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Alternative oxidants and processing procedures for pyrotechnic time delaysMoreira Ricco, Isabel Maria. January 2004 (has links)
Thesis (M.Eng.)(Chemical)--University of Pretoria, 2004. / Includes summary. Includes bibliographical references.
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Control of Surgical Robots with Time Delay using Model Predictive ControlLadoiye, Jasmeet Singh 10 October 2018 (has links)
Minimum invasive surgery is based on bilateral teleoperation in which surgeon interacts with the master side to the slave side that is located at a distance. The synchronization in between the two ends is through a communication channel. The primary objective in the telesurgery is the position and force tracking providing the surgeon with high fidelity. The presence of time delays in the communication channels makes the realization more difficult, and sometimes it may even destabilize the system.
The work focuses on a design of the force control system by using Model Predictive Control to compensate for the effects of the time delay related to the use of surgical arms. Another vital issue of minimum impact velocity during contact with the environment has been tried to achieve by using the prediction from the Model Predictive Control to prevent accidental tissue damage. This work also addresses a problem of the developing a simple delayed free predictive kinematic imaging to understand the type of behavior of the system during contact with the environment when no perception is available.
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Analysis and synthesis of distributed control systems under communication constraintsChen, Yuanye 21 December 2017 (has links)
With the help of rapidly advancing communication technology, control systems
are increasingly integrated via communication networks. Networked control systems
(NCSs) bring significant advantages such as flexible and scalable structures, easy
implementation and maintenance, and efficient resources distribution and allocation.
NCSs empowers to finish some complicated tasks using some relatively simple systems
in a collaborated manner. However, there are also some challenges and constraints
subject to the imperfection of communication channels. In this thesis, the stabilization
problems and the performance limitation problems of control systems subject to
networked-induced constraints are studied.
Overall, the thesis mainly includes two parts: 1) Consensus and consensusability
of multi-agent systems (MASs); 2) Delay margins of NCSs. Chapter 2 and Chapter 3
deal with the consensus problems of MASs, which aim to properly design the control
protocols to ensure the state convergence of all the agents. Chapter 4 and Chapter 5
focus on the consensusability analysis, exploring how the dynamics of the agents and
the networked induced constraints impact the overall systems for achieving consensus.
Chapter 6 pays attention to the delay margins of discrete-time linear time-invariant
(LTI) systems, studying how the dynamics of the plants limit the time delays that
can be tolerated by LTI controllers.
In Chapter 2, the leader-following consensus problem of MASs with general linear
dynamics and arbitrary switching topologies is considered. The MAS with arbitrary
switching topologies is formulated as a switched system. Then the leaderfollowing
consensus problem is transformed to the stability problem of the corresponding
switched system. A necessary and sufficient consensus condition is derived.
The condition is also extended to MASs with time-varying delays.
In Chapter 3, the consensus problem of MASs with general linear dynamics is
studied. Motivated by the multiple-input multiple-output (MIMO) communication
technique, a general framework is considered in which different state variables are
exchanged in different independent communication topologies. This novel framework
could improve the control system design flexibility and potentially improve the system
performance. Fully distributed consensus protocols are proposed and analyzed for
the settings of fixed and switching multiple topologies. The protocols can be applied
using only local information. And the control gains can be designed depending on
the dynamics of the individual agent. By transforming the overall MASs into cascade
systems, necessary and sufficient conditions are provided to guarantee the consensus
under fixed and switching state-variables-dependent topologies, respectively.
Chapter 4 investigates the consensusability problem for MASs with time-varying
delays. The bounded delays can be arbitrarily fast time-varying. The communication
topology is assumed to be undirected and fixed. Considering general linear dynamics
under average state protocols, the consensus problem is then transformed into a
robust control problem. Sufficient frequency domain criteria are established in terms
of small-gain theorem by analyzing the delay dependent gains for both continuoustime
and discrete-time systems. The controller synthesis problems can be solved by
applying the frequency domain design methods.
The consensusablity problem of general linear MASs considering directed topologies
are explored from a frequency domain perspective in Chapter 5. By investigating
the properties of Laplacian spectra, a consensus criterion is established based on the
stability of several complex weighted closed-loop systems. Furthermore, for singleinput
MASs, frequency domain consensusability criteria are proposed on the basis of
the stability margins, which depend on the H∞ norm of the complementary sensitivity
function determined by the agents’ unstable poles. The corresponding design
procedure is also developed.
