<p>An on-line identifier using Functional Link Network (FLN) and Pole-shift (PS) controller for power system stabilizer (PSS) application are presented in this thesis. To have the satisfactory performance of the PSS controller, over a wide range of operating conditions, it is desirable to adapt PSS parameters in real time. Artificial Neural Networks (ANNs) transform the inputs in a low-dimensional space to high-dimensional nonlinear hidden unit space and they have the ability to model the nonlinear characteristics of the power system. The ability of ANNs to learn makes them more suitable for use in adaptive control techniques.</p> <p>On-line identification obtains a mathematical model at each sampling period to track the dynamic behavior of the plant. The ANN identifier consisting of a Functional link Network (FLN) is used for identifying the model parameters. A FLN model eliminates the need of hidden layer while retaining the nonlinear mapping capability of the neural network by using enhanced inputs. This network may be conveniently used for function approximation with faster convergence rate and lesser computational load.</p> <p>The most commonly used Pole Assignment (PA) algorithm for adaptive control purposes assign the pole locations to fixed locations within the unit circle in the z-plane. It may not be optimum for different operating conditions. In this thesis, PS type of adaptive control algorithm is used. This algorithm, instead of assigning the closed-loop poles to fixed locations within the unit circle in the z-plane, this algorithm assumes that the pole characteristic polynomial of the closed-loop system has the same form as the pole characteristic of the open-loop system and shifts the open-loop poles radially towards the centre of the unit circle in the z-plane by a shifting factor &alpha; according to some rules. In this control algorithm, no coefficients need to be tuned manually, so manual parameter tuning (which is a drawback in conventional power system stabilizer) is minimized. The PS control algorithm uses the on-line updated ARMA parameters to calculate the new closed-loop poles of the system that are always inside the unit circle in the z-plane.</p> <p>Simulation studies on a single-machine infinite bus and on a multi-machine power system for various operating condition changes, verify the effectiveness of the combined model of FLN identifier and PS control in damping the local and multi-mode oscillations occurring in the system. Simulation studies prove that the APSSs have significant benefits over conventional PSSs: performance improvement and no requirement for parameter tuning.</p>

The industrial world of robotics requires leading-edge controllers to match the speed of new manipulators. At the University of Waterloo, a three degree-of-freedom ultra high-speed cable-based robot was created called Deltabot. In order to improve the performance of the Deltabot, a new controller called the QNX Multi-Axis Robotic Controller (QMARC) was developed. QMARC is a PC-based controller built for the replacement of the existing commercial controller called PMAC, manufactured by Delta Tau Data Systems. Although the PMAC has its own real-time processor, the rigid and complex internal structure of the PMAC makes it difficult to apply advanced control algorithms and interpolation methods. Adding unconventional hardware to PMAC, such as a camera and vision system is also quite challenging. With the development of QMARC, the flexibility issue of the controller is resolved. QMARC?s open-sourced object-oriented software structure allows the addition of new control and interpolation techniques as required. In addition, the software structure of the main Controller process is decoupled for the hardware, so that any hardware change does not affect the main controller, just the hardware drivers. QMARC is also equipped with a user-friendly graphical user interface, and many safety protocols to make it a safe and easy-to-use system. <br /><br /> Experimental tests has proven QMARC to be a safe and reliable controller. The stable software foundation created by the QMARC will allow for future development of the controller as research on the Deltabot progresses.

This thesis presents a fuzzy logic controller aimed at maintaining constant tension between two adjacent stands in tandem rolling mills. The fuzzy tension controller monitors tension variation by resorting to electric current comparison of different operation modes and sets the reference for speed controller of the upstream stand. Based on modeling the rolling stand as a single input single output linear discrete system, which works in the normal mode and is subject to internal and external noise, the element settings and parameter selections in the design of the fuzzy controller are discussed. To improve the performance of the fuzzy controller, a dynamic fuzzy controller is proposed. By switching the fuzzy controller elements in relation to the step response, both transient and stationary performances are enhanced. To endow the fuzzy controller with intelligence of generalization, flexibility and adaptivity, self-learning techniques are introduced to obtain fuzzy controller parameters. With the inclusion of supervision and concern for conventional control criteria, the parameters of the fuzzy inference system are tuned by a backward propagation algorithm or their optimal values are located by means of a genetic algorithm. In simulations, the neuro-fuzzy tension controller exhibits the real-time applicability, while the genetic fuzzy tension controller reveals an outstanding global optimization ability.

Thanks to development of power semiconductor devices and integrated circuits, active front-end converters with controllability of bidirectional power flow have become popular and viable in industrial applications. This thesis proposes an improved resonant current control for the active front-end converter with LCL filter. The proposed control consists of a band-pass filter tuned at fundamental frequency and various band-rejected filters resonant at harmonic frequencies to provide fundamental current tracking capability as well as enhance harmonic current rejection. Based on this algorithm, the active front-end converter can control dc voltage with unity power factor by sensing converter output current, LCL filter voltage and dc voltage. This approach also conducts harmonic current rejection under distorted line voltage with no phase-locked-loop used, which is the significant advantage in terms of phase lag of frame transformation and computing effort of digital signal processing. Current tracking performance and harmonic rejection capability of the proposed method are verified based on frequency-domain analysis. Computer simulations and experimental results are also implemented to validate effectiveness.

