0.18 um CMOS technology is increasingly used in design and implementation of full adder cells. Hence, there is a need for better understanding of the effects of different cell designs on cell performance, including power dissipation and time delays. This thesis contributes to better understanding of the behavior of single-bit full adder cells when low power-delay products are essential. Thirty one single-bit full adder cells have been implemented in Cadence tool suit and simulated using 0.18 µm CMOS technology to obtain a comprehensive study of the performance of the cells with respect to time (time-delays) and power consumption (power dissipation). Simulation method used for performance measurements has been carefully devised to achieve as accurate measurements as possible with respect to time delay and power dissipation. The method combines the simple measurement technique for obtaining accurate time-delays and power dissipation of a cell, and the transistor resizing technique that allows systematicallyresizing of transistors to achieve minimal power-delay product. The original technique of sizing of the transistors has been extended in this thesis for the purpose of the performance measurements to include both resizing the transistors in the critical path and resizing the transistors on the global level, and therefore efficiently obtain minimal power-delay product for every cell. The result of this performance study is an extensive knowledge of full adder cell behaviour with respect to time and power, including the limitations of the 0.18 µm CMOS technology when used in the area of full adder cells. Furthermore, the study identified full adder cell designs that demonstrated the best performance results with respect to power-delay products. In general, the complex performance simulation method in this thesis that combines the simulation of time delay and critical path transistor resizing provides the most accurate measurements and as such can be used in the future performance analysis of single-bit full adder cells.

This work deals with the control of the human immune system. A standard immune system model is modified by introducing control signals corresponding to drug cocktail and immune suppressor treatments. The ultimate objective is to use these control signals to 'cure' a chronically-ill patient. Control is challenging for this system due to nonlinearities and time delays. In fact, it is shown that fundamental aspects of the system dynamics are lost when the system is linearised; hence, control approaches involving linearisation are fruitless. Feedback linearisation and some optimal control methods are also investigated and shown to be infeasible. However, it is shown that, for certain parameter values and initial conditions related to the virus and patient, a specific open-loop control scheme using only the drug cocktail achieves the objective. It is also proven that, unfortunately, this control scheme fails for other parameter values and initial conditions. A two-stage open-loop controller that uses both control inputs is then proposed. It is shown in simulation that the two-stage controller works over a larger set of parameters and initial conditions than the single-stage controller, but a rigorous analysis of the two-stage controller remains elusive.

Motivated by recent research to automate radiotherapy, this thesis looks into feedback control problems where the feedback sensor imposes considerable time delay. The use of an asymptotic estimator is considered as a method to compensate for the time delay. Properties and parameterizations of asymptotic estimators are analyzed. It is shown that if such a delay compensation scheme is adopted, a separation principle holds, which allows for independent design of the feedback controller and the time delay compensator. The radiotherapy problem is used as a case study to show how asymptotic estimators may be designed, exploiting the separation principle. Lastly, the thesis considers multivariable versions of asymptotic estimators.

