajectory tracking controller is designed. By choosing appropriate Lyapunov function based on its kinematic modeling of AGV system with unknown slip parameter stability is guaranteed, a control law and an update law to estimate the unknown slip parameter can be obtained. The simulation and experimental results show that the proposed controller successfully estimates the unknown parameters and tracks a reference trajectory.

This paper proposes a tracking controller for obstacle avoidance of a quadruped robot using potential functions method. The followings are done for this task. At first, a ceiling-mounted camera system is installed for image processing. The goal point and obstacles are separated and recognized by a color recognition method. Second, a path planning algorithm using potential functions method is proposed to generate the path to avoid obstacles and to plan a path for the quadruped robot to reach from start point to goal point. Third, a quadruped robot is chosen as the mobile platform for this study and the kinematic model for the robot is presented. Fourth, a tracking controller is designed for the quadruped robot to track the trajectory based on the backstepping method using Lyapunov function. Finally, the simulation results are presented to show the effectiveness of the proposed trajectory planning algorithm and the tracking controller. [Keywords — Path tracking ; back stepping ; obstacles avoidance ; potential functions ; quadruped robot ] .

In this paper, stabilization of a 2-degrees-of-freedom (2-DOF) omnidirectional mobile inverted pendulum (OM-IP) is studied. The OM-IP consists of the rod that rotates around a rotary point of a universal joint which is connected at the center of the omnidirectional mobile platform (OMP). For ease of analysis, the OM-IP is decoupled into two subsystems: a 2-DOF inverted pendulum (IP) and an OMP. The IP is a rod that rotates around a universal joint with 2-DOF. The OMP is a body consisting of disk and three omnidirectional wheels that moves on plane and keeps the rod in balance. Dynamic modeling of the 2-DOF OM-IP is presented. From the dynamic equa- tion, an adaptive backstepping control method is proposed to keep the rod in balance. Update law is presented as differential equation of an unknown parameter when the distance from the center of gravity of the rod to the rotary point on the OMP is unknown. Stability of the adaptive controller is proven by using Lyapunov function. Simulation and experimental results show the effectiveness of the proposed controller.

In this paper, stabilization of a 2-degrees-of-freedom (2-DOF) inverted pendulum using an omnidirectional mobile platform (OMP) is studied. The inverted pendulum is a rod that rotating around a universal joint structure with 2-DOF. The OMP consists of platform and three omnidirectional wheels that are moving on x y  plane and keeping the rod balance. The dynamic modeling of the 2-DOF inverted pendulum and the OMP are presented. From the dynamic equation, an adaptive backstepping control method is proposed to keep the rod balance with an assumption that the distance from the center of gravity of the rod to the rotary point on the OMP is unknown. Stability of the adaptive controller is proven by using Lyapunov function. Simulation and experimental results show the effectiveness of the proposed controller.

This paper proposes a controller design for an omnidirectional mobile platform (OMP) with three wheels using adaptive backstepping control. A kinematic modeling and a dynamic modeling of the system with disturbance and friction are presented. Based on the dynamic modeling, an adaptive backstepping controller (ABC) is designed to stabilize the OMP with parameter variations and uncertainties caused by friction and slip to follow a desired path. The controller and update laws are designed based on an adaptive backstepping control theory. It includes two steps: firstly, a virtual state and a stability function are introduced. Secondly, Lyapunov functions for the system are chosen and an adaptive backstepping controller to make the system stabilisable and the update laws to estimate the unknown parameters are obtained. The system stability is guaranteed by the Lyapunov stability theory. The simulation and experimental results are presented to demonstrate the effectiveness of the proposed controller and update laws.

