University of Macau / Faculty of Science and Technology / Department of Electromechanical Engineering

The first part of this thesis deals with studying the effect of the specified bathymetric resolution and ideal bathymetric form parameters on the output from the wave and hydrodynamic modules of Delft-3D. This thesis then describes the use of an optimization to effectively reduce the required bathymetric sampling for input to a numerical forecast model, by using the model’s sensitivity to this input. A genetic algorithm is developed to gradually evolve the survey path for a ship, AUV, or other measurement platform to an optimum, with the resulting effect of the corresponding measured bathymetry on the model, used as a metric. Starting from an initial simulated set of possible random or heuristic sampling paths over the given bathymetry using certain constraints like limited length of track, the algorithm can be used to arrive at the path that would provide the best possible input to the model under those constraints. This suitability is tested by a comparison of the model results obtained by using these new simulated observations, with the results obtained using the best available bathymetry. Two test study areas were considered, and the algorithm was found to consistently converge to a sampling pattern that best captured the bathymetric variability critical to the model prediction.

The reliability of networking and communication systems is vital for the nation's economy and security. Optical and cellular networks have become a critical infrastructure and are indispensable in emergency situations. This dissertation outlines methods for analyzing such infrastructures in the presence of catastrophic failures, such as a hurricane, as well as accidental failures of one or more components. Additionally, it presents a method for protecting against the loss of a single link in a multicast network along with a technique that enables wireless clients to efficiently recover lost data sent by their source through collaborative information exchange. Analysis of a network's reliability during a natural disaster can be assessed by simulating the conditions in which it is expected to perform. This dissertation conducts the analysis of a cellular infrastructure in the aftermath of a hurricane through Monte-Carlo sampling and presents alternative topologies which reduce resulting loss of calls. While previous research on restoration mechanisms for large-scale networks has mostly focused on handling the failures of single network elements, this dissertation examines the sampling methods used for simulating multiple failures. We present a quick method of nding a lower bound on a network's data loss through enumeration of possible cuts as well as an efficient method of nding a tighter lower bound through genetic algorithms leveraging the niching technique. Mitigation of data losses in a multicast network can be achieved by adding redundancy and employing advanced coding techniques. By using Maximum Rank Distance (MRD) codes at the source, a provider can create a parity packet which is e ectively linearly independent from the source packets such that all packets may be transmitted through the network using the network coding technique. This allows all sinks to recover all of the original data even with the failure of an edge within the network. Furthermore, this dissertation presents a method that allows a group of wireless clients to cooperatively recover from erasures (e.g., due to failures) by using the index coding techniques.

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.

Optimization problems are divided into numerical optimization problems and combinatorial optimization problems. Genetic algorithms (GAs) are applied to solve optimization problems widely. GAs with multi-parent crossover are often used to solve numerical optimization problems. However, no effective multi-parent crossover is used for combinatorial optimization problems. Partially mapped crossover (PMX) is the most popular crossover for combinatorial optimization problems. In this thesis, we propose multi-parent partially mapped crossover (MPPMX). A large amount of experimental results show that the improvement ratio of MPPMX reaches 38.63 % over PMX. The p-values of t-test on the difference between MPPMX and PMX range from 10-6 to 10-14, which indicates the significant improvement of MPPMX over PMX.

There exist various applications of transportation of slurries through pipelines all over the world. In the present study, the problem is formulated as a &quot / transportation problem&quot / to determine the pipe diameters and amounts of slurry to be transported from the demand (production) points to the processing (factory) points. The minimization of the cost consisting of the pipe and energy cost terms is considered as the objective function to determine the stated decision variables. Pipe cost is given as the function of pipe diameters and the energy cost is defined as function of pipe diameters and slurry amounts. Energy cost is obtained by using the relation that is previously determined after the experimental studies made for the magnetite ore. The optimization method used in the study is genetic algorithm method. A commercially available software written in C language is used and modified for the present study The proposed methodology to solve this nonlinear programming problem is applied to a transportation system and it is seen that the methodology made the complex, labor intensive equation solution process very convenient for the users.

Abstract Magnetic suspension systems are highly nonlinear and essentially unstable systems. In this thesis, we facilitate the position control problem for the DC electromagnetic suspension system. We utilize a phase-lead controller operating in the inner loop to stabilize the system first, and try to design a PID fuzzy logic controller (PIDFLC) operating in the outer loop to overcome the nonlinearity of the system and to improve the system¡¦s performance. Since the work of setting fuzzy control parameters is a long-winded trial and error, we adopt non-binary modified GAs to help us setting and optimizing parameters. As experimental results show that the designed PIDFLC not only increases the system¡¦s operating range, but also positions accurately and rapidly; meanwhile, it has the ability to eliminate extra disturbance. In addition, comparing with other control theories, the control method which we utilize is easier to be implemented.

