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The paper discusses an identification problem in which a basic feedback control structure, or pilot control strategy, is hypothesized. Identification algorithms are employed to determine the particular form of pilot equalization in each feedback loop. It was found that both frequency- and time-domain identification techniques provide useful information.
For any fault-tolerant control method to take effect, sufficient redundancy must exist in the plant (process) to be controlled. This paper is intended to establish a means of measuring the level of redundancy in connection with feedback control by borrowing the notion of the second-order modes. In particular, it is assumed that foreseeable faults of a process are parameterized in the model of the process. The smallest second-order mode is used as a measure of the potentiality of the process to maintain a certain performance through control reconfiguration at the occurrence of the worst faults over a prescribed set in the fault parameter space. This measure is called by the authors a control reconfigurability. The control reconfigurability is calculated for two process models to show its relevance to redundant actuating capabilities in the models.
An electrified vehicle has a battery pack comprising series-connected battery units providing a main voltage. To supply a lower voltage bus equally from all battery units, a plurality of DC/DC converters are powered by respective units and have their outputs in parallel. A central module has an outer loop controller generating a target current to regulate the bus voltage to a predetermined voltage and has an allocator distributing the target current into a plurality of allocated current commands according to respective states of charge of the battery units. A plurality of local controllers each adjusts a current of a respective DC/DC converter. Each local controller receives a respective allocated current command as a respective feedforward control variable. Each local controller uses an error between the bus voltage and the predetermined voltage to be integrated as a respective feedback control variable only when the error is above a threshold.
This paper describes the design of data acquisition system (DAQ) that is connected to a PC and development of a feedback control system that maintains the coolant temperature of the process at a desired set point using a digital controller system based on the graphical programming language. The paper will provide details about the data acquisition unit, shows the implementation of the controller, and present test results. (authors)
The development of a remotely piloted vehicle system consisting of a remote pilot cockpit and a ground-based digital computer coupled to the aircraft through telemetry data links is described. The feedback control laws are implemented in a FORTRAN program. Flight-test experience involving high feedback gain limits for attitude and attitude rate feedback variables, filtering of sampled data, and system operation during intermittent telemetry data link loss is discussed. Comparisons of closed-loop flight tests with analytical calculations, and pilot comments on system operation are included.
A planar model of a space base and one module is considered. For this simplified system, a feedback controller which is compatible with the modular construction method is described. The systems dynamics are decomposed into two parts corresponding to base and module. The information structure of the problem is non-classical in that not all system information is supplied to each controller. The base controller is designed to accommodate structural changes that occur as the module is added and the module controller is designed to regulate its own states and follow commands from the base. Overall stability of the system is checked by Liapunov analysis and controller effectiveness is verified by computer simulation.
Finite dimensional approximation schemes that work well for distributed parameter systems are often not suitable for the analysis and implementation of feedback control systems. The relationship between approximation schemes for distributed parameter systems and their application to optimal control problems is discussed. A numerical example is given.
Partially constructed/assembled structures in space are complicated enough but their dynamics will also be operating in closed-loop with feedback controllers. The dynamics of such structures are modeled by large-scale finite element models. The model dimension L is extremely large (approximately 10,000) while the numbers of actuators (M) and sensors (P) are small. The model parameters M(sub m) mass matrix, D(sub o) damping matrix, and K(sub o) stiffness matrix, are all symmetric and sparse (banded). Thus simulation of open-loop structure models of very large dimension can be accomplished by special integration techniques for sparse matrices. The problem of simulation of closed-loop control of such structures is complicated by the addition of controllers. Simulation of closed-loop controlled structures is an essential part of the controller design and evaluation process. Current research in the following areas is presented: high-order simulation of actively controlled aerospace structures; low-order controller design and SCI compensation for unmodeled dynamics; prediction of closed-loop stability using asymptotic eigenvalue series; and flexible robot manipulator control experiment.
Data-based predictive control is an emerging control method that stems from Model Predictive Control (MPC). MPC computes current control action based on a prediction of the system output a number of time steps into the future and is generally derived from a known model of the system. Data-based predictive control has the advantage of deriving predictive models and controller gains from input-output data. Thus, a controller can be designed from the outputs of complex simulation code or a physical system where no explicit model exists. If the output data happens to be corrupted by periodic disturbances, the designed controller will also have the built-in ability to reject these disturbances without the need to know them. When data-based predictive control is implemented online, it becomes a version of adaptive control. One challenge of MPC is computational requirements increasing with prediction horizon length. This paper develops a closed-loop dynamic output feedback controller that minimizes a multi-step-ahead receding-horizon cost function with multirate prediction step. One result is a reduced influence of prediction horizon and the number of system outputs on the computational requirements of the controller. Another result is an emphasis on portions of the prediction window that are sampled more frequently. A third result is the ability to include more outputs in the feedback path than in the cost function.
