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Linear electromagnetic actuator is receiving significant attention due to recent advances in power electronics and modern control methods. This research proposes a three-phase tubular linear switched reluctance actuator (LSRA) for application in the semiconductor fabrication industry. The tubular LSRA has a robust construction, low manufacturing and maintenance cost, good fault tolerance capability, and high reliability in a harsh environment, making it an attractive alternative to a permanent magnet linear actuator. However, the tubular LSRA has a long mover, which increases the possibility of the mover deforming during fabrication. So, a new mover design is proposed to overcome the problem. The proposed mover design allows the traveling distance of the actuator to be modified by adding or removing the rings without changing the shaft. The tubular LSRA prototype is fabricated according to the optimized design. To drive the tubular LSRA, a appropriate switching algorithm method are used to provide the correct switching signal. This method is straightforward, while no extensive knowledge of power electronic converter is required. The developed tubular LSRA can generate a maximum static force of 0.65N. Through the open-loop reciprocating motion, the dynamic responses of the tubular LSRA can achieve a maximum velocity of 210mm/s and maximum acceleration of 8m/s2, which are in the performance range for precision mechanism.

In this paper, the Proportional-Integral-Derivative (PID) controller with improved Particle Swarm Optimization (iPSO) algorithm is proposed for the positioning control of nonlinear Electro-Hydraulic Actuator (EHA) system. PID controller is chosen to control the EHA system due to its popularity in industrial applications. The PID controller parameters will be tuned by using the iPSO algorithm to get the lowest overshoot percentage and steady-state error. The conventional PSO algorithm has only one objective function to get the optimum parameters. However, this is not enough to increase the control performance of the EHA system. Therefore, an improved Particle Swarm Optimization (iPSO) that includes the mean error and overshoot percentage as the two objective functions is proposed in this paper. The most popular method in PSO that included two objective functions is Linear Weight Summation (LWS). In this method, the two objective functions are combined with certain weightage into one equation to give the best control performance. This paper focuses on determining the suitable weightage between these two objective functions so that the EHA system can produce the best control performance with less overshoot and less error. Overshoot percentage and steady-state error are used to indicate the best control performance. The results showed that EHA system can perform better by using suitable weightage between the mean error and overshoot percentage.

The usage of the Electro-Hydraulic Actuator (EHA) system in industrial machinery has increasingly attracted public attention nowadays by providing a highly stable output performance due to its incompressible hydraulic fluid. However, the accuracy and positioning control of the hydraulic cylinder are always become issues to engineers or researchers that utilized that actuator. In this paper, a suitable control strategy with a combination of a controller and optimization technique is proposed to control the EHA system. Three types of control strategies are proposed and studied in this paper which are PSO-PID, PSO-SMC, and MOPSO-SMC. This study is conducted through a simulation environment using MATLAB/Simulink with an established EHA system model. This paper focuses on three types of simulation studies which are tracking point analysis, mass variation simulation and pressure variation simulation. The overshoot percentage and steady-state error are used to evaluate and compare the effectiveness of the controller to the EHA system. The simulation results show that the EHA system controlled by MOPSO-SMC having the best output performance with the least overshoot percentage and steady-state error.

Magnetic levitation (maglev) is a way of using electromagnetic fields to levitate objects without any noise or the need for petrol or air. Due to its highly nonlinear and unstable behavior, numerous control solutions have been proposed to overcome it. However, most of them still acquire precise dynamic model parameters, or deep understanding of control theory. To account the complexity in the design procedure, a practical controller consists of classical and modern control approaches are proposed. This chapter presents a practical controller for high positioning performance of a magnetic levitation system. Three strategies of the proposed controller where the PI-PD controller is to enhance transient response, the model-based feedforward control (FF) is incorporated with the PI-PD controller to enhance the overshoot reduction characteristic in attaining a better transient response, and lastly the disturbance compensator (Kz) is integrated as an additional feedback element to reduce the sensitivity function magnitude for robustness enhancement. The proposed controller - FF PI-PD + Kz has a simple and straightforward design procedure. The usefulness of the proposed controller is evaluated experimentally.

Electromyography (EMG) is widely used in various fields to investigate the muscular activities. Since EMG signals contain a wealth of information about muscle functions, there are many approaches in analyzing the EMG signals. It is important to know the features that can be extracting from the EMG signal. The ideal feature is important for the achievement in EMG analysis. Hence, the objective of this paper is to evaluate the features extraction of time domain from the EMG signal. The experiment was setup according to surface electromyography for noninvasive assessment of muscle (SENIAM). The recorded data was analyzed in time domain to get the features. Based on the analysis, three features have been considered based on statistical features. The features was then been evaluate by getting the percentage error of each feature. The less percentage error determines the ideal feature. The results shows that the extracted features of the EMG signals in time domain can be implement in signal classification. These findings could be integrated to design a signal classification based on the features extraction.

A practical control scheme is proposed for a one mass rotary system. It was written to demonstrate the controller performance towards positioning and tracking control. For this system, the Nominal Characteristic Trajectory Following (NCTF) controller is proposed and improved. The objective of NCTF controller is to make the object motion to follow the NCT and ends at it origin. Generally, the NCTF controller consists of a Nominal Characteristic Trajectory (NCT) obtained from open loop response and Proportional Integral (PI) compensator. The CM-NCTF controller is proposed for evaluating the motion performance and compare with the conventional NCTF controller. For positioning control, both NCTF controllers demonstrate almost identical positioning performance. However, for tracking control, CM-NCTF controller demonstrates better tracking performance than the conventional NCTF controller with the smallest motion error presented. Besides, the robustness of the CM-NCTF controller to the variation load is examined.

