This thesis tries to research the term “robust controllers”. Its aim is to compare the robustness of discrete PID controllers (Discrete Equivalent Continuous Controller, Discrete Impulse Area Invariant, Takahashi, Feed-Forward), adaptive discrete PID controllers (Discrete Impulse Area Invariant, Takahashi, Feed-Forward), optimal controllers (quadratic optimal), and adaptive optimal controllers (quadratic optimal) on chosen transfer functions. Its aim is also to check the influence of A/D and D/A converters. The aims to obtain are demarked at the beginning of the text and also there is an explanation of the term “robustness.” Later on there is a description and an approximation to each of the chosen kinds of controllers and the identification methods used in the thesis (for adaptive controllers the method of recursive least-squares was used). The Kharitonov's Theorem are made on the chosen transfer function. Next there is a description of the methods with which the robustness of the controllers will be tested. The first method is the integral criteria, particular ITAE criterion and quadratic criterion. The second one is the analysis of the generalised circle criterion. Furthermore there are various displays of the results obtained and their corresponding comments. The results obtained are graphically displayed and by means of these schemes the particular types of controllers are compared. All of the simulations and results obtained were acquired through the use of the program MATLAB- Simulink. In the end of the thesis there is an overall evaluation.

published_or_final_version / Mechanical Engineering / Doctoral / Doctor of Philosophy

Semi-active suspension systems promise to significantly reduce the necessary trade-off be-tween handling and passenger comfort present in conventional suspension systems by enabling active chassis and wheel control. Öhlins Racing AB have developed a semi-active suspension technology known as CES, Continuously controlled Electronic Suspension, based on solenoid control valves which are integrated into specially designed hydraulic dampers, and are currently developing control and estimation systems which will enable their application in advanced motorcycle suspensions. In these systems an important aspect is being able to accurately control the forces produced. Öhlins’ current system uses an open loop control strategy in which currents sent through the solenoid valves, to achieve the requested damping force under the prevailing circumstances, is calculated using experimentally derived static lookup tables. In this thesis a new closed loop control system, based on the direct measurement of the damper force, is developed and its performance is evaluated in comparison to the old one’s. Sufficient understanding of the system requires extensive modeling and therefore two different models have been developed; a simpler one used for model based control design and a more extensive, high fidelity model used for high accuracy simulations. The developed simulation model is the first of its kind that is able to capture the studied systems behavior with satisfactory accuracy, as demonstrated against real dynamometer measurements. The valves and damper behave in a highly non linear manner and the final controller design uses a combination of exact linearization, non linear state estimation, dynamical inversion and classical control theory. Simulation results indicate that the new controller reduces the root mean square force tracking error to about 63% of that of the existing controller in the evaluation scenarios used. Cascaded within the system is also closed loop current controllers. A developed model based controller is shown to reduce the rise time to less than 30% of that of the existing PID-controllers, reduce the overshoot and provide online estimates of the winding series resistance, providing the basis for future solenoid diagnosis and temperature tracking systems.

Background: Treadmill walking should closely simulate overground walking for research validation and optimal skill transfer. Traditional fixed-speed treadmill (FS) walking may not simulate natural walking because of the fixed belt speed and lack of visual cues. Self-paced (SP) treadmill walking, especially feedback controlled SP treadmill walking, enables close-to-real-time belt speed changes with users' speed changes. Different sensitivity levels of SP treadmill feedback determine how fast the treadmill respond to user's speed change. Few studies have examined the differences between FS and SP treadmill walking, or the difference between sensitivity levels of SP treadmills, and their methods were questionable because of averaging kinematics and kinetics parameters, and failing to examine directly treadmill and subjects' speed data. This study compared FS with two SP modes with variation of treadmill speed and user's speed as dependent variables. Method: Thirteen young healthy subjects participated. Subjects walked on a motorized split-belt treadmill under FS, high sensitivity SP (SP-H) and low sensitivity SP (SP-L) conditions at normal walking speed. Root mean square error (RMSE) for subject's pelvis global speed (Vpg), pelvis speed with respect to treadmill speed (Vpt), and treadmill speed (Vtg) data were collected for all trials. Results: Significant condition effects were found between FS and the two SP modes in all RMSE values (p < 0.001). The two sensitivity levels of SP had similar speed patterns. Large subject × condition interaction effects were found for all variables (p < 0.001). Only small subject effects were found. Conclusions: The results of the study reveal different walking patterns between FS and SP. However, the two sensitivity levels failed to differ much. More habituation time may be needed for subjects to learn to optimally respond to the SP algorithm. Future work should include training subjects for more natural responses, applying a feed-forward algorithm, and testing the effect of optic flow on FS and SP speed variation. / text

Approved for public release; distribution in unlimited. / This thesis considers the problem of time-optimal spacecraft slew maneuvers. Since the work of Bilimoria and Wie it has been known that the time-optimal reorientation of a symmetric rigid body was not the eigenaxis maneuver once thought to be correct. Here, this concept is extended to axisymmetric and asymmetric rigid body reorientations with idealized independent torque generating devices. The premise that the time-optimal maneuver is not, in general, an eigenaxis maneuver, is shown to hold for all spacecraft configurations. The methodology is then extended to include spacecraft control systems employing magnetic torque rods, a combination of pitch bias wheel with magnetic torque rods, and finally to control systems employing single gimbal control moment gyros. The resulting control solutions, designed within the limitations of the actuators, eliminate the requirement to avoid actuator singularities. Finally, by employing sampled-state feedback the viability of real-time optimal closed loop control is demonstrated.

