Structural tailoring and feedback control synthesis - An interdisciplinary approach
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Abstract not provided.
This disclosure concerns a method for making a hybrid organic/inorganic material having an architecture. The method includes combining a peptoid comprising a sequence of N-substituted glycine residues and an inorganic material or inorganic material precursor to form a hybrid organic/inorganic material comprising the peptoid and the inorganic material, the hybrid organic/inorganic material having an architecture based at least in part on the peptoid sequence. The hybrid organic/inorganic materials include a cluster of nanoparticles of an inorganic material and peptoids, the cluster formed by random attachment of nanoparticles to one another by peptoid-peptoid and peptoid-nanoparticle surface interactions, wherein the hybrid material has an architecture based at least in part on the peptoid sequence.
Synthesis of optimal controls for linear problems with retarded controls
Synthesis of optimal controls for linear systems with retarded controls
Substructure synthesis from a controls perspective is considered. An efficient and computationally robust method for synthesis of substructures is developed. The method considers the interface forces/moments as control inputs and redefines the synthesis problem in terms of obtaining a constant gain compensator which would ensure the connectivity requirements of the combined structure. Orthogonal similarity transformations are used to provide simplified synthesized dynamics of the combined system. The simplicity of form in transformed coordinates are exploited to effectively deal with modeling parametric and non-parametric uncertainties at substructure level. Uncertainty models of reasonable size and complexity are derived for the combined structure from those in the substructure models.
Adrenal medulla biochemistry and morphology, discussing epinephrine synthesis control by glucocorticoid hormones
Pontryagin optimal principle applied to minimum fuel satellite attitude control with two feedback controls
Using automatic control theory with simple pilot model for synthesizing helicopter landing approach flight director control laws
The choice of temperature and gas conditions used in a water pressure-controlled reactor is guided by density functional theory (DFT) to synthesize nearly phase pure lanthanide scandate nanoparticles (LnScO 3 , Ln = La, Nd, Sm, Gd). In this synthetic method, low water vapor partial pressures, well below water’s gas liquidus, inhibit particle growth, while an excess of water vapor results in undesired rare earth hydroxide and oxyhydroxide secondary phases. The optimal humidity for high-purity LnScO 3 particle synthesis is shown to vary with the lanthanide; DFT is used to calculate the thermodynamics of secondary phase formation for each lanthanide tested, such that the role of water vapor may be quantified and used to maintain phase purity (greater than 96 mol%) across the series. Furthermore, the combination of thermodynamic calculation and experimental confirmation with this pressure-controlled reactor provides an opportunity to explore analogous syntheses of other inorganic perovskite nanoparticles.
The problem of control systems synthesis is considered for controlling the rigid-body attitude and elastic motion of a large deployable space-based antenna. Two methods for control systems synthesis are considered. The first method utilizes the stability and robustness properties of the controller consisting of torque actuators and collocated attitude and rate sensors. The second method is based on the linear-quadratic-Gaussian (LQG) control theory. A combination of the two methods, which results in a two-level hierarchical control system, is also briefly discussed. The performance of the controllers is analyzed by computing the variances of pointing errors, feed misalignment errors and surface contour errors in the presence of sensor and actuator noise.
This paper describes the software design patterns and vehicle interfaces that were employed to transition vehicle controllers from simulation environments to open-road field experiments. The approach relies on a life cycle that utilizes model-based design and code generation, along with agile software development, and both software and hardware-in-the-loop testing, with additional safety margins. Autonomous designs should consider the dynamics of mixed autonomy in traffic to safely operate among humans. The software that provides a vehicle’s behavior intelligence is often developed through simulation, which may have a mismatch between dynamics, or as a result of a reinforcement learning workflow, which may be a black box with challenges to analyze. In each of these cases, it is important to have research interfaces that provide strongly typed data streams accessible to researchers who are not software experts while continuing to satisfy safety and liveness constraints. This paper describes how we design the hardware platform interfaces and software design process for a mixed autonomy traffic experiment with a leader-follower scenario. Controller synthesis for these vehicles requires clearly articulated vehicle interfaces and software design patterns for successful onboard deployment. Testing strategies for such controllers are also described before algorithms are transitioned to full-scale field experiments with safety operators for the vehicles. Testing strategies include software-in-the-loop simulation testing, hardware-in-the-loop simulation, ghost-car testing, and read-only testing in live traffic. With our approach, we were not only able to validate our controller synthesized in scripts and simulation, but also able to scale deployment to multiple vehicles.
A paradigm for control law design for modern engineering systems is proposed: Minimize control law complexity subject to the achievement of a specified accuracy in the face of a specified level of uncertainty. Correspondingly, the overall goal is to make progress towards the development of a control law design methodology which supports this paradigm. Researchers achieve this goal by developing a general theory of optimal constrained-structure dynamic output feedback compensation, where here constrained-structure means that the dynamic-structure (e.g., dynamic order, pole locations, zero locations, etc.) of the output feedback compensation is constrained in some way. By applying this theory in an innovative fashion, where here the indicated iteration occurs over the choice of the compensator dynamic-structure, the paradigm stated above can, in principle, be realized. The optimal constrained-structure dynamic output feedback problem is formulated in general terms. An elegant method for reducing optimal constrained-structure dynamic output feedback problems to optimal static output feedback problems is then developed. This reduction procedure makes use of star products, linear fractional transformations, and linear fractional decompositions, and yields as a byproduct a complete characterization of the class of optimal constrained-structure dynamic output feedback problems which can be reduced to optimal static output feedback problems. Issues such as operational/physical constraints, operating-point variations, and processor throughput/memory limitations are considered, and it is shown how anti-windup/bumpless transfer, gain-scheduling, and digital processor implementation can be facilitated by constraining the controller dynamic-structure in an appropriate fashion.
Development of digital robust control laws for active control of high performance flexible aircraft and large space structures is a research area of significant practical importance. The flexible system is typically modeled by a large order state space system of equations in order to accurately represent the dynamics. The active control law must satisy multiple conflicting design requirements and maintain certain stability margins, yet should be simple enough to be implementable on an onboard digital computer. Described here is an application of a generic digital control law synthesis procedure for such a system, using optimal control theory and constrained optimization technique. A linear quadratic Gaussian type cost function is minimized by updating the free parameters of the digital control law, while trying to satisfy a set of constraints on the design loads, responses and stability margins. Analytical expressions for the gradients of the cost function and the constraints with respect to the control law design variables are used to facilitate rapid numerical convergence. These gradients can be used for sensitivity study and may be integrated into a simultaneous structure and control optimization scheme.
Lyapunov control system synthesis of highly resonant plant