Chapter 6 studies the delay margin problem of discrete-time LTI systems. For
general LTI plants with multiple unstable poles and nonminimum phase zeros, we
employ analytic function interpolation and rational approximation techniques to derive
bounds on delay margins. Readily computable and explicit lower bounds are
found by computing the real eigenvalues of a constant matrix, and LTI controllers can
be synthesized based on the H∞ control theory to achieve the bounds. The results
can be also consistently extended to the case of systems with time-varying delays.
For first-order unstable plants, we also obtain bounds achievable by proportionalintergral-
derivative (PID) controllers, which are of interest to PID control design and
implementation. It is worth noting that unlike its continuous-time counterpart, the
discrete-time delay margin problem being considered herein constitutes a simultaneous
stabilization problem, which is known to be rather difficult. While previous work
on the discrete-time delay margin led to negative results, the bounds developed in
this chapter provide instead a guaranteed range of delays within which the delayed
plants can be robustly stabilized, and in turn solve the special class of simultaneous
stabilization problems in question.
Finally, in Chapter 7, the thesis is summarized and some future research topics
are also presented. / Graduate
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Automatic clustering with application to time dependent fault detection in chemical processesLabuschagne, Petrus Jacobus 06 July 2009 (has links)
Fault detection and diagnosis presents a big challenge within the petrochemical industry. The annual economic impact of unexpected shutdowns is estimated to be $20 billion. Assistive technologies will help with the effective detection and classification of the faults causing these shutdowns. Clustering analysis presents a form of unsupervised learning which identifies data with similar properties. Various algorithms were used and included hard-partitioning algorithms (K-means and K-medoid) and fuzzy algorithms (Fuzzy C-means, Gustafson-Kessel and Gath-Geva). A novel approach to the clustering problem of time-series data is proposed. It exploits the time dependency of variables (time delays) within a process engineering environment. Before clustering, process lags are identified via signal cross-correlations. From this, a least-squares optimal signal time shift is calculated. Dimensional reduction techniques are used to visualise the data. Various nonlinear dimensional reduction techniques have been proposed in recent years. These techniques have been shown to outperform their linear counterparts on various artificial data sets including the Swiss roll and helix data sets but have not been widely implemented in a process engineering environment. The algorithms that were used included linear PCA and standard Sammon and fuzzy Sammon mappings. Time shifting resulted in better clustering accuracy on a synthetic data set based on than traditional clustering techniques based on quantitative criteria (including Partition Coefficient, Classification Entropy, Partition Index, Separation Index, Dunn’s Index and Alternative Dunn Index). However, the time shifted clustering results of the Tennessee Eastman process were not as good as the non-shifted data. Copyright / Dissertation (MEng)--University of Pretoria, 2009. / Chemical Engineering / unrestricted
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Cancer Invasion in Time and SpaceJanuary 2020 (has links)
abstract: Cancer is a disease involving abnormal growth of cells. Its growth dynamics is perplexing. Mathematical modeling is a way to shed light on this progress and its medical treatments. This dissertation is to study cancer invasion in time and space using a mathematical approach. Chapter 1 presents a detailed review of literature on cancer modeling.
Chapter 2 focuses sorely on time where the escape of a generic cancer out of immune control is described by stochastic delayed differential equations (SDDEs). Without time delay and noise, this system demonstrates bistability. The effects of response time of the immune system and stochasticity in the tumor proliferation rate are studied by including delay and noise in the model. Stability, persistence and extinction of the tumor are analyzed. The result shows that both time delay and noise can induce the transition from low tumor burden equilibrium to high tumor equilibrium. The aforementioned work has been published (Han et al., 2019b).
In Chapter 3, Glioblastoma multiforme (GBM) is studied using a partial differential equation (PDE) model. GBM is an aggressive brain cancer with a grim prognosis. A mathematical model of GBM growth with explicit motility, birth, and death processes is proposed. A novel method is developed to approximate key characteristics of the wave profile, which can be compared with MRI data. Several test cases of MRI data of GBM patients are used to yield personalized parameterizations of the model. The aforementioned work has been published (Han et al., 2019a).