In this study, the non-binary coding, elitist strategy, increasing mutation rate, extinction, and immigration strategy are used to improve the simple genetic algorithms. The improved search technique can reduce the possibility of falling into the local optimum due to the premature convergence in a large searching space, and increase the chance of finding out the near-optimal parameters. The hydraulic forming machine used in this thesis, includes a power source of a hydraulic motor and a actuator of two hydraulic cylinders. Both the internal pressure and axial force are controlled to hydroform the tubes into the shapes we want. The PID fuzzy logic controller is implemented to control the proportional direction valve and pressure reducing valve of this dual-cylinder electro-hydraulic system so that the loading path can follow the optimal forming curve of axial-feeding and pressure prescribed. From the experimental results, it is clear that the near-optimal PIDFLC controller designed via modified genetic algorithms can make the loading path follow the prescribed curve, and effective for reducing system uncertainty caused by the varying loads and system unstability resulting from the nonlinear characteristics of the hydraulic system.

The problem of observing a given set of Earth target sites within an assigned time frame is examined. Attention is given mainly to visiting these sites as sub-satellite nadir points. Solutions to this problem in the literature require thrusters to continuously maneuver the satellite from one site to another. A natural solution is proposed. A natural solution is a gravitational orbit that enables the spacecraft to satisfy the mission requirements without maneuvering. Optimization of a penalty function is performed to find natural solutions for satellite orbit configurations. This penalty function depends on the mission objectives. Two mission objectives are considered: maximum observation time and maximum resolution. The penalty function poses multi minima and a genetic algorithm technique is used to solve this problem. In the case that there is no one orbit satisfying the mission requirements, a multi-orbit solution is proposed. In a multi-orbit solution, the set of target sites is split into two groups. Then the developed algorithm is used to search for a natural solution for each group. The satellite has to be maneuvered between the two solution orbits. Genetic algorithms are used to find the optimal orbit transfer between the two orbits using impulsive thrusters. A new formulation for solving the orbit maneuver problem using genetic algorithms is developed. The developed formulation searches for a mini mum fuel consumption maneuver and guarantees that the satellite will be transferred exactly to the final orbit even if the solution is non-optimal. The results obtained demonstrate the feasibility of finding natural solutions for many case studies. The problem of the design of suitable satellite constellation for Earth observing applications is addressed. Two cases are considered. The first is the remote sensing missions for a particular region with high frequency and small swath width. The second is the interferometry radar Earth observation missions. In satellite constellations orbit's design, a new set of compatible orbits, called the "Two-way orbits",whose ground track path is a closed-loop trajectory that intersects itself, in some points, with tangent intersections is introduced. Conditions are derived on the orbital elements such that these Two-way Orbits exist and satellites flying in these orbits pass the tangent intersection points at the same time. Finally, the recently proposed concept of observing a space object from onboard a spacecraft using a star tracker is considered. The measurements of the star tracker provide directions to the target in space and do not provide range measurements. Estimation for the orbit of the target space object using the measurements of the star tracker is developed. An observability analysis is performed to derive conditions on the observability of the system states. The Gaussian Least Squares Differential Correction Technique is implemented. The results obtained demonstrate the feasibility of using the measurements of the star tracker to get a good estimate for the target orbit within a period of measurements ranging from about 20 percent to 50 percent of the orbital period depending on the two orbits.

The Power System Automation Lab at Texas A&M University developed a fault location scheme that can be used for radial distribution systems. When a fault occurs, the scheme executes three stages. In the first stage, all data measurements and system information is gathered and processed into suitable formats. In the second stage, three fault location methods are used to assign possibility values to each line section of a feeder. In the last stage, a fuzzy resolver is used to aggregate the outputs of the three fault location methods and assign a final possibility value to each line section of a feeder. By aggregating the outputs of the three fault location methods, the fuzzy resolver aims to obtain a smaller subset of line sections as potential faulted sections than the individual fault location methods. Fuzzy aggregation operators are used to implement fuzzy resolvers. This dissertation reports on a methodology that was developed utilizing fuzzy aggregation operators in the fuzzy resolver. Three fuzzy aggregation operators, the min, OWA, and uninorm, and two objective functions were used to design the fuzzy resolver. The methodologies to design fuzzy resolvers with respect to a single objective function and with respect to two objective functions were presented. A detailed illustration of the design process was presented. Performance studies of designed fuzzy resolvers were also performed. In order to design and validate the fuzzy resolver methodology, data were needed. Due to the lack of real field data, simulating a distribution feeder was a feasible alternative to generate data. The IEEE 34 node test feeder was modeled. Time current characteristics (TCC) based protective devices were added to this feeder. Faults were simulated on this feeder to generate data. Based on the performance studies of designed fuzzy resolvers, the fuzzy resolver designed using the uninorm operator without weights is the first choice. For this fuzzy resolver, no optimal weights are needed. In addition, fuzzy resolvers using the min operator and OWA operator can be used to design fuzzy resolvers. For these two operators, the methodology for designing fuzzy resolvers with respect to two objective functions was the appropriate choice.