Mohd Azraai Mohd Razman

Bouc-Wen Model Parameter Identification for a MR Fluid Damper Using Particle Swarm Optimization

This paper present parameter identification fitting which are employed into a current model. Irregularity hysteresis of Bouc-Wen model is colloquial with magneto-rheological (MR) fluid damper. The model parameters are identified with a Particle Swarm Optimization (PSO) which involves complex dynamic representation. The PSO algorithm specifically determines the best fit value and decrease marginal error which compare to the experimental data from various operating conditions in a given boundary.

Modelling and Control of an Upper Extremity Exoskeleton for Rehabilitation

This paper presents the modelling and control of a two degree of freedom upper extremity exoskeleton for rehabilitation. The Lagrangian formulation was employed to obtain the dynamic modelling of both the anthropometric based human upper limb as well as the exoskeleton that comprises of the upper arm and the forearm. A proportional-derivative (PD) architecture is employed to investigate its efficacy performing a joint task trajectory tracking in performing flexion/extension on the elbow joint as well as the forward adduction/abduction on the shoulder joint. An active force control (AFC) algorithm is also incorporated into the aforementioned controller to examine its effectiveness in compensating disturbances. It was found from the study that the AFC-PD performed well against the disturbances introduced into the system without compromising its tracking performances as compared to the conventional PD control architecture.

System integration and control of Dynamic Ankle Foot Orthosis for lower limb rehabilitation

Gait disorder is the inability of a person to assume upright position, maintain neither balance nor the aptitude to initiate and sustain rhythmic stepping. This form of disability may originate from cerebellar disease, stroke, spinal injury, cardiac disease or other general conditions that may bring about such disorder. Studies have shown that ones mobility may be improved with continuous locomotor activity. Traditional rehabilitation therapy is deemed labour as well as cost intensive. Rehabilitation robotics has been explored to address the drawbacks of conventional rehabilitation therapy and the increasing demand for gait rehabilitation. This paper presents a simple yet decent technique in the control and actuation of a new Dynamic Ankle-Foot Orthosis (DAFO) designed to rehabilitate the dorsiflexion and plantarflexion motion of the ankle. The DAFO is equipped with two force sensitive resistors (FSR), which act as a limit switch controlling the actuation of the DC motor to a certain dorsiflexion/plantarflexion motion according to the gait phases detected. The results show that the two FSR sensors are sufficient to detect gait phases and act as limit switches to control the actuation of the ankle DC motors, and thus proving the potential of the current system and design for future application.

The Identification and Control of a Finger Exoskeleton for Grasping Rehabilitation

This paper evaluates the efficacy of different classical control architectures in performing grasping motion. The exoskeleton system was obtained via system identification method in which the input and output data was measured by means of current sensor (ACS712) and encoder attached to a DC geared motor (SPG30e-270k). The data obtained is split with a ratio of 70:30 for estimation and validation, respectively. The transfer function of the system is evaluated by varying the number of poles and zeros that are able to fit well with validation data. The performance of the classical P, PI, PD and PID control techniques were then evaluated in its ability to track the desired trajectory. It was demonstrated from the study that the PID controller provides the least steady state error as well as a reasonably fast settling time.

The Identification of hunger behaviour of lates calcarifer using k-nearest neighbour

Fish Hunger behaviour is essential in determining the fish feeding routine, particularly for fish farmers. The inability to provide accurate feeding routines (under-feeding or over-feeding) may lead to the death of the fish and consequently inhibits the quantity of the fish produced. Moreover, the excessive food that is not consumed by the fish will be dissolved in the water and accordingly reduce the water quality through the reduction of oxygen quantity. This problem also leads to the death of the fish or even spur fish diseases. In the present study, a correlation of Barramundi fish-school behaviour with hunger condition through the hybrid data integration of image processing technique is established. The behaviour is clustered with respect to the position of the school size as well as the school density of the fish before feeding, during feeding and after feeding. The clustered fish behaviour is then classified through k-Nearest Neighbour (k-NN) learning algorithm. Three different variations of the algorithm namely, fine, medium and coarse are assessed on its ability to classify the aforementioned fish hunger behaviour. It was found from the study that the fine k-NN variation provides the best classification with an accuracy of 88%. Therefore, it could be concluded that the proposed integration technique may assist fish farmers in ascertaining fish feeding routine.

The Control of an Upper Extremity Exoskeleton for Stroke Rehabilitation by Means of a Hybrid Active Force Control

This paper evaluates the efficacy of a hybrid active force control in performing a joint based trajectory tracking of an upper limb exoskeleton in rehabilitating the elbow joint. The plant of the exoskeleton system is obtained via system identification method whilst the PD gains were tuned heuristically. The estimated inertial parameter that enables the AFC disturbance rejection effect is attained by means of a non-nature based metaheuristic optimisation technique known as simulated Kalman filter (SKF). It was demonstrated that the proposed PDAFC scheme outperformed the classical PD algorithm in tracking the prescribed trajectory in the presence of disturbance attributed by the limb weight.

A hybrid joint based controller for an upper extremity exoskeleton

This paper presents the modelling and control of a two degree of freedom upper extremity exoskeleton. The Euler-Lagrange formulation was used in deriving the dynamic modelling of both the human upper limb as well as the exoskeleton that consists of the upper arm and the forearm. The human model is based on anthropometrical measurements of the upper limb. The proportional-derivative (PD) computed torque control (CTC) architecture is employed in this study to investigate its efficacy performing joint-space control objectives specifically in rehabilitating the elbow and shoulder joints along the sagittal plane. An active force control (AFC) algorithm is also incorporated into the PD-CTC to investigate the effectiveness of this hybrid system in compensating disturbances. It was found that the AFC- PD-CTC performs well against the disturbances introduced into the system whilst achieving acceptable trajectory tracking as compared to the conventional PD-CTC control architecture.

Altitude and Attitude Control of a Trirotor UAV

This paper outlines the dynamic modelling as well as the attitude and altitude control of a rotary based unmanned aerial vehicle (UAV). A multirotor vertical take-off and landing (VTOL) UAVs, namely Trirotor aircraft is investigated. In essence the the trirotor model consists of three DC motors equipped with three fixed pitch angle rotors without the aid of a swashplate. The mathematical modelling of this multirotor is governed by the Newton-Euler formulation. A classical control algorithm viz. heuristic (Proportional-Integral-Derivative) PID tuning was adopted in the attitude and altitude control of this particular multirotor configuration. It was established from the Simulink simulations that, a PD controller was suffice to control the attitude whilst PID was apt for controlling the altitude of this form of multirotor.