Transceiver designs and analysis for LTI, LTV and broadcast channels - new matrix decompositions and majorization theory

Signal processing techniques play important roles in the design of digital communication systems. These include information manipulation, transmitter signal processing, channel estimation, channel equalization and receiver signal processing. By interacting with communication theory and system implementing technologies, signal processing specialists develop efficient schemes for various communication problems by wisely exploiting various mathematical tools such as analysis, probability theory, matrix theory, optimization theory, and many others. In recent years, researchers realized that multiple-input multiple-output (MIMO) channel models are applicable to a wide range of different physical communications channels. Using the elegant matrix-vector notations, many MIMO transceiver (including the precoder and equalizer) design problems can be solved by matrix and optimization theory. Furthermore, the researchers showed that the majorization theory and matrix decompositions, such as singular value decomposition (SVD), geometric mean decomposition (GMD) and generalized triangular decomposition (GTD), provide unified frameworks for solving many of the point-to-point MIMO transceiver design problems.

In this thesis, we consider the transceiver design problems for linear time invariant (LTI) flat MIMO channels, linear time-varying narrowband MIMO channels, flat MIMO broadcast channels, and doubly selective scalar channels. Additionally, the channel estimation problem is also considered. The main contributions of this dissertation are the development of new matrix decompositions, and the uses of the matrix decompositions and majorization theory toward the practical transmit-receive scheme designs for transceiver optimization problems. Elegant solutions are obtained, novel transceiver structures are developed, ingenious algorithms are proposed, and performance analyses are derived.

The first part of the thesis focuses on transceiver design with LTI flat MIMO channels. We propose a novel matrix decomposition which decomposes a complex matrix as a product of several sets of semi-unitary matrices and upper triangular matrices in an iterative manner. The complexity of the new decomposition, generalized geometric mean decomposition (GGMD), is always less than or equal to that of geometric mean decomposition (GMD). The optimal GGMD parameters which yield the minimal complexity are derived. Based on the channel state information (CSI) at both the transmitter (CSIT) and receiver (CSIR), GGMD is used to design a butterfly structured decision feedback equalizer (DFE) MIMO transceiver which achieves the minimum average mean square error (MSE) under the total transmit power constraint. A novel iterative receiving detection algorithm for the specific receiver is also proposed. For the application to cyclic prefix (CP) systems in which the SVD of the equivalent channel matrix can be easily computed, the proposed GGMD transceiver has K/log_2(K) times complexity advantage over the GMD transceiver, where K is the number of data symbols per data block and is a power of 2. The performance analysis shows that the GGMD DFE transceiver can convert a MIMO channel into a set of parallel subchannels with the same bias and signal to interference plus noise ratios (SINRs). Hence, the average bit rate error (BER) is automatically minimized without the need for bit allocation. Moreover, the proposed transceiver can achieve the channel capacity simply by applying independent scalar Gaussian codes of the same rate at subchannels.

In the second part of the thesis, we focus on MIMO transceiver design for slowly time-varying MIMO channels with zero-forcing or MMSE criterion. Even though the GGMD/GMD DFE transceivers work for slowly time-varying MIMO channels by exploiting the instantaneous CSI at both ends, their performance is by no means optimal since the temporal diversity of the time-varying channels is not exploited. Based on the GTD, we develop space-time GTD (ST-GTD) for the decomposition of linear time-varying flat MIMO channels. Under the assumption that CSIT, CSIR and channel prediction are available, by using the proposed ST-GTD, we develop space-time geometric mean decomposition (ST-GMD) DFE transceivers under the zero-forcing or MMSE criterion. Under perfect channel prediction, the new system minimizes both the average MSE at the detector in each space-time (ST) block (which consists of several coherence blocks), and the average per ST-block BER in the moderate high SNR region. Moreover, the ST-GMD DFE transceiver designed under an MMSE criterion maximizes Gaussian mutual information over the equivalent channel seen by each ST-block. In general, the newly proposed transceivers perform better than the GGMD-based systems since the super-imposed temporal precoder is able to exploit the temporal diversity of time-varying channels. For practical applications, a novel ST-GTD based system which does not require channel prediction but shares the same asymptotic BER performance with the ST-GMD DFE transceiver is also proposed.

