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This paper demonstrates continuous optimization on the differentiable manifold formed by continuous constraint functions. The first order tensor geodesic differential equation is solved on the manifold in both numerical and closed analytic form for simple nonlinear programs. Advantages and disadvantages with respect to conventional optimization techniques are discussed.
We present a differentiable predictive control (DPC) methodology for learning constrained control laws for unknown nonlinear systems. DPC poses an approximate solution to multiparametric programming problems emerging from explicit nonlinear model predictive control (MPC). Contrary to approximate MPC, DPC does not require supervision by an expert controller. Instead, a system dynamics model is learned from a small dataset of recorded observations of the perturbed system's dynamics and the control law is optimized offline by interaction with the learned system model. The DPC method is based on two sequential steps, i) system identification using a constrained neural state-space model, and ii) optimization of an explicit control law parametrized by another neural network in closed-loop simulation with the identified neural state-space model. The combination of a differentiable closed-loop system and penalty methods for constraint handling of system outputs and inputs allows us to optimize the control law's parameters directly by backpropagating economic MPC loss through the learned system model. By incorporating domain knowledge and leveraging established techniques from optimal control, our method leverages deep neural networks as nonlinear function approximators for system identification and control while avoiding concomitant costs of intractably large datasets, and computationally expensive over-parametrized models. The scalability, data efficiency, and constrained optimal control capability of the proposed DPC method are demonstrated in simulation using a multi-zone building emulator.
Abstract A general framework to derive nonlinear elastic and elastoplastic material models from granular micromechanics is proposed, where a constraint‐based variational structure is introduced to classical grain contact‐based homogenization methods of hyperelasticity. Like the classical hyperelastic methods, reference solutions for closed‐form hyperelastic material models are analytically derived from the grain‐scale contact mechanics. However, unlike prior methods, the proposed homogenization framework defines closed‐form hyperelastoplastic material models that extend multiscale variational methods to granular plasticity. The proposed framework is used to develop novel granular micromechanics‐based macroscopic models for a Mises type solid, Drucker–Prager type plasticity, and grain‐contact cohesive‐debonding with a deviatorically and volumetrically coupled nonlinearly elastic response. Macroscopic plastic parameters and yield criteria are explicitly related to their microscale counterparts, for example, the friction coefficient governing intergranular slip. Numerical examples and comparison to measurements from the literature, including triaxial compaction of concrete, are provided to investigate model predictions and demonstrate calibration to experimental data.
A GPU-accelerated optical frequency domain reflectometry (OFDR) system with an improved integrated auxiliary interferometer is proposed. Unlike conventional approaches that require separate auxiliary interferometers and multiple detection channels, the proposed OFDR system embeds this functionality directly into the signal via an intentional beat component. This enables self-calibration of laser nonlinearity while maintaining a cost-effective hardware configuration. Building on this simplified configuration, the system leverages GPU acceleration with an NVIDIA RTX 4070 Ti to achieve real-time performance, delivering high-throughput signal processing for continuous OFDR interrogation. The signal processing pipeline comprises signal capture, resampling for nonlinearity compensation, and frequency shift computation, all optimized for parallel execution. Hardware benchmarking demonstrates substantial acceleration over CPU implementations, achieving up to a 45× speedup for resampling and frequency shift computations and enabling processing latencies below 30 ms. Thermal response validation is conducted under two complementary scenarios: localized heating using a water bath and cryogenic-temperature conditions using liquid nitrogen. Under localized heating, the system achieves an accuracy of 0.249 °C with a thermal sensitivity of 5.971 GHz/°C, while cryogenic-temperature validation demonstrates a frequency shift response with a sensitivity of 2.383 GHz/°C and an accuracy of 2.04 °C. The high acceleration of the proposed GPU-accelerated OFDR system and its accuracy are achieved by exploiting CUDA-based stride indexing, enabling efficient parallel segmentation and processing of large datasets without additional memory copies. The benchmarking results confirm the robustness, accuracy, and deployability of the proposed OFDR system across a wide temperature range, establishing it as a practical platform for real-time distributed fiber sensing in structurally dynamic environments.