Networked control systems (NCSs) are a kind of distributed control systems in which the data between control components are exchanged via communication networks. Because of the attractive advantages of NCSs such as reduced system wiring, low weight, and ease of system diagnosis and maintenance, the research on NCSs has received much attention in recent years. The first part (Chapter 2 - Chapter 4) of the thesis is devoted to designing new controllers for NCSs by incorporating the network-induced delays. The thesis also conducts research on filtering of multirate systems and identification of Hammerstein systems in the second part (Chapter 5 - Chapter 6).<br /><br /> Network-induced delays exist in both sensor-to-controller (S-C) and controller-to-actuator (C-A) links. A novel two-mode-dependent control scheme is proposed, in which the to-be-designed controller depends on both S-C and C-A delays. The resulting closed-loop system is a special jump linear system. Then, the conditions for stochastic stability are obtained in terms of a set of linear matrix inequalities (LMIs) with nonconvex constraints, which can be efficiently solved by a sequential LMI optimization algorithm. Further, the control synthesis problem for the NCSs is considered. The definitions of <em>H₂</em> and <em>H_∞</em> norms for the special system are first proposed. Also, the plant uncertainties are considered in the design. Finally, the robust mixed <em>H₂/H_&infin;</em> control problem is solved under the framework of LMIs. <br /><br /> To compensate for both S-C and C-A delays modeled by Markov chains, the generalized predictive control method is modified to choose certain predicted future control signal as the current control effort on the actuator node, whenever the control signal is delayed. Further, stability criteria in terms of LMIs are provided to check the system stability. The proposed method is also tested on an experimental hydraulic position control system. <br /><br /> Multirate systems exist in many practical applications where different sampling rates co-exist in the same system. The <em>l₂-l_&infin;</em> filtering problem for multirate systems is considered in the thesis. By using the lifting technique, the system is first transformed to a linear time-invariant one, and then the filter design is formulated as an optimization problem which can be solved by using LMI techniques. <br /><br /> Hammerstein model consists of a static nonlinear block followed in series by a linear dynamic system, which can find many applications in different areas. New switching sequences to handle the two-segment nonlinearities are proposed in this thesis. This leads to less parameters to be estimated and thus reduces the computational cost. Further, a stochastic gradient algorithm based on the idea of replacing the unmeasurable terms with their estimates is developed to identify the Hammerstein model with two-segment nonlinearities. <br /><br /> Finally, several open problems are listed as the future research directions.

In conventional bilateral teleoperation, transmission delay over the Internet can potentially cause instability. The wave variable algorithm guarantees stability under varying transmission delay at the cost of poor transient performance. Adding a predictor on the master side can reduce this undesirable side-effect, but that would require a slave model. An inaccurate slave model used in the predictor as well as variations in transmission delay, both of which are likely under realistic situations, can result in steady state errors. A direct drift control algorithm is used to drive this error to zero regardless of the source of error. A semi-adaptive predictor that can distinguish between free space and rigid contact environment is used to provide more accurate force feedback on the master side. A full adaptive predictor is also used that estimates the slave environment parameters using recursive least squares with a forgetting factor. This research presents the experimental results and evaluations of the wave variable based methods under a realistic operation environment using a real master and slave. The effectiveness of this algorithm is fully evaluated using human subjects with no previous experience in haptics. Three algorithms are tested using PHANTOM brand haptic devices as master and slave: conventional bilateral teleoperation with no transmission delay as control, wave variable teleoperation with approximately 200 ms transmission delay one way, and wave variables with adaptive predictor and direct drift control with approximately 200 ms transmission delay one way. For each algorithm the human subjects are asked to perform three simple tasks: use the master to force the slave to track a reference trajectory in free space with the least amount of error, identify a contour surface on the slave side as accurately as possible using only haptic information from the master, and navigate a simple maze on the slave side in the least amount of time using haptic information from the master.

In recent years, relay communication has been proved to achieve the transmis-sion diversity order with space-time block coding (STBC). Most research assumedthat the relay nodes are in perfect synchronization. However, in actual, becausethe transmitting time at each relay is different, the signals from different relays received at destination will interfere with each other. Inter-symbol interference (ISI) iscaused. Besides, the time synchronization error will reduce orthogonality of space-time block coding and result in serious performance degrade. This thesis proposes a time delay compensation method by using Fourier transform and Least Square(LS)estimation method. The destination node can utilize the estimated time delay tosynchronize the received signal. Then, the space-time coding will maintain orthogonality at the receiver. Simulation results show that the proposed method caneffectively improve the performance of cooperative networks when imperfect timesynchronization exists.

In this thesis an adaptive backstepping control scheme is proposed for a class of multi-input perturbed systems with time-varying delays to solve regulation problems. The systems to be controlled contain n blocks¡¦ dynamic equations, hence n-1 virtual input controllers are designed from the first block to the (n-1)th block, and the backstepping controller is designed from the last block. In addition, adaptive mechanisms are embedded in each virtual input controllers and proposed controller, so that the least upper bounds of perturbations are not required to be known beforehand. Furthermore, the dynamic equations of the systems to be controlled need not satisfy strict-feedback form, and the upper bounds of the time delays as well as their derivatives need not to be known in advance either. The resultant controlled systems guarantee asymptotic stability in accordance with the Lyapunov stability theorem. Finally, a numerical example and a practical application are given for demonstrating the feasibility of the proposed control scheme.

