Linear And Nonlinear Dynamic Modelling Of Motorized Prosthetic Hand System

This paper described the dynamic modeling of motorized prosthetic finger system.Recently prosthetic hands become more importance because its capability to become potential substitute hand for amputee.By using various type of actuators,prosthetic hands become more practical as it could operate with neuro motors energy which initiated by the Automatic Nervous System (ANS) of the brain.However the mathematical modeling of the system needs to be appropriately determined to ensure the accuracy of the control design later on.This paper explained the linear and nonlinear dynamic modeling of the system using Lagrangian equation.The model of the system is derived by considering the energies of the finger when it is actuated by the DC motor.The linear and nonlinear model based on the Lagrangian function of the motion of the finger is evaluated based on the characteristic of the output response.The results show the significant finding of the output characteristic of the linear and nonlinear dynamic modeling of the system

Movement intention detection using neural network for quadriplegic assistive machine

Biomedical signal lately have been a hot topic for researchers, as many journals and books related to it have been publish. In this paper, the control strategy to help quadriplegic patient using Brain Computer Interface (BCI) on basis of Electroencephalography (EEG) signal was used. BCI is a technology that obtain user's thought to control a machine or device. This technology has enabled people with quadriplegia or in other words a person who had lost the capability of his four limbs to move by himself again. Within the past years, many researchers have come out with a new method and investigation to develop a machine that can fulfill the objective for quadriplegic patient to move again. Besides that, due to the development of bio-medical and healthcare application, there are several ways that can be used to extract signal from the brain. One of them is by using EEG signal. This research is carried out in order to detect the brain signal to controlling the movement of the wheelchair by using a single channel EEG headset. A group of 5 healthy people was chosen in order to determine performance of the machine during dynamic focusing activity such as the intention to move a wheelchair and stopping it. A neural network classifier was then used to classify the signal based on major EEG signal ranges. As a conclusion, a good neural network configuration and a decent method of extracting EEG signal will lead to give a command to control robotic wheelchair

Second Order Sliding Mode Controller for Longitudinal Wheel Slip Control

This paper investigates the longitudinal wheel slip tracking control approach for ground vehicle. A mathematical model of a quarter vehicle undergoing a straight-line braking maneuver is used as the control model. Second order sliding mode (SOSM) control approach using super-twisting technique is proposed to manipulate the braking torque to control the wheel slip. The effectiveness of the SOSM is compared to the conventional sliding mode in the simulations of emergency straight line braking in Simulink. With the SOSM, the chattering phenomenon is eliminated, giving a smooth tracking trajectory and lower slip error and control effort

Optimization Techniques In PID Controller On A Nonlinear Electro-Hydraulic Actuator System

The controller is an important component in the nonlinear control system, especially for the system that needs accuracy in position tracking. Electro-Hydraulic Actuator (EHA) system i s a popular nonlinear system that is used by researchers. Proportional- Integral-Derivative (PID) controller is the most popular controller that is normally used in the industry. This i s mainly because of i ts simplicity in the design process. However, there are three constants that need to be assigned in the PID controller, often we called thi s as the parameters s election process or the PID tuning process. In this paper, a comparison s tudy for the selection process of the PID parameters process will be conducted among Ziegler-Nichols tuning method, conventional Particle Swarm Optimization (PSO) technique and Priority-based Fitness Particle Swarm Optimization (PFPSO) technique. PFPSO is one of the improved versions of the conventional PSO technique. The s imulation study wi ll be conducted on a nonlinear Electro-Hydraulic Actuator (EHA) system. A simple robustness test on the PID controller will be evaluated in terms of actuator internal leakage. Results showed that the PID performed better whe n its controller's parameters are selected using PFPSO technique rather than the Ziegler-Nichols method and conventional PSO technique

The effects of auto-tuned method in PID and PD control scheme for gantry crane system

Gantry crane system is a mechanism in heavy engineering that moves payload such container from one point to another. Generally, experienced operators or experts are required to control manually the gantry position while minimizing the payload vibration or swing oscillation. Therefore, those manpower has to be trained in order to operate the gantry crane system safely and efficiently. Thus, to overcome this problem, a feedback control scheme has been utilized in the system. In this paper, PID and PD controllers are introduced for controlling the trolley displacement and the swing oscillation in the gantry crane system. PID controller is designed for tracking the desired position of the trolley whereas PD controller is implemented to minimize the payload oscillation. The PID and PD parameters are tuned by the auto-tuning method. Simulation results have demonstrated satisfactory response based on control system performances