Microwave phononics is a promising platform for sensing, computing, and quantum information science; thus, sensitive and high-throughput characterization tools are needed not only for device verification and optimization but also for revealing transient and nonlinear dynamics. Existing interferometric optical vibrometers for 2D mapping are challenged by operating point stabilization, surface reflectivity contrast, and long acquisition time. Here, we use spectral interferometry, which is insensitive to these factors and utilizes a continuous raster scanning scheme for vibration mapping with high throughput. We intensity-modulate our broadband light source with an electro-optic modulator to resolve vibrations at microwave frequencies. Our system requires no fast photodetector or digitizer operating in the microwave frequency range. We image the 1 GHz vibration field of a 300 × 150 µm 2 area of an entire surface acoustic wave device in 10 min with simultaneous surface profilometry. Our system has a vibration sensitivity of 120 fm/sqrt(Hz) and a linear throughput of 0.77 mm/s on the chip surface. The technique offers capabilities for characterizing a wide range of acoustic wave and micromechanical devices to better understand their behavior and performance.
Monograph on estimation and optimal control with quantized measurements covering linear, nonlinear and time varying systems
Book on theory of optimal control and mathematical programming covering linear, nonlinear, quadratic programmings, etc
The paper discusses dynamic analyses and testing of aerospace vehicles and the application of such analyses and testing to nonaerospace fields. Items covered in the section on dynamic analyses of aerospace vehicles include self-induced and forced oscillatory loads, approaches to dynamic modeling and analysis, nonlinear analyses, and integrated dynamics design and optimization. Items covered in the section on the dynamic testing of aerospace vehicles include integrated test philosophy, test facilities, and ways of improving performance and reducing costs. The nonaerospace applications that are discussed include ground and water transportation, medicine, and nuclear power plants.
The present quantitative approach to the problem of reconfiguring a degradable multimode system assigns some modules to computation and arranges others for reliability. By using expected total reward as the optimal criterion, there emerges an active reconfiguration strategy based not only on the occurrence of failure but the progression of the given mission. This reconfiguration strategy requires specification of the times at which the system should undergo reconfiguration, and the configurations to which the system should change. The optimal reconfiguration problem is converted to integer nonlinear knapsack and fractional programming problems.
The problem of minimization of fuel consumption during the atmospheric portion of an aeroassisted, orbital transfer with plane change is addressed. The complete mission has required three characteristic velocities, a deorbit impulse at high earth orbit (HEO), a boost impulse at the atmospheric exit, and a reorbit impulse at low earth orbit (LEO). A performance index has been formulated as the sum of these three impulses. Application of optimal control principles has led to a nonlinear, two-point, boundary value problem which was solved by using a multiple shooting algorithm. The strategy for the atmospheric portion of the minimum-fuel transfer is to start initially with the maximum positive lift in order to recover from the downward plunge, and then to fly with a gradually decreasing lift such that the vehicle skips out of the atmosphere with a flight path angle near zero degrees.
The problem of minimization of fuel consumption during the atmospheric portion of an aeroassisted, orbital transfer with plane change is addressed. The complete mission has required three characteristic velocities, a deorbit impulse at high earth orbit (HEO), a boost impulse at the atmospheric exit, and a reorbit impulse at low earth orbit (LEO). A performance index has been formulated as the sum of these three impulses. Application of optimal control principles has led to a nonlinear, two-point, boundary value problem which was solved by using a multiple shooting algorithm. The strategy for the atmospheric portion of the minimum-fuel transfer is to start initially with the maximum positive lift in order to recover from the downward plunge, and then to fly with a gradually decreasing lift such that the vehicle skips out of the atmosphere with a flight path angle near zero degrees.
Some authors take a classical approach to the simultaneous structure/control optimization by attempting to simultaneously minimize the weighted sum of the total mass and a quadratic form, subject to all of the structural and control constraints. Here, the optimization will be based on the dynamic response of a structure to an external unknown stochastic disturbance environment. Such a response to excitation approach is common to both the structural and control design phases, and hence represents a more natural control/structure optimization strategy than relying on artificial and vague control penalties. The design objective is to find the structure and controller of minimum mass such that all the prescribed constraints are satisfied. Two alternative solution algorithms are presented which have been applied to this problem. Each algorithm handles the optimization strategy and the imposition of the nonlinear constraints in a different manner. Two controller methodologies, and their effect on the solution algorithm, will be considered. These are full state feedback and direct output feedback, although the problem formulation is not restricted solely to these forms of controller. In fact, although full state feedback is a popular choice among researchers in this field (for reasons that will become apparent), its practical application is severely limited. The controller/structure interaction is inserted by the imposition of appropriate closed-loop constraints, such as closed-loop output response and control effort constraints. Numerical results will be obtained for a representative flexible structure model to illustrate the effectiveness of the solution algorithms.
