Call number: LD2668 .T4 1985 M44 / Master of Science

In nature, through millions of years of evolution, fish and cetaceans have developed fast efficient and highly manoeuvrable methods of marine propulsion. A recent explosion in demand for sub sea robotics, for conducting tasks such as sub sea exploration and survey has left developers desiring to capture some of the novel mechanisms evolved by fish and cetaceans to increase the efficiency of speed and manoeuvrability of sub sea robots. Research has revealed that interactions with vortices and other unsteady fluid effects play a significant role in the efficiency of fish and cetaceans. However attempts to duplicate this with robotic fish have been limited by the difficulty of predicting or sensing such uncertain fluid effects. This study aims to develop a gait generation method for a robotic fish with a degree of passivity which could allow the body to dynamically interact with and potentially synchronise with vortices within the flow without the need to actually sense them. In this study this is achieved through the development of a novel energy based gait generation tactic, where the gait of the robotic fish is determined through regulation of the state energy rather than absolute state position. Rather than treating fluid interactions as undesirable disturbances and `fighting' them to maintain a rigid geometric defined gait, energy based control allows the disturbances to the system generated by vortices in the surrounding flow to contribute to the energy of the system and hence the dynamic motion. Three different energy controllers are presented within this thesis, a deadbeat energy controller equivalent to an analytically optimised model predictive controller, a $H_\infty$ disturbance rejecting controller with a novel gradient decent optimisation and finally a error feedback controller with a novel alternative error metric. The controllers were tested on a robotic fish simulation platform developed within this project. The simulation platform consisted of the solution of a series of ordinary differential equations for solid body dynamics coupled with a finite element incompressible fluid dynamic simulation of the surrounding flow. results demonstrated the effectiveness of the energy based control approach and illustrate the importance of choice of controller in performance.

Recent advances in wireless communication and micro-electro-mechanical systems (MEMS) have led to the development of implementation of low-cost, low power, multifunctional sensor nodes. These sensor node are small in size and communicate untethered in short distances. The nodes in sensor networks have limited battery power and it is not feasible or possible to recharge or replace the batteries, therefore power consumption should be minimized so that overall network lifetime will be increased. In order to minimize power consumed during idle listening, some nodes, which can be considered redundant, can be put to sleep. In this thesis study, basic routing algorithms and duty cycle control algorithms for WSNs in the literature are studied. One of the duty cycle control algorithms, Role Alternating, Coverage Preserving, and Coordinated Sleep algorithm (RACP) is examined and simulated using the ns2 simulation environment. A novel duty cycle control algorithm, Sink Initiated Path Formation (SIPF) is proposed and compared to RACP in terms of sleep sensor ratio and time averaged coverage.

The increasing use of electrical technologies within on-board (aircraft, road vehicle, train and ship) power systems is resulting in complex and highly dynamic networks in which energy storage devices have an important role to play, for example to resolve the instantaneous mismatch between load demand and power availability or to provide the flexibility to optimise overall performance. In this thesis, a multi-level controller for a super-capacitor based energy storage system (ESS) is designed, simulated, emulated and validated experimentally to show its effectiveness in smoothing load and managing state-of-charge of the energy storage system. This thesis first investigates the low level control of the dual-interleaved converter, particularly at light load where seven discontinuous conduction modes (DCMs) appear. A thorough analysis of these operating modes is given and validated by simulations and experiments. Based on the analysis, an inverse-model-based feed-forward current controller is implemented, offering a low level converter control interface which serves the high level supervisory controller within the energy storage system. Two supervisory control methods have been proposed in this thesis, both producing a super-capacitor current reference for the low level controller. The first supervisory control not only manages the energy within the ESS but also shields the primary power source from rapid load transients , which has been examined through an emulated ESS in the Intelligent Electrical Power Network Evaluation Facility (IEPNEF). A more advanced supervisory controller is then proposed which in addition to the benefits of the first control, regulates the rate-of-change in power that is drawn from the primary power source in the system. The proposed second control method is implemented within a real super-capacitor energy storage system in IEPNEF, with both simulation and experimental results successfully demonstrating and validating its operation.

