<p>This thesis investigates two significant problems in control and coordination of complex teleoperation systems as they relate to the operation of a mobile robotic manipulator. The first part of the thesis focuses on the design of a control framework to resolve kinematic redundancy in teleoperation of a mobile robotic manipulator. Apart from the redundancy, workspace considerations for the operator and robot and asymmetry of master and slave systems pose significant design challenges in such telerobotic systems . The second part of the thesis considers psychophysical aspects of teleoperation from the operator's perspective. This part presents a method for automatic {\em optimal} positioning of a single camera for a remotely navigated mobile robot in systems with a controllable camera platform. In each part, a constrained optimization problem is formulated and solved in real time. The solution of these optimization problems are integrated seamlessly into the teleoperation control framework in order to assist the operator in accomplishing the main task. The proposed control framework in the first part allows the operator to concentrate on the manipulation task while the mobile base and arm joint configurations are automatically {\em optimized} according to the needs of the task. Autonomous control subtasks are defined to guide the base and the arms towards this optimal configuration while the operator teleoperates the end-effector(s) of the mobile arm(s). The teleoperation and autonomous control tasks have adjustable relative priorities set by the system designer. The work in the second part enables the operator to focus mainly on navigation and manipulation while the camera viewpoint is automatically adjusted. The workspace and motion limits of the camera system and the location of the obstacles are taken into consideration in camera view planning. A head tracking system enables the operator to use his/her head movements as an extra control input to guide the camera placement, if and when necessary. Both proposed controllers have been implemented and evaluated in teleoperation experiments and user studies. The results of these experiments confirm the effectiveness of these controllers and demonstrate significant improvements compared to other existing controllers from the literature included in the studies.</p> / Master of Applied Science (MASc)

<p>In this thesis, a human-in-the-loop control system is presented to assist an operator in teleoperation of a mobile robot. In a conventional teleoperation paradigm, the human operator would directly navigate the robot without any assistance which may result in poor performance in complex and unknown task environments due to inadequacy of visual feedback. The proposed method in this thesis builds on an earlier general control framework that systematically combines teleoperation and autonomous control subtasks. In this approach, the operator controls the mobile robot (slave) using a force-feedback haptic interface (master). Teleoperation control commands coordinate master and slave robots while an autonomous control subtask helps the operator avoid collisions with obstacles in the robot task environment by providing corrective force feedback. The autonomous collision avoidance is based on a Model Predictive Control (MPC) philosophy. The autonomous subtask control commands are generated by formulating and solving a constrained optimization problem over a rolling horizon window of time into the future using system models to predict the operator force and robot motion. The goal of the optimization is to prevent collisions within the prediction horizon by applying corrective force feedback, while minimizing interference with the operator teleoperation actions. It is assumed that the obstacles are stationary and sonar sensors mounted on the mobile robot measure the obstacle distances relative to the robot. Two formulation of MPC-based collision avoidance are proposed. The first formulation directly incorporates raw observation points as constraints in the MPC optimization problem. The second formulation relies on a line segment representation of the task environment. This thesis employs the well-known Hough transform method to effectively transform the raw sensor data into line segments. The extracted line segments constitute a compact model for the environment that is used in the formulation of collision constraints. The effectiveness of the proposed model-predictive control obstacle avoidance schemes is demonstrated in teleoperation experiments where the master robot is a 3DOF haptic interface and the slave is a P3-DX mobile robot equipped with eight (8) sonar sensors at the front.</p> / Master of Applied Science (MASc)

This thesis describes a digital control system used by the Network Analog Group of the Bonneville Power Administration. This system, the Random Sequence Closing Control System, provides automatic control for a special purpose analog computer used in the study of switching surge over voltages on power transmission lines. This system, which uses pseudorandom data, has made it feasible to analyze switching surge phenomena on a statistical basis.

The advancement in solar panel and battery technology makes them useful for energy supply and storage. This thesis involves the modeling and charging control of a lithium ion battery system for solar panels. The proposed model is based on the parameters and characteristics of a realistic battery and solar panel system; and the hybrid control approach combines the advantages of the adaptive incremental conductance method and the perturb and observe method to track the maximum power point of the solar panel for charging the battery unit. Computer simulation results demonstrate that this proposed approach offers a faster convergence rate than the adaptive incremental conductance method, and less steady-state error than the perturb and observe method.

This thesis discusses the modeling of uncertainty of red blood cell (RBC) lifespan distribution in patients suffering from Chronic Kidney Disease(CKD) patients, whose anemia is managed through periodic dosing of erythropoietin (EPO). In healthy individuals, RBCs containing hemoglobin (Hgb) are produced in the bone marrow. When oxygen carried by hemoglobin is transported to human tissues throughout the body, the kidneys sense reduced level of Hgb and secretes EPO that simulates proliferation of red cell precursors and eventually producing red blood cells. However, in CKD patients, their kidneys fail to secrete enough EPO, so that too few of RBCs are produced to maintain a sufficient Hgb level. As a result, artificial EPO dosing is required when the kidney loses this function to avoid anemia. To develop effective artificial EPO dosing schemes, it is important to have models of how EPO does dynamically affect hemoglobin levels. Since there is significant uncertainty in this process, it is equally valuable to have mathematical models of such uncertainties, and in this thesis we focus on uncertainty in the lifespan of red blood cells. In this thesis, we consider two different types of models for RBC lifespan uncertainty: the time-invariant and time-varying cases. In the former, we treat the probabilistic distribution of cell lifespans as fixed for a given patient, but variable (uncertain) over the population. In the latter case, the cell lifespan distribution can change from moment to moment for a given patient. Amongst several possible choices of RBC lifespan distributions, this thesis will focus on the gamma distribution. For the time-invariant model, a first-order gamma distribution is selected as the nominal distribution, and a multiplicative error model is proposed to analyze the impact of lifespan uncertainty on anemia management. In the time-varying case, the lifespan distribution is not fixed in time, but allowed to switch over a finite collection of gamma distributions. In other words, each newly-born RBC has a lifespan coming from a distribution chosen from a collection. Both of these models are analyzed so as to evaluate the impact of lifespan uncertainty on the performance of anemia management schemes; including stability and response time.