This paper proposes a sensorless control construction adapting to different speed with DSP2407 as the signal processing control core for rotation compressor. The sensorless control method obtains the rotor position by detecting the back electromotive force signals directly, then obtains better communications and the speed estimation by using digital signal which controlling power switches. Finally ,it carries out speed feedback control and current feedback control to improvt efficiency. Comparing adaptive-step control with traditional-step control and six-step control , the experiment result shows that adaptive-step control has better efficiency and lower vibration.

Based on the Lyapunov stability theorem, two design methodologies of adaptive block backstepping controller is proposed in this thesis for a class of multi-input systems with matched and mismatched perturbations to solve regulation problems. The main difference between these two method is that perturbation estimations are only employed in each virtual control input in the second method, whereas in the first method, the perturbation estimation is only employed in the last block. According to the number of block (m) in the dynamic equations of plant to be controlled, m-1 virtual input controllers are designed from the first block to the (m-1)th block, and the proposed robust controller is designed from the last block. Adaptive mechanisms are employed in each of the virtual input controllers as well as the robust controller, so that the least upper bounds of perturbations and perturbation estimation errors are not required. Furthermore, the dynamic equations of the plant do not need to satisfy the block strict feedback form, and the resultant control system can achieve asymptotic stability or uniformly ultimately boundedness. Finally, a numerical example and a practical example are given for demonstrating the feasibility of the proposed control schemes.

With the development of the network, people are increasingly used to exchanging information on the Internet. Therefore, the capability of robot controller should not be limited to control robots locally. The objective of this thesis is to provide a system, the screenplay based performance platform of Robotic puppet shows (SBPP), commanding multiple robots; each robot performing its own role based on a script composed by the developed authoring tool. Wherever and whenever a user wants to use SBPP, he/she just needs connect to the network and begins to design a script. SBPP consists of three parts: the graphic authoring platform (GAP) of screenplays for robotic puppet shows, the screenplay interpreter (SI) for multi-morphic robots, and robots themself. The work of this thesis is concentrated on the implementation of the GAP and robots (model: DARwIn-OP) control. The GAP provides options for a variety of robots to users. The users can easily design their own robot scripts merely by drag-and-drop operating on icons representing the actions, behavior, and short scripts, respectively. Whenever a script is created or updated, GAP will automatically save the script as an XML file format internally. In addition, robots can be conducted to express their emotions orally by utter the lines composed. The system is demonstrated by a play of ¡§do-as-I-do¡¨ and recoded in a video at YouTube:¡¨ http://www.youtube.com/watch?v=v8ErTOgAQSo¡¨.

The different between Remotely Operated Vehicle (ROV) and Autonomous Underwater Vehicle (AUV) is that ROV is connected with the main computer by the electronic cable, so the operator can control the vehicle depending on the environment showing on the monitor; However, AUV is dependent on the received data to autonomously respond the condition via controlling program. In our research, we wanted to use the General Purpose Controller, which had been developed in the previous experiment, in the mission-mode to construct our AUV system for remaining the original ROV controlling system and switching mode between AUV system and ROV system. The mission was divided into primary and secondary mission written by the txt file which is known as mission script, including execute time, target, and mission type etc. In addition, we used the Watch Dog Timer (WDT) in our AUV for the security procedure. When the mission is failed or over the setting time, the AUV will change to the security mode and go forward to the water surface. The other topic in this research wanted to use the Seafloor Laser Scanner (SLS), which was mounted on the AUV, to improve the scanning efficiency. However, when the scanner was working, the AUV had to maintain the stable altitude to the sea floor, so the accurately output power of thruster is needed to be considered and tested. In this part, we found out the properly controlling way in the small water tank first, and then checked the attitude and scanning system in the swimmer pool and towing tank in NCKU respectively, to prove the ability of SLS of AUV system.

The tube hydroforming (THF) technology has been widely used in manufacturing the lightweight and high strength components. The success of THF is largely dependent on the selection of the loading paths: internal pressure vs. time and axial feeding vs. time. The Finite element method is used to simulate the forming result of different loading paths and reduce the cost of die-testing. T-shape tube hydroforming is investigated adaptive simulation by combining FEM code LS-DYNA with fuzzy logic controller subroutine is proposed. During the simulation process, subroutines can adjust the loading paths according to the values of the minimum tube thickness and its variance. Then, the purpose of better thickness distribution of the formed tube at the side branch is achieved. Comparing with other linear loading paths, this adaptive control method got better results. In experiments, the validity of LS-DYNA applied in THF process is verified and the experimental results by adaptive simulation are better than those by the linear loading paths.

Magnetic suspension systems are highly nonlinear and essentially unstable systems. In this thesis, we utilize a phase-lead controller operating in the inner loop to stabilize the magnetic suspension system at first. Furthermore, we design a fuzzy PID controller operating in the outer loop to overcome the nonlinearity and to improve the system¡¦s performances. Because of setting the parameters in traditional fuzzy PID is a long-winded trial and error, so we adopt non-binary modified adaptive genetic algorithms to help us finding the parameters of fuzzy PID controller. As to the experimental implementation, we set two situations in our experiment test: (1) we utilize fuzzy PID controller with initial voltage to test the positions control, and eliminate the extra disturbance. And, (2) we utilize fuzzy PID controller without initial voltage to control the position of suspension object. For the experimental results, we obtain that the designed fuzzy PID controller not only increases the system¡¦s operating range, but also positions accurately and rapidly, and it meanwhile can eliminate the extra disturbance.