Vibration-based energy harvesting using piezoelectric materials have been investigated by several research groups with the aim of harvesting maximum energy and providing power to low-powered wireless electronic systems for their entire operational life. The electromechanical coupling effect introduced by the piezoelectric vibration energy harvesting (PVEH) mechanism presents modelling challenges. For this reason, there has been a continuous effort to develop different modelling techniques to describe the PVEH mechanism and its effects on the dynamics of the system. The overall aims of this thesis are twofold: (1) a thorough theoretical and experimental analysis of a PVEH beam or assembly of beams; (2) an in-depth analytical and experimental investigation of the novel concept of a dual function piezoelectric vibration energy harvester beam/tuned vibration absorber (PVEH/TVA) or 'electromechanical TVA' and its potential application to vibration control. The salient novel contributions of this thesis can be summarised as follows: (i) An in-depth experimental validation of a PVEH beam model based on the analytical modal analysis method (AMAM), with the investigations conducted over a wider frequency range than previously tested. (ii) The precise identification of the electrical loads that harvest maximum power and that induce maximum electrical damping. (iii) A thorough investigation of the influence of mechanical damping on PVEH beams. (iv) A procedure for the exact modelling of PVEH beams, and assemblies of such beams, using the dynamic stiffness matrix (DSM) method. (v) A procedure to enhance the power output from a PVEH beam through the application of a tip rotational restraint and the use of segmented electrodes. (vi) The theoretical basis for the novel concept of a dual function PVEH beam/TVA, and its realisation and experimental validation for a prototype device. A thorough experimental validation of a cantilever piezoelectric bimorph energy harvester without a tip mass is presented under random excitation. The study provided a deep insight into the effect of PVEH on the dynamics of the system for variations in electrical load. An alternative modelling technique to AMAM, based on the DSM, is introduced for PVEH beams. Unlike AMAM, the DSM is exact, since it is based on the exact solution to the bending wave equation. It also readily lends itself to the modelling of beams with different boundary conditions or assemblies of beams of different crosssections. AMAM is shown to converge to DSM if a sufficiency of modes is used. Finally, an in-depth theoretical and experimental investigation of a prototype PVEHbeam/TVA device is presented. This device comprises a pair of bimorphs shunted by R-L-C circuitry and can be used as a tuned mass damper (TMD) to attenuate a vibration mode of a generic structure. The optimal damping required by this TMD is generated by the PVEH effect of the bimorphs. Such a device combines the advantages of conventional mechanical and electrical TVAs, overcoming their relative disadvantages. The results demonstrate that the ideal degree of attenuation can be achieved by the proposed device through appropriate tuning of the circuitry, thereby presenting the prospect of a novel class of 'electromechanical' tuned vibration absorbers.

This thesis considers the problem of implementation of Model Predictive Control (MPC) strategies in the general area of Heating, Ventilation, Air Conditioning (HVAC). Specifically, the contributions utilize the constraint handling and optimality properties of MPC to achieve energy efficient control of many different HVAC systems. First, the thesis focuses on a linear offset-free MPC design for a vapor compression cycle. The key contributions include a a sequential tuning method and application to a detailed simulation test-bed, demonstrating superior closed-loop results to that of traditional control strategies in the presence of both disturbances and measurement noise. Next, a modified linear offset-free MPC formulation is implemented on a heat pump. The key contribution is the formulation of an optimization problem that recognizes the tradeoff between energy conservation and tracking performance. Simulation results illustrate superior performances as measured through three separate metrics: safety, energy efficiency and tracking. The implementation of MPC formulations to these realistic problems also pointed to a lack of MPC formulations with explicit performance considerations in the control design. Thus, in the final part of the thesis, these observed shortcomings in the standard offset-free linear MPC design are addressed via a new performance specification-based MPC. Desired closed-loop output response is specified and achieved through a tiered optimization formulation that can handle plant model mismatch. Superior closed-loop response, in terms of desired transient behavior and disturbance rejection, relative to standard linear-based and offset-free MPC designs is achieved. Finally, directions for future work are discussed. / Thesis / Doctor of Philosophy (PhD)