The performance of a quadrotor can be significantly disturbed in presence of wind. In this paper, a simple-to-implement attitude controller is proposed to render a robust and accurate trajectory tracking in presence of disturbance and model uncertainties. The attitude controller design is based on Quantitative Feedback Theory (QFT). A fuzzy logic controller is further employed to provide satisfactory position trajectory tracking for the quadrotor. The performances of the controllers, in terms of disturbance rejection and trajectory tracking are experimentally studied. Finally, a flight scenario is performed to compare the performances of the designed QFT-Fuzzy control scheme with the ArduCopter controller. / May 2016

Thesis. 1976. M.S.--Massachusetts Institute of Technology. Dept. of Electrical Engineering and Computer Science. / Microfiche copy available in Archives and Engineering. / Includes bibliographical references. / by Jorge F. Baca. / M.S.

Repetitive Control (RC) seeks to converge to zero tracking error of a feedback control system performing periodic command as time progresses, or to cancel the influence of a periodic disturbance as time progresses, by observing the error in the previous period. Iterative Learning Control (ILC) is similar, it aims to converge to zero tracking error of system repeatedly performing the same task, and also adjusting the command to the feedback controller each repetition based on the error in the previous repetition. Compared to the conventional feedback control design methods, RC and ILC improve the performance over repetitions, and both aiming at zero tracking error in the real world instead of in a mathematical model. Linear Model Predictive Control (LMPC) normally does not aim for zero tracking error following a desired trajectory, but aims to minimize a quadratic cost function to the prediction horizon, and then apply the first control action. Then repeat the process each time step. The usual quadratic cost is a trade-off function between tracking accuracy and control effort and hence is not asking for zero error. It is also not specialized to periodic command or periodic disturbance as RC is, but does require that one knows the future desired command up to the prediction horizon. The objective of this dissertation is to present various design schemes of improving the tracking performance in a control system based on ILC, RC and LMPC. The dissertation contains four major chapters. The first chapter studies the optimization of the design parameters, in particular as related to measurement noise, and the need of a cutoff filter when dealing with actuator limitations, robustness to model error. The results aim to guide the user in tuning the design parameters available when creating a repetitive control system. In the second chapter, we investigate how ILC laws can be converted for use in RC to improve performance. And robustification by adding control penalty in cost function is compared to use a frequency cutoff filter. The third chapter develops a method to create desired trajectories with a zero tracking interval without involving an unstable inverse solution. An easily implementable feedback version is created to optimize the same cost every time step from the current measured position. An ILC algorithm is also created to iteratively learn to give local zero error in the real world while using an imperfect model. This approach also gives a method to apply ILC to endpoint problem without specifying an arbitrary trajectory to follow to reach the endpoint. This creates a method for ILC to apply to such problems without asking for accurate tracking of a somewhat arbitrary trajectory to accomplish learning to reach the desired endpoint. The last chapter outlines a set of uses for a stable inverse in control applications, including Linear Model Predictive Control (LMPC), and LMPC applied to Repetitive Control (RC-LMPC), and a generalized form of a one-step ahead control. An important characteristic is that this approach has the property of converging to zero tracking error in a small number of time steps, which is finite time convergence instead of asymptotic convergence as time tends to infinity.

Liu Lu. / Thesis (M.Phil.)--Chinese University of Hong Kong, 2005. / Includes bibliographical references (leaves 65-70). / Abstracts in English and Chinese. / Abstract --- p.i / Acknowledgement --- p.ii / Chapter 1 --- Introduction --- p.1 / Chapter 1.1 --- The Output Regulation Problem --- p.1 / Chapter 1.2 --- Control Design with Unknown High-frequency Gain Sign --- p.3 / Chapter 1.3 --- Contribution of the Thesis --- p.4 / Chapter 1.4 --- Thesis Outline --- p.5 / Chapter 2 --- Global Robust Stabilization of a Class of Nonlinear Systems --- p.6 / Chapter 2.1 --- Introduction --- p.7 / Chapter 2.2 --- Problem Formulation and Preliminaries --- p.8 / Chapter 2.3 --- Main Result --- p.11 / Chapter 2.4 --- An Example --- p.20 / Chapter 2.5 --- Application of Theorem 2.1 --- p.26 / Chapter 2.5.1 --- Chua's Circuit and Control Problem --- p.26 / Chapter 2.5.2 --- Solvability of the Control Problem --- p.28 / Chapter 2.5.3 --- Simulation Results --- p.32 / Chapter 2.5.4 --- Conclusion --- p.33 / Chapter 2.6 --- Conclusion --- p.36 / Chapter 3 --- Global Robust Output Regulation of Nonlinear Systems in Output Feedback Form --- p.39 / Chapter 3.1 --- Introduction --- p.40 / Chapter 3.2 --- Output Regulation Converted to Stabilization --- p.42 / Chapter 3.3 --- Main Result --- p.49 / Chapter 3.4 --- An Example --- p.55 / Chapter 3.5 --- Conclusion --- p.58 / Chapter 4 --- Conclusions --- p.62 / List of Figures --- p.64 / Bibliography --- p.65 / Biography

Chen Zhiyong. / "April 2005." / Thesis (Ph.D.)--Chinese University of Hong Kong, 2005. / Includes bibliographical references (p. 205-215) / Electronic reproduction. Hong Kong : Chinese University of Hong Kong, [2012] System requirements: Adobe Acrobat Reader. Available via World Wide Web. / Mode of access: World Wide Web. / Abstracts in English and Chinese.