The third part of the thesis considers two quality of service (QoS) transceiver design problems for flat MIMO broadcast channels. The first one is the power minimization problem (min-power) with a total bitrate constraint and per-stream BER constraints. The second problem is the rate maximization problem (max-rate) with a total transmit power constraint and per-stream BER constraints. Exploiting a particular class of joint triangularization (JT), we are able to jointly optimize the bit allocation and the broadcast DFE transceiver for the min-power and max-rate problems. The resulting optimal designs are called the minimum power JT broadcast DFE transceiver (MPJT) and maximum rate JT broadcast DFE transceiver (MRJT), respectively. In addition to the optimal designs, two suboptimal designs based on QR decomposition are proposed. They are realizable for arbitrary number of users.

Finally, we investigate the design of a discrete Fourier transform (DFT) modulated filterbank transceiver (DFT-FBT) with LTV scalar channels. For both cases with known LTV channels and unknown wide sense stationary uncorrelated scattering (WSSUS) statistical channels, we show how to optimize the transmitting and receiving prototypes of a DFT-FBT such that the SINR at the receiver is maximized. Also, a novel pilot-aided subspace channel estimation algorithm is proposed for the orthogonal frequency division multiplexing (OFDM) systems with quasi-stationary multi-path Rayleigh fading channels. Using the concept of a difference co-array, the new technique can construct M^2 co-pilots from M physical pilot tones with alternating pilot placement. Subspace methods, such as MUSIC and ESPRIT, can be used to estimate the multipath delays and the number of identifiable paths is up to O(M^2), theoretically. With the delay information, a MMSE estimator for frequency response is derived. It is shown through simulations that the proposed method outperforms the conventional subspace channel estimator when the number of multipaths is greater than or equal to the number of physical pilots minus one.

Design, specification, and synthesis of aircraft electric power systems control logic

Cyber-physical systems integrate computation, networking, and physical processes. Substantial research challenges exist in the design and verification of such large-scale, distributed sensing, ac- tuation, and control systems. Rapidly improving technology and recent advances in control theory, networked systems, and computer science give us the opportunity to drastically improve our approach to integrated flow of information and cooperative behavior. Current systems rely on text-based spec- ifications and manual design. Using new technology advances, we can create easier, more efficient, and cheaper ways of developing these control systems. This thesis will focus on design considera- tions for system topologies, ways to formally and automatically specify requirements, and methods to synthesize reactive control protocols, all within the context of an aircraft electric power system as a representative application area.

This thesis consists of three complementary parts: synthesis, specification, and design. The first section focuses on the synthesis of central and distributed reactive controllers for an aircraft elec- tric power system. This approach incorporates methodologies from computer science and control. The resulting controllers are correct by construction with respect to system requirements, which are formulated using the specification language of linear temporal logic (LTL). The second section addresses how to formally specify requirements and introduces a domain-specific language for electric power systems. A software tool automatically converts high-level requirements into LTL and synthesizes a controller.

The final sections focus on design space exploration. A design methodology is proposed that uses mixed-integer linear programming to obtain candidate topologies, which are then used to synthesize controllers. The discrete-time control logic is then verified in real-time by two methods: hardware and simulation. Finally, the problem of partial observability and dynamic state estimation is ex- plored. Given a set placement of sensors on an electric power system, measurements from these sensors can be used in conjunction with control logic to infer the state of the system.

On erasure coding for distributed storage and streaming communications

The work presented in this thesis revolves around erasure correction coding, as applied to distributed data storage and real-time streaming communications.

First, we examine the problem of allocating a given storage budget over a set of nodes for maximum reliability. The objective is to find an allocation of the budget that maximizes the probability of successful recovery by a data collector accessing a random subset of the nodes. This optimization problem is challenging in general because of its combinatorial nature, despite its simple formulation. We study several variations of the problem, assuming different allocation models and access models, and determine the optimal allocation and the optimal symmetric allocation (in which all nonempty nodes store the same amount of data) for a variety of cases. Although the optimal allocation can have nonintuitive structure and can be difficult to find in general, our results suggest that, as a simple heuristic, reliable storage can be achieved by spreading the budget maximally over all nodes when the budget is large, and spreading it minimally over a few nodes when it is small. Coding would therefore be beneficial in the former case, while uncoded replication would suffice in the latter case.

