Automatic control

In this paper, the possibility of using a Small Water-plane Area Twin Hull (SWATH) as an
unmanned Arctic scientific research vessel is analyzed. Before carrying out the stability
analysis of the SWATH ship, this paper briefly outlines the importance of the Arctic survey,
which guides the importance of the new research ship for Arctic scientific exploration. In
addition to being used as a long-tern monitoring and data collection platform, it is also used
as a recovery mothership for autonomous equipment such as an AUV.
After briefly introducing the basic background of a SWATH, it’s advantages and
disadvantages are enumerated and analyzed, and a combination of theoretical and practical
tests are used to conduct a brief analysis and summary of the reasons for the appearance of
trim by head arising from SWATH navigation. Trim by head occurs when a vessel incline such that its plane of flotation is not coincident with its mean waterline plane. In terms of
theory, hydrodynamic equations are used to theoretically deduce the SWATH state of
navigation and get the corresponding characteristic equation. Finally, a new type USV be
designed conceptionally and be created as a model by Solid-work software. Conceptual
design combines the advantages of SWATH and remedy deficiency of its longitudinal
stability. The theoretical calculation and analysis of the struts of the conceptual model
proves that the oblique struts structure can effectively improves the transverse stability of
the model, and with the help of the special slender ellipse structure which is installed on
the model’s struts, the righting moment of the model is increased when it’s heeling during
a large angle. The hydrodynamic analysis of the conceptual model is carried out by Star-
CCM software. The simulation results also prove the effectiveness of stabilizer fins to the
longitudinal stability of the conceptual design and reflects the data information of the
model in terms of resistance and motion state. At last, we have a general understanding of
the performance characteristics of the conceptual model by analysis the feedback data,
which provides reliable support for future improvement and optimization.

With the strikingly fast development of industrial applications and research projects, control systems have become more and more complex than ever. Intelligent control techniques, featuring their being more robust and their availability when system mathematical models are unknown, have proven to be one of the most attractive and highlighted areas in the automatic control arena. This thesis concentrates first on the design of a laser tracking system. A standard design procedure of Fuzzy Logic Controllers (FLCs) is followed, which is then realized in a PC-based environment in the design. An essential issue in this thesis study is the auto tuning of the Fuzzy Logic Controller. An efficient tuning method, mu-law functions, which can adjust both the shape and scaling gain of fuzzy controller's decision table is adopted. Also a search process called Downhill Simplex Search is chosen. Combining these two methods, a Simplex-mu-law auto-tuning algorithm that fits our application is applied to tune the FLC for the laser tracking system. Another issue covered in this research is to modify the Fuzzy Logic Controller structure by changing the distribution of the membership functions. Based on the analysis of the real time error histogram of the system, a novel method is proposed in the thesis for the modification of the membership functions To assess the effectiveness of the methods proposed in this thesis, a prototype laser tracking system is constructed at the FAU Robotics Center. The control strategy proposed in this thesis is tested extensively by simulations and experimentations on the prototype system.

Recent advances in computer engineering make the computational approaches to controller design for high order systems practical. In this dissertation, a series of computational methods based on cell state space for the design and optimization of Takagi-Sugeno (TS) type Fuzzy Logic Controllers (FLCs) are presented. The approaches proposed in this research can be classified into two categories: feed forward design and feedback design. An Optimal Control Table (OCT) based on cell state space is used in all the feed forward design approaches. An FLC can be trained by Least Mean Square (LMS) algorithm with an OCT serving as the training set. For high order systems, due to physical memory limit, the cell resolution is generally low. A specially modified k-d tree representation of cell space is proposed to save the memory while keeping the cell resolution as high as possible. The control command for a point that is not a cell center is approximated by interpolating an OCT. All these commands can be used as training data to train an FLC. An iterative feedback design approach named Incremental Best Estimate Directed Search (IBEDS) is proposed to further optimize a training set. It is a kind of globally directed random search method. The general philosophy is that since the best possible performance of an FLC largely depends on the quality of the training set, if the training set is optimized, an FLC trained by the set would also be optimized. Based on IBEDS, two other feedback FLC design algorithms are also proposed. In one algorithm, subtractive clustering method is used to extract the structure of an FLC from an OCT. The coefficients of the FLC obtained are then optimized with IBEDS. The other algorithm applies IBEDS to three system models and finds the training set that has the worst performance for all the models. This training set is further optimized to improve robustness of a trained FLC.