Traffic signal control is an effective way to improve the efficiency of traffic networks and reduce users’ delays. Ant Colony Optimization (ACO) is a metaheuristic based on the behavior of ant colonies searching for food. ACO has successfully been used to solve many NP-hard combinatorial optimization problems and its stochastic and decentralized nature fits well with traffic flow networks. This thesis investigates the application of ACO to minimize user delay at traffic intersections. Computer simulation results show that this new approach outperforms conventional fully actuated control under the condition of high traffic demand.

In this thesis, the viability of decentralized, noncooperative multi-robot path planning algorithms is tested. Three algorithms based on the Batch Informed Trees (BIT*) algorithm are presented. The first of these algorithms combines Optimal Reciprocal Collision Avoidance (ORCA) with BIT*. The second of these algorithms uses BIT* to create a path which the robots then follow using an artificial potential field (APF) method. The final algorithm is a version of BIT* that supports replanning. While none of these algorithms take advantage of sharing information between the robots, the algorithms are able to guide the robots to their desired goals, with the algorithm that combines ORCA and BIT* having the robots successfully navigate to their goals over 93% for multiple environments with teams of two to eight robots.

Industrial programs written on Programmable Logic Controllers (PLCs) have become an essential component of many modern industries, including automotive, aerospace, manufacturing, infrastructure, and even amusement parks. As these safety-critical systems become larger and more complex, ensuring their continuous error-free operation has become a significant and important challenge. Formal methods are a potential solution to this issue but have traditionally required substantial time and expertise to deploy. This usability issue is compounded by the fact that PLCs are highly proprietary and have substantial licensing costs, making it difficult to learn about or deploy formal methods on them. This thesis presents the OPPP (Open-source Proving of PLC Programs) system as a solution to this usability issue. The OPPP system allows the end-to-end creation and verification of PLC programs from within the development environment. The system is created with an emphasis on being easy to use, with formal constraints presented in English phrases that require no special knowledge to understand. The system uses entirely open-source components, including modified versions of both the OpenPLC development environment and the PLCverif verification platform. The OPPP system is then demonstrated to formalize the requirements of two college-level introductory PLC programming problems. It is further demonstrated to correctly find errors in and verify the correctness of a known good and known bad solution to each problem.

<p>Hydraulic systems are commonly used for actuation and manipulation of heavy loads. They are found in a variety of different industries, such as in automotive, manufacturing, robotics, construction, and aerospace. Conventional hydraulic systems use a centralized constant pressure supply system. Pressurized fluid is then channeled to actuators using servo-valves. The advantages of these systems are their high torque to mass ratio, and the ability to control speed and direction with relative precision. However, there are also disadvantages such as the requirement of a bulky centralized supply, leakage, noise, and reduced energy efficiency due to orifice flow and the requirement for maintaining a constant supply pressure.</p> <p>Electro-Hydrostatic Actuation systems (EHA) alleviate many of the above mentioned shortcomings of servo-valve controlled hydraulic systems. In the EHA position control is achieved by regulating the pumping action. Here, a fixed or a variable displacement pump can be used to move oil from one chamber of the actuator to the other. In these actuators, the presence of nonlinearities associated with pump/motor static friction and backlash, pressure drop in the piping system, and nonlinear friction at the load have a significant effect on the performance and positional precision of the system.</p> <p>This research will focus on developing a multiple inner-loop control strategy by implementing multiple inner-loops that utilize the differential pump/load position and velocity. The main goal will be to decrease the effect of the pump backlash as well as the nonlinear friction at the load; both of which negatively impact positional precision. Therefore, the main benefit of this method is an improvement in trajectory tracking precision, which is particularly important for high precision hydrostatic systems. Furthermore, a sliding mode control strategy will be incorporated into the design to suppress load oscillations reported in precision trajectory tracking applications. The research hypothesis states that sliding mode control in conjunction with multiple inner-loops, will improve the trajectory tracking performance of a hydrostatic actuation system by partially compensating the effects of static friction at the load. Theoretical analysis, simulation supported by experimental results are presented to demonstrate the effectiveness of the newly developed methods in suppressing the effects of nonlinearities on the EHA performance, with the downside of an increased complexity due to the increased number of controller parameters.</p> / Doctor of Philosophy (PhD)

<p>Sampled-data supervisory control deals with timed discrete event systems (TDES) where the supervisors are to be implemented as sampled-data controllers. A sampled-data controller views the system as a series of inputs and outputs and is controlled by a periodic clock. It samples its inputs, changes state, and updates its outputs on each clock edge (the tick event). The sampled-data supervisory control framework provides a set of conditions that the TDES system must satisfy to ensure its correct behaviour in order to be implemented as sampled data controllers. A serious limitation for automatic verification of systems is the size of the system's synchronous product. To overcome this limitation, we propose the use of a compositional approach to the verification of sampled-data supervisory control. In this approach, first we recast the required conditions for sampled-data supervisory control in terms of other properties such as language inclusion, nonblocking or controllability, which already have existing compositional methods and algorithms. This makes the sampled-data properties suitable for compositional verification, considerably increasing the size of systems that can be handled using sampled-data supervisory control. We also develop and implement a set of algorithms for the compositional verification of these sampled-data properties. We provide an example of the SD Controlled Flexible Manufacturing System to test our algorithms.</p> / Master of Science (MSc)