Second, we study how distributed storage allocations affect the recovery delay in a mobile setting. Specifically, two recovery delay optimization problems are considered for a network of mobile storage nodes: the maximization of the probability of successful recovery by a given deadline, and the minimization of the expected recovery delay. We show that the first problem is closely related to the earlier allocation problem, and solve the second problem completely for the case of symmetric allocations. It turns out that the optimal allocations for the two problems can be quite different. In a simulation study, we evaluated the performance of a simple data dissemination and storage protocol for mobile delay-tolerant networks, and observed that the choice of allocation can have a significant impact on the recovery delay under a variety of scenarios.

Third, we consider a real-time streaming system where messages created at regular time intervals at a source are encoded for transmission to a receiver over a packet erasure link; the receiver must subsequently decode each message within a given delay from its creation time. For erasure models containing a limited number of erasures per coding window, per sliding window, and containing erasure bursts whose maximum length is sufficiently short or long, we show that a time-invariant intrasession code asymptotically achieves the maximum message size among all codes that allow decoding under all admissible erasure patterns. For the bursty erasure model, we also show that diagonally interleaved codes derived from specific systematic block codes are asymptotically optimal over all codes in certain cases. We also study an i.i.d. erasure model in which each transmitted packet is erased independently with the same probability; the objective is to maximize the decoding probability for a given message size. We derive an upper bound on the decoding probability for any time-invariant code, and show that the gap between this bound and the performance of a family of time-invariant intrasession codes is small when the message size and packet erasure probability are small. In a simulation study, these codes performed well against a family of random time-invariant convolutional codes under a number of scenarios.

Finally, we consider the joint problems of routing and caching for named data networking. We propose a backpressure-based policy that employs virtual interest packets to make routing and caching decisions. In a packet-level simulation, the proposed policy outperformed a basic protocol that combines shortest-path routing with least-recently-used (LRU) cache replacement.

Optimal uncertainty quantification via convex optimization and relaxation

Many engineering applications face the problem of bounding the expected value of a quantity of interest (performance, risk, cost, etc.) that depends on stochastic uncertainties whose probability distribution is not known exactly. Optimal uncertainty quantification (OUQ) is a framework that aims at obtaining the best bound in these situations by explicitly incorporating available information about the distribution. Unfortunately, this often leads to non-convex optimization problems that are numerically expensive to solve.

This thesis emphasizes on efficient numerical algorithms for OUQ problems. It begins by investigating several classes of OUQ problems that can be reformulated as convex optimization problems. Conditions on the objective function and information constraints under which a convex formulation exists are presented. Since the size of the optimization problem can become quite large, solutions for scaling up are also discussed. Finally, the capability of analyzing a practical system through such convex formulations is demonstrated by a numerical example of energy storage placement in power grids.

When an equivalent convex formulation is unavailable, it is possible to find a convex problem that provides a meaningful bound for the original problem, also known as a convex relaxation. As an example, the thesis investigates the setting used in Hoeffding's inequality. The naive formulation requires solving a collection of non-convex polynomial optimization problems whose number grows doubly exponentially. After structures such as symmetry are exploited, it is shown that both the number and the size of the polynomial optimization problems can be reduced significantly. Each polynomial optimization problem is then bounded by its convex relaxation using sums-of-squares. These bounds are found to be tight in all the numerical examples tested in the thesis and are significantly better than Hoeffding's bounds.

Synthesis and potency of long end-associative polymers for mist control

Long linear polymers that are end-functionalized with associative groups were studied as additives to hydrocarbon fluids to mitigate the fire hazard associated with the presence of mist in a crash scenario. These polymers were molecularly designed to overcome both the shear-degradation of long polymer chains in turbulent flows, and the chain collapse induced by the random placement of associative groups along polymer backbones. Architectures of associative groups on the polymer chain ends that were tested included clusters of self-associative carboxyl groups and pairs of hetero-complementary associative units.

