Anan Suebsomran

Balancing control of bicycle robot

This paper addresses the development of the bicycle robot with balancing control. The flywheel is a device to control bicycle robot stabilizing in a prescribed roll angle. Balancing of bicycle maintains by the rotating of two flywheels with a constant angular velocity. There are composed of two fly wheels, upper and lower fly wheel. The rotations around pitch axis of two fly wheels in different directions cause the change of angular momentum with time. The torque will produce due to weight changing of fly wheel and its direction is proportional to rotating axis. The result from summation of torque from two fly wheels will be set to zero at stable point. To tracking with desired roll angle, PD controller is used to tracking the roll angle by controlling the pitch angle of fly wheels according to a prescribed control of roll angle. The results balancing control of bicycle robot stabilization are shown by simulation methods.

Design and simulation of a novel indoor mobile robot localization method using a light-emitting diode positioning system

A key problem of mobile robots is that of the positioning capability in order to detect their locations in the operating environment. A promising technology used in indoor localization recently is Visible Light Communication (VLC). In this paper, an integrated Angle of Arrival-Received Signal Strength (AOA-RSS) localization method using the VLC, which could get high accuracy with simple hardware, is proposed. In addition, the Extended Kalman Filter (EKF) and Particle Filter (PF) algorithms are combined with the proposed AOA-RSS localization method in order to achieve higher accuracy of the mobile robot positioning. By computer simulation, the performance of the proposed AOA-RSS localization method combined with the EKF and PF algorithms are compared. The combination scheme outperforms the individual VLC localization with small error approximation of a few centimetres.

Improvement of the VLC localization method using the Extended Kalman Filter

This paper deals with localization problem of mobile robots in indoor environment based on Visible Light Communications (VLC). We propose an integrated AOA-RSS localization method of Angle of Arrival (AOA) and Received Signal Strength (RSS) methods to find out position of a mobile robot using an array of photodiodes (PDs). Performance of the integrated localization method depends on the number of PDs mounted on the mobile robot. In order to achieve more accurately in positioning the mobile robots location, we propose a combination of the proposed AOA-RSS localization method and the Extended Kalman Filter (EKF) algorithm. The efficiency of this combination is proved through computer simulation. The EKF also addresses a significant problem in robot navigation that is to control the mobile robot moving on the specified path in a certain activity.

Optimal Control of Electromagnetic Suspension EMS System

This paper presents the controller design of magnetic levitation application. The highly nonlinear electromag- netic suspension EMS system is hard and limited system control subjected to prescribed stability of system. Due to the nonlinear dynamics of system, the linearization of the nonlinear EMS plant is described by linear model. An attraction force about the prescribed nominal operating point of current and air gap positioning is chosen for linearization by a nominal operating point. Optimal control is applied for controlling nonlinear dynamics of EMS plant. Linear quadratic regulator (LQR) controller applies for this control objective. The system stability is proofed by using Lyapunovs method. From the results the reference of air gap position can be tracked with the desired nominal operating control as shown in simulation and practical manner. Electromagnetic suspension EMS system is significantly applied in advanced technology such as ground transporta- tion, magnetic bearing and other applications. Control of electromagnetic suspension EMS system is a key technology but has some difficulties due to its nonlinearity, instability, and uncertainty. To overcome the problems mentiond. This research focuses on designing the control system for increas- ing the performance of EMS system. Normally many re- searchers applied the nonlinear control for EMS system. From references (1) proposed nonlinear state and output- feedback H ! controllers to suppress guide way induced dis- turbances. From experiment result, air-gap position can be controlled at 4 mm at nominal operating point. (2) also pro- posed the designed linear quadratic state feedback regulator. It can maintain the closed-loop stability in the presence of some certain actuator failures. The control of such a system is applied to fault control application of electromagnets sus- pension model of maglev train. The simulation study of the design is done by numerical study of magnetic levitation model in linear model. (3) presented the results on the robust stabilization of a class of feedback linearized nonlinear sin- gle-input/single-output (SISO) systems with parametric un- certainty. They implemented of nonlinear feedback lineariz- ing control for an electromagnetic suspension EMS system. Comparison on the technique of feedback linearization and classical state feedback control by using linearization with small perturbation is demonstrated by practical experiment. They concluded that feedback linearization control yielded the stable control of tracking at air gap reference, while the classical state feedback control using linearization at small perturbation could not keep system stable. The model of dy- namics and control of electromagnetic suspension is de- scribed by (4). And (5) also proposed the applied magnetic levitation for educational purpose. They described the opera- tion of a pulse width modulation converter in a magnetic suspension system. The pulse width-modulated (PWM) con- verter illustrates modern principles of power electronics, such as PWM control, current-mode control, averaged and linearized models of switched-mode converters, and power supply design. The experimental system shown the levitation control with diameter 6 cm and weight 0.8 kg of a metallic sphere. (6) applied the laser displacement measurement for the feedback control of air gap of magnetic levitation and suspension system. Then system is increased the accuracy and smoothness of control output signal due to the high reso- lution of feedback measurement device.