Chattering Analysis of an Optimized Sliding Mode Controller for an Electro-Hydraulic Actuator System

Wear and tear are usually caused by various factors, which reduce the life span of a mechanical part. In the control engineering of an Electrohydraulic actuator system, the wear and tear can be caused by the system or the controller itself. This article examines the chattering effect that occurs during the sliding mode controller (SMC) design, and its effect on the nonlinear electrohydraulic actuator (EHA) system. To examine the chattering phenomenon, signum function is first applied on the switching function of the SMC. Then, parameters of the controller are obtained using single objective particle swarm optimization (PSO) method. These parameters are then applied to the switching function with hyperbolic tangent function. Lastly, the performance of both functions is analysed and compared based on graph and numerical data. From the output data, chattering phenomenon generated on the signum function is greatly eliminated by using hyperbolic tangent function

Investigation of single cart gantry crane system performance using scheduling algorithm

This paper investigates the implementation of two types of scheduling algorithm to obtain the best performances of the Single Cart Gantry Crane System (GCS). In this research, Deadline Monotonic Priority Assignment (DMPA) and Earliest Deadline First (EDF) scheduling algorithm are chosen to be implemented. The main ideas of this approach is to find the schedule that more compatible and provide more stable result for the system. The Cart performances will be analyzed in term of Settling Time (Ts) and Overshoot (OS). In this study, a simple PID controller that acts as a basic control structure is used. The application of TRUETIME kernel block also is implemented to be executed in a MATLAB environment. It has been demonstrated that implementation of these two algorithms will help this system to be more stabilized according to appropriate execution time

Improved Third Order PID Sliding Mode Controller for Electrohydraulic Actuator Tracking Control

An electrohydraulic actuator (EHA) system is a combination of hydraulic systems and electrical systems which can produce a rapid response, high power-to-weight ratio, and large stiffness. Nevertheless, the EHA system has nonlinear behaviors and modeling uncertainties such as frictions, internal and external leakages, and parametric uncertainties, which lead to significant challenges in controller design for trajectory tracking. Therefore, this paper presents the design of an intelligent adaptive sliding mode proportional integral and derivative (SMCPID) controller, which is the main contribution toward the development of effective control on a third-order model of a double-acting EHA system for trajectory tracking, which significantly reduces chattering under noise disturbance. The sliding mode controller (SMC) is created by utilizing the exponential rule and the Lyapunov theorem to ensure closed-loop stability. The chattering in the SMC controller has been significantly decreased by substituting the modified sigmoid function for the signum function. Particle swarm optimization (PSO) was used to lower the total of absolute errors to adjust the controller. In order to demonstrate the efficacy of the SMCPID controller, the results for trajectory tracking and noise disturbance rejection were compared to those obtained using the proportional integral and derivative (PID), the proportional and derivative (PD), and the sliding mode proportional and derivative (SMCPD) controllers, respectively. In conclusion, the results of the extensive research given have indicated that the SMCPID controller outperforms the PD, PID, and SMCPD controllers in terms of overall performance.

Performance Analysis of Position Tracking Control With PID Controller Using An Improved Optimization Technique

An Electro-Hydraulic Actuator (EHA) system is usually utilized in production industry such as automotive industry which requires precision, high force and long operating hours. When dealing with the production of engineering parts that require precision, high force and long operating hours, a controller is usually required. It is observed from the literature, an appropriate tuning technique is essential in order to obtain optimal controller’s performance. Therefore, a computational tuning technique, namely Priority-based Fitness Particle Swarm Optimization (PFPSO) is proposed to obtain the parameters of the Proportional-Integral-Derivative (PID) controller in this paper. The performance of the EHA system will be evaluated and compared based on the priority characters of the PFPSO tuning technique, which included settling time and overshoot percentage that affect the output results of the EHA system. As a result, it is observed that the priority based on settling time produced a better result, which enhances the steady-state performance of the EHA system that fulfills the requirement of the precision contro