Linear polymers with clusters of discrete numbers of carboxyl groups on their chain ends were investigated first: an innovative synthetic strategy was devised to achieve unprecedented backbone lengths and precise control of the number of carboxyl groups on chain ends (N). We found that a very narrow range of N allows the co-existence of sufficient end-association strength and polymer solubility in apolar media. Subsequent steady-flow rheological study on solution behavior of such soluble polymers in apolar media revealed that the end-association of very long chains in apolar media leads to the formation of flower-like micelles interconnected by bridging chains, which trap significant fraction of polymer chains into looped structures with low contribution to mist-control. The efficacy of very long 1,4-polybutadiene chains end-functionalized with clusters of four carboxyl groups as mist-control additives for jet fuel was further tested. In addition to being shear-resistant, the polymer was found capable of providing fire-protection to jet fuel at concentrations as low as 0.3wt%. We also found that this polymer has excellent solubility in jet fuel over a wide range of temperature (-30 to +70°C) and negligible interference with dewatering of jet fuel. It does not cause an adverse increase in viscosity at concentrations where mist-control efficacy exists.

Four pairs of hetero-complementary associative end-groups of varying strengths were subsequently investigated, in the hopes of achieving supramolecular aggregates with both mist-control ability and better utilization of polymer building blocks. Rheological study of solutions of the corresponding complementary associative polymer pairs in apolar media revealed the strength of complementary end-association required to achieve supramolecular aggregates capable of modulating rheological properties of the solution.

Both self-associating and complementary associating polymers have therefore been found to resist shear degradation. The successful strategy of building soluble, end-associative polymers with either self-associative or complementary associative groups will guide the next generation of mist-control technology.

Electron transfer in chemically and genetically modified myoglobins

The temperature dependences of the reduction potentials (E^o') of wildtype human myoglobin (Mb) and three site-directed mutants have been measured by using thin-layer spectroelectrochemistry. Residue Val68, which is in van der Waals contact with the heme in Mb, has been replaced by Glu, Asp, and Asn. At pH 7.0, reduction of the heme iron (III) in the former two proteins is accompanied by uptake of a proton by the protein. The changes in E^o', and the standard entropy (ΔS^o') and enthalpy (ΔH^o') of reduction in the mutant proteins were determined relative to values for wild-type; the change in E^o' at 25°C was about -200 millivolts for the Glu and Asp mutants, and about -80 millivolts for the Asn mutant. Reduction of Fe(III) to Fe(II) in the Glu and Asp mutants is accompanied by uptake of a proton. These studies demonstrate that Mb can tolerate substitution of a buried hydrophobic group by potentially charged and polar residues, and that such amino acid replacements can lead to substantial changes in the redox thermodynamics of the protein.

Through analysis of the temperature dependence and shapes of NMR dispersion signals, it is determined that a water molecule is bound to the sixth coordination site of the ferric heme in the Val68Asp and in the Val68Asn recombinant proteins while the carboxyl group of the sidechain of Glu68 occupies this position in Val68Glu. The relative rhombic distortions in the ESR spectra of these mutant proteins combined with H₂¹⁷O and spin interconversion experiments performed on them confirm the conclusions of the NMRD study.

The rates of intramolecular electron transfer (ET) of (NH₃)₅Ru-His48 (Val68Asp, His81GIn, Cys110AIa)Mb and (NH₃)₅Ru-His48 (Val68GIu,His81GIn,Cys110Ala)Mb were measured to be .85(3)s^-1 and .30(2)s^-1, respectively. This data supports the hypothesis that entropy of 111 reduction and reorganization energy of ET are inversely related. The rates of forward and reverse ET for (NH₃)₅ Ru-His48 (Val68GIu, His81 GIn, Cys110AIa)ZnMb -7.2(5)•10⁴s^-1and 1.4(2)•10⁵s^-1, respectively- demonstrate that the placement of a highly polar residue nearby does not significantly change the reorganization energy of the photoactive Zn porphyrin.

The distal histidine imidazoles of (NH₃)₄isnRu-His48 SWMb and (NH₃)₅Ru-His48 SWMb were cyanated with BrCN. The intramolecular ET rates of these BrCN-modified Mb derivatives are 5.5(6)s^-1 and 3.2(5)s^-1, respectively. These respective rates are 20 and 10 times faster than those of their noncyanated counterparts after the differences in ET rate from driving force are scaled according to the Marcus equation. This increase in ET rate of the cyanated Mb derivatives is attributed to lower reorganization energy since the cyanated Mb heme is pentacoordinate in both oxidation states; whereas, the native Mb heme loses a water molecule upon reduction so that it changes from six to five coordinate. The reorganization energy from Fe-OH₂ dissociation is estimated to be .2eV. This conclusion is used to reconcile data from previous experiments in our lab. ET in photoactive porphyrin-substituted myoglobins proceed faster than predicted by Marcus Theory when it is assumed that the only difference in ET parameters between photoactive porphyrins and native heme systems is driving force. However, the data can be consistently fit to Marcus Theory if one corrects for the smaller reorganization in the photoactive porphyrin systems since they do not undergo a coordination change upon ET.