It is desirable to have robust high performance nonlinear control with a model-free design approach for the real time automatic control of practical industrial processes. The field has seen the application of Sliding Mode Controllers (SMCs). SMCs are nonlinear robust controllers, however most design approaches related to SMCs are model-based approaches. PID controllers and some Fuzzy Logic Controllers (FLCs) are model-free controllers, however their robustness is not integrated into their design parameters directly. This dissertation presents two new types of robust high performance nonlinear controllers with model-free design approaches. One introduces fuzzy logic to a model-free SMC which is a simple saturation function incorporating three design parameters. Due to the interpolative nature of fuzzy control, a TSK type FLC with the model-free SMCs as its rule's consequents will produce a controller with a nonlinear sliding curve and a nonlinear boundary layer. We call this controller a Fuzzy Sliding Controller (FSC). The other uses a new type of Variable Structure Controller (VSC), which intentionally switches from one controller to another controller during a step response. In conventional approaches to VSC, the control surface does not change its shape during a step response. The new type of VSC intentionally changes the shape of the control surface during the step response. This technique is analogous to that technique employed in image processing called "morphing" where a given image gradually changes over time to the image of a different entity. In order to avoid confusion with the conventional approach to a VSC, we use the term "Morphological" Controller (MC) for the VSC of the new type. The performance and robustness with respect to parameter variations, disturbances and slow sample rates of the proposed controllers are studied in detail with a DC motor and an Inverted Pendulum System. As a means to verify the proposed controllers in practical cases, we design the model-free SMC, the FSC and the MC for the highly nonlinear and uncertain dynamics of an Autonomous Underwater Vehicle, Ocean Voyager II. It is shown that the proposed controllers are high performance and high robustness controllers.

As part of a project to study internal waves, FAU plans to utilize an AUV to tow a magnetometer to study electromagnetic signatures from internal waves. This research is focused on the electromagnetic noise issues related to using an AUV to tow the magnetic sensor package. There are active sources of electromagnetic noise caused by an AUV that are present in addition to those induced by the Earth's magnetic field and permanent magnets. To characterize the magnetic noise associated with the AUV magnetometer tow system, the various active source elements were identified, the orientation sensitivity of the sensors being used was determined, and the magnetic anomaly of a similar AUV which may be eventually be used in a magnetic sensing arrangement was measured. The results are used to show the proposed sensing arrangement will likely not achieve the necessary sensitivity to measure subtle internal wave signals.

A magnetometer with a sensitivity of 0.01nT will be towed through the thermocline by a 2.87 meter long, 0.533 meter diameter autonomous underwater vehicle (AUV) to measure the magnetic fluctuations generated by oceanic internal waves. At this point, no research has been found that suggests towed magnetometer measurements have been done using an AUV. Simulations of the AUV, tow cable, and towfish are performed to provide an understanding of the effects of changing different input parameters, such as towing speed (0.5-2m/s), cable length (5-15m), vehicle trajectory (circle and vertical zig zag maneuvers), and current (0.25-1.25m/s). The AUV-cabletowfish system and equations of motion needed for the simulations are described herein. Results show that a 5m tow cable provides better towfish maneuvering than the longer cable lengths. High towfish pitch angle is decreased by decreasing the distance between CG and CB. Surface currents speed of 0.25m/s change the AUV and towfish circle maneuver to a spiral trajectory, while 1.25m/s current speed cause a zig zag trajectory.

The main contribution in this thesis is the design of a robust AUV docking guidance and navigation approach that can guide and home an AUV towards an acoustic source located on an oriented bottom-mounted underwater docking station, under presence of unknown current disturbances and in the absence of any form of onboard velocity sensor. A Complementary Filter and various forms of Kalman Filters were separately formulated to estimate the current and vehicle positions with strategic vehicle manoeuvres. A current compensator uses the estimated current to maintain the desired vehicle course while under current disturbance. Tagaki-Sugeno-Kang Fuzzy Inference System was designed to realize fuzzy docking guidance manoeuvres. Finally, Monte Carlo runs were performed on a designed AUV docking simulator to evaluate the docking robustness against various docking conditions. Simulation results demonstrated robustness in the designed docking guidance and navigation approach.