A theoretical comparison of various low and high order multipliers for 200 GHz and 1 THz has been carried out. Novel diodes including single barrier varactors, barrier-intrinsic-n(+)diodes and high electron mobility varactors are shown to have excellent theoretical performance, comparable or better than the conventional Schottky varactors for single and double diode frequency multipliers at millimeter and submillimeter wavelengths, whereas quantum well diodes, since they suffer from high resistive losses, are shown to be less attractive. In comparison to the conventional Schottky varactor, these new diodes have some potential advantages in their characteristics such as a stronger nonlinearity or a special symmetry. For future optimization some general comments on these advantages as well as other factors affecting multiplication are given.
A method for modeling discontinuities in a coaxial transmission line is presented. The methodology involves the use of a nonlinear least-squares fit program to optimize the fit between theoretical data (from the model) and experimental data. When this method was applied to modeling discontinuities in a slightly damaged Galileo spacecraft S-band (2.295-GHz) antenna cable, excellent agreement between theory and experiment was obtained over a frequency range of 1.70-2.85 GHz. The same technique can be applied for diagnostics and locating unknown discontinuities in other types of microwave transmission lines, such as rectangular, circular, and beam waveguides.
A method is presented to integrate the design space of structural/control system optimization problems in the case of linear state feedback control. Conventional structural sizing variables and elements of the feedback gain matrix are both treated as strictly independent design variables in optimization by extending design variable linking concepts to the control gains. Several approximation concepts including new control design variable linking schemes are used to formulate the integrated structural/control optimization problem as a sequence of explicit nonlinear mathematical programming problems. Examples which involve a variety of behavior constraints, including constraints on dynamic stability, damped frequencies, control effort, peak transient displacement, acceleration, and control force limits, are effectively solved by using the method presented.
A major goal in the control of complex mechanical system such as spacecraft rocket engine's advanced aircraft, and power plants is to achieve high performance with increased reliability, component durability, and maintainability. The current practice of decision and control systems synthesis focuses on improving performance and diagnostic capabilities under constraints that often do not adequately represent the materials degradation. In view of the high performance requirements of the system and availability of improved materials, the lack of appropriate knowledge about the properties of these materials will lead to either less than achievable performance due to overly conservative design, or over-straining of the structure leading to unexpected failures and drastic reduction of the service life. The key idea in this report is that a significant improvement in service life could be achieved by a small reduction in the system dynamic performance. The major task is to characterize the damage generation process, and then utilize this information in a mathematical form to synthesize a control law that would meet the system requirements and simultaneously satisfy the constraints that are imposed by the material and structural properties of the critical components. The concept of damage mitigation is introduced for control of mechanical systems to achieve high performance with a prolonged life span. A model of fatigue damage dynamics is formulated in the continuous-time setting, instead of a cycle-based representation, for direct application to control systems synthesis. An optimal control policy is then formulated via nonlinear programming under specified constraints of the damage rate and accumulated damage. The results of simulation experiments for the transient upthrust of a bipropellant rocket engine are presented to demonstrate efficacy of the damage-mitigating control concept.
Optimal extraction of pulses of constant known shape from a time series with stationary noise is well understood and widely used in detection applications. Applications where high resolution is required over a wide range of input signal amplitudes use much of the dynamic range of the sensor. The noise will in general vary over this signal range, and the response may be a nonlinear function of the energy input. We present an optimal least squares procedure for inferring input energy in such a detector with nonstationary noise and nonlinear energy response.
A testing procedure was used in a 16-foot Transonic Propulsion Wind Tunnel which leads to optimum wing airfoil sections without stopping the tunnel for model changes. Being experimental, the optimum shapes obtained incorporate various three-dimensional and nonlinear viscous and transonic effects not included in analytical optimization methods. The method is a closed-loop, computer-controlled, interactive procedure and employs a Self-Optimizing Flexible Technology wing semispan model that conformally adapts the airfoil section at two spanwise control stations to maximize or minimize various prescribed merit functions subject to both equality and inequality constraints. The model, which employed twelve independent hydraulic actuator systems and flexible skins, was also used for conventional testing. Although six of seven optimizations attempted were at least partially convergent, further improvements in model skin smoothness and hydraulic reliability are required to make the technique fully operational.