Finally, the intramolecular ET rate of (NH₃)₄isnRu-His48 SWMb was measured to be 3.0(4)s^-1. This rate is within experimental error of that for (NH₃)₄pyrRu-His48 SWMb even though the former has 80mV more driving force. One likely possibility for this observation is that the tetraamminepyridineruthenium group undergoes less reorganization upon ET than the tetraammineisonicotinamideruthenium group. Moreover, analysis of the (NH₃)₄isnRu-His48 SWMb experimental system gives a likely explanation of why ET was not observed previously in (NH₃)₄isnRu-Cytochrome C.

DNA-Mediated Charge Transport Devices for Protein Detection

Detection of biologically relevant targets, including small molecules, proteins, DNA, and RNA, is vital for fundamental research as well as clinical diagnostics. Sensors with biological elements provide a natural foundation for such devices because of the inherent recognition capabilities of biomolecules. Electrochemical DNA platforms are simple, sensitive, and do not require complex target labeling or expensive instrumentation. Sensitivity and specificity are added to DNA electrochemical platforms when the physical properties of DNA are harnessed. The inherent structure of DNA, with its stacked core of aromatic bases, enables DNA to act as a wire via DNA-mediated charge transport (DNA CT). DNA CT is not only robust over long molecular distances of at least 34 nm, but is also especially sensitive to anything that perturbs proper base stacking, including DNA mismatches, lesions, or DNA-binding proteins that distort the π-stack. Electrochemical sensors based on DNA CT have previously been used for single-nucleotide polymorphism detection, hybridization assays, and DNA-binding protein detection. Here, improvements to (i) the structure of DNA monolayers and (ii) the signal amplification with DNA CT platforms for improved sensitivity and detection are described.

First, improvements to the control over DNA monolayer formation are reported through the incorporation of copper-free click chemistry into DNA monolayer assembly. As opposed to conventional film formation involving the self-assembly of thiolated DNA, copper-free click chemistry enables DNA to be tethered to a pre-formed mixed alkylthiol monolayer. The total amount of DNA in the final film is directly related to the amount of azide in the underlying alkylthiol monolayer. DNA monolayers formed with this technique are significantly more homogeneous and lower density, with a larger amount of individual helices exposed to the analyte solution. With these improved monolayers, significantly more sensitive detection of the transcription factor TATA binding protein (TBP) is achieved.

Using low-density DNA monolayers, two-electrode DNA arrays were designed and fabricated to enable the placement of multiple DNA sequences onto a single underlying electrode. To pattern DNA onto the primary electrode surface of these arrays, a copper precatalyst for click chemistry was electrochemically activated at the secondary electrode. The location of the secondary electrode relative to the primary electrode enabled the patterning of up to four sequences of DNA onto a single electrode surface. As opposed to conventional electrochemical readout from the primary, DNA-modified electrode, a secondary microelectrode, coupled with electrocatalytic signal amplification, enables more sensitive detection with spatial resolution on the DNA array electrode surface. Using this two-electrode platform, arrays have been formed that facilitate differentiation between well-matched and mismatched sequences, detection of transcription factors, and sequence-selective DNA hybridization, all with the incorporation of internal controls.

For effective clinical detection, the two working electrode platform was multiplexed to contain two complementary arrays, each with fifteen electrodes. This platform, coupled with low density DNA monolayers and electrocatalysis with readout from a secondary electrode, enabled even more sensitive detection from especially small volumes (4 μL per well). This multiplexed platform has enabled the simultaneous detection of two transcription factors, TBP and CopG, with surface dissociation constants comparable to their solution dissociation constants.

With the sensitivity and selectivity obtained from the multiplexed, two working electrode array, an electrochemical signal-on assay for activity of the human methyltransferase DNMT1 was incorporated. DNMT1 is the most abundant human methyltransferase, and its aberrant methylation has been linked to the development of cancer. However, current methods to monitor methyltransferase activity are either ineffective with crude samples or are impractical to develop for clinical applications due to a reliance on radioactivity. Electrochemical detection of methyltransferase activity, in contrast, circumvents these issues. The signal-on detection assay translates methylation events into electrochemical signals via a methylation-specific restriction enzyme. Using the two working electrode platform combined with this assay, DNMT1 activity from tumor and healthy adjacent tissue lysate were evaluated. Our electrochemical measurements revealed significant differences in methyltransferase activity between tumor tissue and healthy adjacent tissue.