This paper describes the practical control of non-friction mechanism for precision positioning. Non-friction mechanism is often used for precision positioning. Even though it has a simple structure, still, plant identification is compulsory needed during designing a conventional controller. This makes the controller non- user-friendly and non-practical-used in industry. For overcoming this problem, practical controller based on NCTF (Nominal Characteristic Trajectory Following) controller is proposed. NCTF controller consists of a nominal characteristic trajectory (NCT) and a PI compensator, which is free from exact modeling and parameter identification. The NCT is determined using an open-loop time responses of the mechanism. PI compensator is used to make the mechanism motion to follow the NCT and it is tuned without identification of model parameter. Non-friction mechanism has non-damping characteristic and often has short-working range. A suitable current input to stop the non-damping mechanism within a short working range in open-loop condition and to be able to improve the damping characteristic of the mechanism is necessary. The positioning performances of two different current inputs are examined and discussed. The positioning performance of NCTF control system is evaluated based on simulation and experimental results.

In this paper, the Continuous Motion (CM) NCTF controller is proposed for a point-to-point (PTP) positioning system of a one mass rotary system. For this system, the CM-NCTF controller is designed based on the conventional structure of NCTF controller and improved. The CM-NCTF controller consists of Nominal Characteristic Trajectory (NCT) and Proportional Integral (PI) compensator. It is designed without knowing exact system modeling and parameter evaluation. The NCT is constructed from open loop responses while the PI compensator is designed based on the constructed-NCT itself. The effectiveness of the CM NCTF controller is evaluated and compared with the PID controller for positioning and tracking motion performances experimentally. The robustness of the CM NCTF controller is validated by varying the mass load. Overall, the CM-NCTF controller demonstrates promising positioning and tracking performances, and low sensitivity towards the change of mass load in comparison with the PID controller.

This paper discusses an experimental setup (mechanical testing) & modeling result of pneumatic muscle actuator. In recent times, the Pneumatic Muscle Actuator (PMA) has achieved popularity in the field of research, robotics and industrial application due to its advantages such as light weight actuator, dynamic, powerful and resistant to dust and clean. Due to its nonlinear dynamics, the muscle actuator is difficult to be controlled. In this paper a pneumatic muscle actuator system is developed for motion control purpose. The dynamic system modeling is discussed. Open loop test and static load experiment have been conducted and validated with the mathematical model. Finally, a brief conclusion of the pneumatic muscle actuator experimental setup and dynamic system modeling is made.

This paper presents vertical motion control of a one-legged hopping robot using Central Pattern Generator (CPG). The hopping dynamic of the hopping robot is produced by controlling the motor speed to produce force through the crank to the mass, spring, and damper. The classical controllers; PI and PID controller are designed to control the vertical motion of a one legged hopping robot. The parameters for each PI and PID controller are determined by using Ziegler-Nichols method. However, the outputs produced by the controllers do not reach the desired input. Therefore, a CPG model is designed to integrate with these controllers in order to control the hopping robot. The CPG implementation in a mass-spring-damper model is extended to investigate on its dynamic mechanism and vertical motion during hopping. All of integration controller performances are analyzed based on the dynamic response of the hopping robot to reach the desired height. Statistical method is used to analyze the dynamic response. The statistical features that analyzed are mean, mod, error, minimum and maximum boundary of the hopping height produced. As a result, the integration CPG with PI controller is the best controller for the designed one legged hopping robot in term of the mean of the hopping height and error in achieving the desired height.

This paper discusses about the development of output feedback Sliding Mode Control (SMC) and demonstrates that this controller is able to reject disturbance in a nonlinear system. The designed SMC controller works well to ensure system stability and eliminates disturbance in linear and nonlinear dynamics systems. The approach to develop output feedback controller is by implementing High Gain Observer and the output performance from this controller is compared with the output response from the state feedback SMC. Both designed controllers are constructed in simulation by using MATLAB SIMULINK tool. The required gains involve in the designed control laws are tuned heuristically by trial and error approach. The state response results obtained from the simulations are analyzed. Based on the observation and analysis to the results it shows that the output feedback SMC illustrates smooth state response and reduces the effect of disturbance as provided by the state feedback (SMC) without disturbance.

This project develops an algorithm to optimize the dynamic performance of an industrial robot with aid of vision system technology. It consists of three major phases; (1) theoretical, simulation and practical of forward and inverse kinematics for Fanuc LR Mate 200iB robot to determine their D-H parameters, (2) optimization of robot movements, and (3) implementation of practical tasks. The camera is used as a vision sensor to incorporate an intelligent algorithm for the recognition of coordinates of target objects' and to guide the robot to perform certain tasks. The optimization process involves the control of two parameters known as position (Theta) and speed (omega) of the 3 main axes of the robot. Its forward and inverse kinematics problems will be simulated using Robotic tools of Matlab 7.0 and Roboguide V2.3.2. The simulation results will be compared with the real practical movements. This paper will describe the technique, calculation and method on how the first phase was done.