This thesis presents the design, modeling, and control of a fully-actuated multi-rotor unmanned aerial vehicle (UAV). Unlike conventional multi-rotors, which suffer from two degrees of underactuation in their propeller plane, the choice of an unconventional propeller configuration in the new drone leads to an even distribution of actuation across the entire force-torque space. This allows the vehicle to produce any arbitrary combination of forces and torques within a bounded magnitude and hence execute motion trajectories unattainable with conventional multi-rotor designs. This system, referred to as the \omninospace, decouples the position and attitude controllers, simplifying the motion control problem. Position control is achieved using a PID feedback loop with gravity compensation, while attitude control uses a cascade architecture where the inner loop follows an angular rate command set by the outer attitude control loop. A novel model is developed to capture the disturbance effects among interacting actuator airflows of the \omninospace. Given a desired actuator thrust, the model computes the required motor command using the current battery voltage and thrusts of disturbing actuators. A system identification is performed to justify the use of a linear approximation for parameters in the model to reduce its computational footprint in real-time implementation. The \omni benefits from two degrees of actuation redundancy resulting in a control allocation problem where feasible force-torques may be produced through an infinite number of actuator thrust combinations. A novel control allocation approach is formulated as a convex optimization to minimize the \omnis energy consumption subject to the propeller thrust limits. In addition to energy savings, this optimization provides fault tolerance in the scenario of a failed actuator. A functioning prototype of the \omni is built and instrumented. Experiments carried out with this prototype demonstrate the capabilities of the new drone and its control system in following various translational and rotational trajectories, some of which would not be possible with conventional multi-rotors. The proposed optimization-based control allocation helps reduce power consumption by as much as 6\%, while being able to operate the drone in the event of a propeller failure. / Thesis / Master of Applied Science (MASc)

<p>Dat je pregled mogućnosti za povišenje energetske efikasnosti<br />pneumatskog programabilnog manipulatora primenjenog u kontaktnim<br />zadacima. Projektovano je i realizovano ispitno postrojenje. Posebno<br />je ukazano na mogućnosti projektovanja različitih upravljačkih<br />sistema. Razvijeni su primeri PWM i proporcionalnog upravljanja.<br />Ispitana su predložena rešenja iz različitih aspekata energetske<br />efikasnosti i kvaliteta praćenja trajektorije pri korišćenju<br />različitih vrsta materijala i alata. Izvučeni su potrebni zaključci.</p> / <p>This paper contains an overview of possibilities for increasing the energy<br />efficiency of programmable pneumatic manipulator in contact tasks.<br />Experimental station is designed and realized as a testbed. Especially, point<br />is on possibilities of designing of new control systems. Examples of PWM<br />and proportional control are developed. Proposed solutions are examined<br />from aspects of energy efficiency and quality of trajectory tracking, by using<br />various types of materials and tools. Necessary conclusions are drawn.</p>

Magnetic shape memory alloys are active materials which deform under the application of a magnetic field or an external stress. Due to their internal friction, recognizable from the strain-stress hysteresis, this new material technology allows the design of multistable actuators. This paper describes and characterizes an innovative airflow control valve whose aperture is proportional to the deformation of the active material and thus controllable by the input voltage. The multistability of the material is partially exploited within an airflow control loop to reduce the energy losses of the valve when a specific airflow value must be hold.

Electric vehicles, which have both energy storage capability and mobility capability, can provide a new solution for electricity sharing between different building communities (i.e., a group of buildings connected with a microgrid). This comes to the community-to-community (C2C) energy sharing network. The C2C energy sharing networks have the potential to not only minimize the effects of electric vehicle integration into the energy grid, but also improve the electricity grid efficiency as a whole. In this thesis, a coordinated smart charging method of electric vehicles (EVs) is proposed for the C2C model. The proposed method considers the power regulation needs in both the present parking community and the next destination community. Then, based on the needs of both communities, the control method will decide the optimal amount of electricity that can be delivered by EV, so that the energy performances in both communities can be the best. The developed coordinated control has been compared with a base case (without any smart charging) and an uncoordinated control case under two control strategies: minimizing the peak energy exchanges with the grid and maximizing the renewable self-utilization. The genetic algorithm tools in MATLAB software are used for the optimization of the model. Meanwhile, to test the robustness of this C2C model, different combinations of building communities have been studied, namely residential-workplace, residential-university, and residential-workshop communities. The case study reveals that the C2C model is effective in improving energy performance under both control strategies. Peak reduction control strategies work most effectively for smaller systems with lower electricity demand and production. With C2C energy sharing, the annual mean peak reduction ranged from 39 % at the smallest community and 20 % at the largest community. Self-consumption maximization strategies work best for systems with a larger surplus of electricity production. With C2C energy sharing, the annual self-consumption increase ranged from 50 % at the community with the largest production surplus, to 7 % at the community with the smallest production surplus. The residential-workshop community studied in this thesis benefited the most from C2C charging control due to its production surplus and the relatively low electricity demands of the communities.