As differential activity was observed between colorectal tumor tissue and healthy adjacent tissue, ten tumor sets were subsequently analyzed for DNMT1 activity both electrochemically and by tritium incorporation. These results were compared to expression levels of DNMT1, measured by qPCR, and total DNMT1 protein content, measured by Western blot. The only trend detected was that hyperactivity was observed in the tumor samples as compared to the healthy adjacent tissue when measured electrochemically. These advances in DNA CT-based platforms have propelled this class of sensors from the purely academic realm into the realm of clinically relevant detection.

Distributed Optimal Control of Cyber-Physical Systems: Controller Synthesis, Architecture Design and System Identification

The centralized paradigm of a single controller and a single plant upon which modern control theory is built is no longer applicable to modern cyber-physical systems of interest, such as the power-grid, software defined networks or automated highways systems, as these are all large-scale and spatially distributed. Both the scale and the distributed nature of these systems has motivated the decentralization of control schemes into local sub-controllers that measure, exchange and act on locally available subsets of the globally available system information. This decentralization of control logic leads to different decision makers acting on asymmetric information sets, introduces the need for coordination between them, and perhaps not surprisingly makes the resulting optimal control problem much harder to solve. In fact, shortly after such questions were posed, it was realized that seemingly simple decentralized optimal control problems are computationally intractable to solve, with the Wistenhausen counterexample being a famous instance of this phenomenon. Spurred on by this perhaps discouraging result, a concerted 40 year effort to identify tractable classes of distributed optimal control problems culminated in the notion of quadratic invariance, which loosely states that if sub-controllers can exchange information with each other at least as quickly as the effect of their control actions propagates through the plant, then the resulting distributed optimal control problem admits a convex formulation.

The identification of quadratic invariance as an appropriate means of "convexifying" distributed optimal control problems led to a renewed enthusiasm in the controller synthesis community, resulting in a rich set of results over the past decade. The contributions of this thesis can be seen as being a part of this broader family of results, with a particular focus on closing the gap between theory and practice by relaxing or removing assumptions made in the traditional distributed optimal control framework. Our contributions are to the foundational theory of distributed optimal control, and fall under three broad categories, namely controller synthesis, architecture design and system identification.

We begin by providing two novel controller synthesis algorithms. The first is a solution to the distributed H-infinity optimal control problem subject to delay constraints, and provides the only known exact characterization of delay-constrained distributed controllers satisfying an H-infinity norm bound. The second is an explicit dynamic programming solution to a two player LQR state-feedback problem with varying delays. Accommodating varying delays represents an important first step in combining distributed optimal control theory with the area of Networked Control Systems that considers lossy channels in the feedback loop. Our next set of results are concerned with controller architecture design. When designing controllers for large-scale systems, the architectural aspects of the controller such as the placement of actuators, sensors, and the communication links between them can no longer be taken as given -- indeed the task of designing this architecture is now as important as the design of the control laws themselves. To address this task, we formulate the Regularization for Design (RFD) framework, which is a unifying computationally tractable approach, based on the model matching framework and atomic norm regularization, for the simultaneous co-design of a structured optimal controller and the architecture needed to implement it. Our final result is a contribution to distributed system identification. Traditional system identification techniques such as subspace identification are not computationally scalable, and destroy rather than leverage any a priori information about the system's interconnection structure. We argue that in the context of system identification, an essential building block of any scalable algorithm is the ability to estimate local dynamics within a large interconnected system. To that end we propose a promising heuristic for identifying the dynamics of a subsystem that is still connected to a large system. We exploit the fact that the transfer function of the local dynamics is low-order, but full-rank, while the transfer function of the global dynamics is high-order, but low-rank, to formulate this separation task as a nuclear norm minimization problem. Finally, we conclude with a brief discussion of future research directions, with a particular emphasis on how to incorporate the results of this thesis, and those of optimal control theory in general, into a broader theory of dynamics, control and optimization in layered architectures.