The Study of Cooling Process on Runout Table by Simulation Method

This research aims to achieving the effective cooling parameter on the runout table (ROT) of strip steel in hot rolling process. The 2-dimensional transient heat conduction is developed including the external force convection and heat source due to translational motion. The material property, boundary, and initial condition are defined and bounded to model geometry. The strip velocity, cooling water temperature, and external fluid velocity are chosen for the influent parameters during cooling process at ROT. To find the optimality of cooling operating requirement, simulation study is conducted throughout this research. To reach the objective of optimal cooling consumption at ROT, temperature distribution in the strip steel during cooling governs by the form of heat transfer equation. To solve 2-dimensional transient heat conduction by numerical methods, the backward difference formula (BDF) applies to discretization of partial differentiation equation (PDE). The parallel sparse direct linear solver (PARDISO) and conjugate gradients method are comparatively applied to computation in linear algebraic equation. The simulation studies are divided into 12 case studies with three variations subjected to cooling conditions at ROT. From simulation results, the range of such three variations can be identified in relation to economic cooling system and desired quality of products.

Estimation and control of Automatic Guided Vehicle

In this paper a control strategy of Automatic Guided Vehicle (AGV) is proposed. The structure of AGV is described. The strategy is based on two main purposes: the path is stored in the PLC memory and the vehicle displacement is calculated form the wheel rotation measurement. The control and localisation systems are developed. Reference path and observation measurement are matched. To keep track of the matching result of both positions, the estimated position information used to update the vehicles position by using the Kalman Filtering (KF) algorithm. Test performance is verified with accurate positioning control by simulation and experimentation.

3D-Shape Recognition Based Tactile Sensor

a surface recognition algorithm capable of determining contact surfaces types by means of tactile sensor fusion is proposed. The authors present a recognition processes for 3-dimensional deformations in a 2-dimensional parametric domain. Tactile information is extracted by physical contact with a grasped object through a sensing medium. Information is obtained directly at the interface between the object and the sensing device and relates to three-dimensional position and orientation of the object in the presence of noise. The technique called “eigenvalue trajectory analysis”, is introduced and adopted for specifying the margin of classification and classification thresholds. The authors demonstrate mathematically that this approach, which complements existing work, offers significant computational advantages when applied to challenging contact scenarios such as dynamic recognition of contact deformations.

Heading Control of a RC Helicopter by Fuzzy Logic

This research aims to control the heading of a small RC helicopter based on fuzzy logic control approach. Control of such a vehicle is normally nonlinear system. To be linear system, the mathematical model of this system would be archived and its parameters. From such difficulty of obtaining mathematical model and parameters, thus in this propose we develop the heading control of a small RC helicopter by using fuzzy logic control, which is overcome the unmodeling of such vehicle, for objective of developed control system. The performance of system is specified to control in time domain design specification. The rule based construction for designing the fuzzy system is related to input and output membership function for inference fuzzy system. Second order response time is specified, and error e and delta error (e) are conditionally assigned for constructing the rule of fuzzy inference system using Mamdani reasoning scheme. Defuzzification method applies the center of gravity (COG) method to computation the output to compensate the error and delta error signal. Finally the result of experiment reveals that the tracking of control of desire heading command and feedback signal is archived via the desired control performance in heading control of a small RC helicopter system.

Digital PID Controller Design of Electromagnetic Suspension (EMS) System

This paper presents the digital PID controller design of magnetic levitation application. The highly nonlinear of electromagnetic suspension (EMS) system is hardly and limited the system control subjected to prescribed stability of system. Due to the nonlinear dynamics of system, the linearization of the nonlinear EMS plant is described by linear model. An attraction force about the prescribed nominal operating point of current and air gap positioning is chosen for linearization at a nominal operating point. Such a linear system, digital PID controller is designed for controlling the EMS plant. The system stability is validated by experiment methods. From the results, the reference of air gap position can be tracked with the desired nominal operating air gap position control as shown in practical manner.

Direct adaptive neuro control for teleoperation

This paper presents the controller design of teleoperation system. Many of uncertainty during operations through the reciprocal interaction occur at each subsystem side, master and slave. Since teleoperation applies in different places, thus control effort is hard to obtaining the certain parameters due to the fidelity of human and machine to perform some task. This research is proposed the direct adaptive neuro control. With approximation of uncertainty parametric system, radial basis function network (RBFN) is employed to approximate an uncertainty come up with input signal. This approximate signal is fed to model reference adaptive control structure with adaptive law. Disturbance is generated to incorporate with system. The result of teleoperation system is clearly explained in simulation fashion with the comparison to performance of controller. Finally we can be concluded that the purpose of design system can work well in the teleoperation applications.