In this paper, a differential sliding mode tracking controller (DSMC) using voltage input is designed for trajectory tracking of the three-wheeled omnidirectional mobile platform (OMP) based on its dynamic modeling with disturbances. First, a tracking error vector is defined, and then a differential sliding surface vector is chosen. A control law is obtained by using Lyapunov direct method with backstepping technique. The control law stabilizes the sliding surface vector and makes the tracking error vector go to zero asymptotically. To implement the designed controllers, a control system is developed based on PIC microcontroller. A camera sensor and encoders are used. The simulation and experiment results are presented to illustrate effectiveness of the proposed controller.

This paper proposes a controller design for an omnidirectional mobile platform (OMP) with three wheels using backstepping control. A kinematic model and dynamic model of the system are presented. Based on the dynamic modeling, a backstepping controller is designed to stabilize the OMP when following a desired path. The controller is designed based on a backstepping control theory. It includes two steps: first, a virtual state and a stability function are introduced. Second, Lyapunov functions for the system are chosen and an equation for the virtual control that makes the system stabile is obtained. The system stability is guaranteed by the Lyapunov stability theory. The simulation and experimental results are presented to demonstrate the effectiveness of the proposed controller.

In this paper, a control scheme that combines a kinematic controller and a sliding mode dynamic controller with external disturbances is proposed for an automatic guided vehicle to track a desired trajectory with a specified constant velocity. It provides a method of taking into account specific mobile robot dynamics to convert desired velocity control inputs into torques for the actual mobile robot. First, velocity control inputs are designed for the kinematic controller to make the tracking error vector asymptotically stable. Then, a sliding mode dynamic controller is designed such that the mobile robot’s velocities converge to the velocity control inputs. The control law is obtained based on the backstepping technique. System stability is proved using the Lyapunov stability theory. In addition, a scheme for measuring the errors using a USB camera is described. The simulation and experimental results are presented to illustrate the effectiveness of the proposed controller.

This paper presents a Kinect camera sensor-based object tracking and following system for the four wheel independent steering automatic guided vehicle (4WIS-AGV) using Kalman filter and backstepping control method. To accomplish this task, the following steps are executed: Firstly, a blue colored object is detected by the Kinect camera sensor using a color-based object detection method and its center coordinates inside the RGB image frames are obtained. The global position coordinates of the detected object and the 4WIS-AGV are obtained using Kinect depth data and NAV200 navigation system. Secondly, a Kalman filter is used to estimate the global position and velocity coordinates of the detected moving object. Thirdly, a backstepping control method using Lyapunov function is adopted for the 4WIS-AGV to perform the object following task. Finally, simulation and experiment are performed to verify the effectiveness of the proposed system. The results show that the 4WIS-AGV with Kinect camera sensor can follow the moving object well with the designed controller.

This paper proposes trajectory tracking algorithm for differential drive type of Automatic Guided Vehicle (AGV) system with the unknown wheel radii using adaptive backstepping control method. To guarantee the tracking errors go to zero, backstepping control method is proposed. By choosing appropriate Lyapunov function based on its kinematic modeling, system stability is guaranteed and a control law can be obtained. In this paper, the unknown radii of left and right wheels caused by uneven load distribution or manufacturing imperfection are considered. To solve this problem, an adaptive law is proposed to estimate the changing of wheels radii. The simulation and experimental results show that the proposed controller successfully estimates the unknown parameters and tracks the reference trajectories.

This paper proposes a tracking controller for obstacle avoidance of an omni-directional mobile vehicle (OMV) using potential function method through a ceiling-mounted camera system. To do this task, the followings were done. At first, for image processing, a ceiling-mounted camera system was installed to get images. The goal point and obstacles were separated and recognized by a color recognition method. Second, potential function method was proposed to generate the shortest path to avoid obstacles from the start point to the goal point. The mobile platform is a mecanum wheel omni-directional vehicle. Third, the tracking controller is designed for the OMV to track a trajectory generated by a path planning algorithm based on the backstepping method using Lyapunov function. Finally, the simulation results were presented to show the effectiveness of the proposed trajectory planning algorithm and tracking controller for obstacle avoidance of the OMV.