Chapter 4 presents an innovative way of forecasting spatial cancer invasion. Most mathematical models, including the ones described in previous chapters, are formulated based on strong assumptions, which are hard, if not impossible, to verify due to complexity of biological processes and lack of quality data. Instead, a nonparametric forecasting method using Gaussian processes is proposed. By exploiting the local nature of the spatio-temporal process, sparse (in terms of time) data is sufficient for forecasting. Desirable properties of Gaussian processes facilitate selection of the size of the local neighborhood and computationally efficient propagation of uncertainty. The method is tested on synthetic data and demonstrates promising results. / Dissertation/Thesis / Doctoral Dissertation Applied Mathematics 2020
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STUDIES ON BILATERAL CONTROL OF TELEOPERATOR UNDER TIME DELAY / 時間遅れのあるバイラテラル遠隔制御に関する研究Imaida, Takashi 23 July 2015 (has links)
京都大学 / 0048 / 新制・課程博士 / 博士(工学) / 甲第19237号 / 工博第4072号 / 新制||工||1628(附属図書館) / 32236 / 京都大学大学院工学研究科航空宇宙工学専攻 / (主査)教授 泉田 啓, 教授 藤本 健治, 教授 松野 文俊 / 学位規則第4条第1項該当 / Doctor of Philosophy (Engineering) / Kyoto University / DFAM
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The Effects of Behavioral Skills Training on a Mother's Implementation ofConstant Time Delay for her Children with Autism and Developmental DelayChen, Yu Ling 30 July 2019 (has links)
No description available.
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Topological Data Analysis on Road Network DataZha, Xiao 29 August 2019 (has links)
No description available.
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Performance Evaluation of Hybrid and Predictive Controllers In Remote SurgeryChai, Vivian 25 May 2023 (has links)
Telerobotics are becoming increasingly more prevalent in the medical field due to the many advantages they have over standard methods. In particular, their use in surgical procedures provides benefits such as safer operations and greater health care access, among others. However, there are drawbacks that dissuade telerobotic usage and aspects that can still be improved upon. Examples of these include the inevitable impact of time delay and the existence of disturbances, such as patient-manipulator contact. These factors can result in system destabilization and ultimately task failure, discouraging the usage of telerobotics in these settings.
This thesis investigates the effects of time delay and contact disturbances on telerobotic performance in a surgical setting. In this work, different methods of improving telerobotic performance such as using hybrid controllers and predictive technology are explored. The goal is to investigate options for mitigating the negative effects of these elements while improving overall telerobotic performance.
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Power System Stability Improvement with Decommissioned Synchronous Machine Using Koopman Operator Based Model Predictive ControlLi, Xiawen 06 September 2019 (has links)
Traditional generators have been decommissioned or replaced by renewable energy generation due to utility long-standing goals. However, instead of flattening the entire plant, the rotating mass of generator can be utilized as a storage unit (inertia resource) to mitigate the frequency swings during transient caused by the renewables. The goal of this work is to design a control strategy utilizing the decommissioned generator interfaced with power grid via a back-to-back converter to provide inertia support. This is referred to as decoupled synchronous machine system (DSMS). On top of that, the grid-side converter is capable of providing reactive power as an auxiliary voltage controller. However, in a practical setting, for power utilities, the detailed state equations of such device as well as the complicated nonlinear power system are usually unobtainable making the controller design a challenging problem. Therefore, a model free, purely data-driven strategy for the nonlinear controller design using Koopman operator-based framework is proposed. Besides, the time delay embedding technique is adopted together with Koopman operator theory for the nonlinear system identification. Koopman operator provides a linear representation of the system and thereby the classical linear control algorithms can be applied. In this work, model predictive control is adopted to cope with the constraints of the control signals. The effectiveness and robustness of the proposed system are demonstrated in Kundur two-area system and IEEE 39-bus system. / Doctor of Philosophy / Power system is facing an energy transformation from the traditional fuel to sustainable renewable such as solar, wind and so on. Unlike the traditional fuel energized generators, the renewable has very little inertia to maintain frequency stability. Therefore, this work proposes a new system referred to as decoupled synchronous machine system (DSMS) to support the grid frequency. DSMS consists of the rotating mass of generator and a back-to-back converter which can be utilized as an inertia resource to mitigate the frequency oscillations. In addition, the grid-side converter can provide reactive power to improve voltage performance during faults. This work aims to design a control strategy utilizing DSMS to support grid frequency and voltage. However, an explicit mathematical model of such device is unobtainable in a practical setting making data-driven control the only option. A data-driven technique which is Koopman operator-based framework together with time delay embedding algorithm is proposed to obtain a linear representation of the system. The effectiveness and robustness of the proposed system are demonstrated in Kundur two-area system and IEEE 39-bus system.
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