Considered in this research is a framework for effective formation control of multirobot systems in dynamic environments. The basic formation control involves two important considerations: (1) Real-time trajectory generation algorithms for distributed control based on nominal agent models, and (2) robust tracking of reference trajectories under model uncertainties. Proposed is a two-layer hierarchical architecture for collectivemotion control ofmultirobot nonholonomic systems. It endows robotic systems with the ability to simultaneously deal with multiple tasks and achieve typical complex formation missions, such as collisionfree maneuvers in dynamic environments, tracking certain desired trajectories, forming suitable patterns or geometrical shapes, and/or varying the pattern when necessary. The study also addresses real-time formation tracking of reference trajectories under the presence of model uncertainties and proposes robust control laws such that over each time interval any tracking errors due to system uncertainties are driven down to zero prior to the commencement of the subsequent computation segment. By considering a class of nonlinear systems with favorable finite-time convergence characteristics, sufficient conditions for exponential finite-time stability are established and then applied to distributed formation tracking controls. This manifests in the settling time of the controlled system being finite and no longer than the predefined reference trajectory segment computing time interval, thus making tracking errors go to zero by the end of the time horizon over which a segment of the reference trajectory is generated. This way the next segment of the reference trajectory is properly initialized to go into the trajectory computation algorithm. Consequently this could lead to a guarantee of desired multi-robot motion evolution in spite of system uncertainties. To facilitate practical implementation, communication among multi-agent systems is considered to enable the construction of distributed formation control. Instead of requiring global communication among all robots, a distributed communication algorithm is employed to eliminate redundant data propagation, thus reducing energy consumption and improving network efficiency while maintaining connectivity to ensure the convergence of formation control.

In the laser market, there have been various kinds of lasers designed and utilized for different purposes. As time goes on, their powers have been gradually increased from kilowatts (kW) to terawatts (TW). One of the most famous methods in laser science technology is Chirped Pulse Amplification (CPA) which enables table-top terawatt laser systems. This method provides high output power (tens of TW), very short pulse duration (few tens of femtoseconds) and large energy (mJ) for ultrafast lasers. One of the most well-known ultrafast lasers is Titanium:Sapphire laser. This thesis work concentrates on how delay a pulse generator should work so that Verdi and the oscillator pulse coincide. Moreover, by assembling a terawatt laser system, the most important issues are timing between seed pulse and pump pulse and time delays of all components of this system / autocorrelator, pump source, photodiode, Pockels cell, stretcher and dazzler were examined. This timing and the time delays were separately identified for terawatt laser systems. In this study, the aim is to attain the terawatt level output by arranging pump and seed pulses timing and the time delay on the components of the laser system setup.

n the problem of time delay estimation (TDE), the desired source signals of interest are correlated and with a specific spectral distribution. In such cases, the convergence speed using the conventional approaches, viz., time domain adaptive constrained and unconstrained LMS TDE algorithms, becomes slowly and the performance of TDE will be degraded, dramatically. In fact, the convergence rate depends highly on the distribution of spectral density of the desired signal sources. Also, the performance of TDE is affected by the background noises, accordingly. To circumvent the problem described above, in this thesis, a transformed domain adaptive constrained filtering scheme, refers to the constrained adaptive DCT-LMS algorithm, for TDE is devised. We show that this new proposed constrained algorithm, with the so-called direct delay estimation formula, for non-integer TDE does perform better than the conventional time domain adaptive constrained and unconstrained LMS TDE algorithms and the unconstrained adaptive DCT-LMS TDE algorithm. Finally, to further reduce the spread of eigenvalue in the unconstrained adaptive DCT-LMS algorithm, the Gram-Schmidt orthogonalizer approach realizing by the adaptive Escalator is investigated. It indicates that bias of TDE will occur without using the constraint of weight vector. That is, it could not be used to alleviate the effect due to background noises.