This work explores the application of the recently developed Koopman operator approach for model identification and feedback control of a hydraulic fracturing process. Controlling fracture propagation and proppant transport with precision is a challenge due in large part to the difficulty of constructing approximate models that accurately capture the characteristic moving boundary and highly-coupled dynamics exhibited by the process. Koopman operator theory is particularly attractive here as it offers a way to explicitly construct linear representations for even highly nonlinear dynamics. The method is data-driven and relies on lifting the states to an infinite-dimensional space of functions called observables where the dynamics are governed by a linear Koopman operator. Here this work considers two problems: (a) fracture geometry control, and (b) proppant concentration control. In both cases, an approximate linear model of the corresponding dynamics is constructed and used to design a model predictive controller (MPC). The manuscript shows that in the case of highly nonlinear dynamics, as observed in the proppant concentration, use of canonical functions in the observable basis fails. In such cases, a priori system knowledge can be leveraged to choose the required basis. The numerical experiments demonstrate that the Koopman linear model shows excellent agreement with the real system and successfully achieves the desired target values maximizing the oil and gas productivity. Additionally, due to its linear structure, the Koopman models allow convex MPC formulations that avoid any issues associated with nonlinear optimization.
This article highlights work at Oak Ridge National Laboratory’s Manufacturing Demonstration Facility to develop closed-loop, feedback control for laser-wire based Directed Energy Deposition, a form of metal Big Area Additive Manufacturing (m-BAAM), a process being developed in partnership with GKN Aerospace specifically for the production of Ti-6Al-4V pre-forms for aerospace components. A large-scale structural demonstrator component is presented as a case-study in which not just control, but the entire 3D printing workflow for m-BAAM is discussed in detail, including design principles for large-format metal AM, toolpath generation, parameter development, process control, and system operation, as well as post-print net-shape geometric analysis and finish machining. In terms of control, a multi-sensor approach has been utilized to measure both layer height and melt pool size, and multiple modes of closed-loop control have been developed to manipulate process parameters (laser power, print speed, deposition rate) to control these variables. Layer height control and melt pool size control have yielded excellent local (intralayer) and global (component-level) geometry control, and the impact of melt pool size control in particular on thermal gradients and material properties is the subject of continuing research. Further, these modes of control have allowed the process to advance to higher deposition rates (exceeding 7.5 lb/hr), larger parts (1-meter scale), shorter build times, and higher overall efficiency. The control modes are examined individually, highlighting their development, demonstration, and lessons learned, and it is shown how they operate concurrently to enable the printing of a large-scale, near net shape Ti-6Al-4V component.
This article proposes a system-wide optimal resource dispatch strategy that enables a shift from a primarily energy cost-based approach, to a strategy using simultaneous price signals for energy, power and ramping behavior. A formal method to compute the optimal sub-hourly power trajectory is derived for a system when the price of energy and ramping are both significant. Optimal control functions are obtained in both time and frequency domains, and a discrete-time solution suitable for periodic feedback control systems is presented. The method is applied to North America Western Interconnection for the planning year 2024, and it is shown that an optimal dispatch strategy that simultaneously considers both the cost of energy and the cost of ramping leads to significant cost savings in systems with high levels of renewable generation: the savings exceed 25% of the total system operating cost for a 50% renewables scenario.
We develop and study protocols for deterministic remote entanglement generation using quantum feedback, without relying on an entangling Hamiltonian. In order to formulate the most effective experimentally feasible protocol, we introduce the notion of average-sense locally optimal feedback protocols, which do not require real-time quantum state estimation, a difficult component of real-time quantum feedback control. We use this notion of optimality to construct two protocols that can deterministically create maximal entanglement: a semiclassical feedback protocol for low-efficiency measurements and a quantum feedback protocol for high-efficiency measurements. The latter reduces to direct feedback in the continuous-time limit, whose dynamics can be modeled by a Wiseman-Milburn feedback master equation, which yields an analytic solution in the limit of unit measurement efficiency. Our formalism can smoothly interpolate between continuous-time and discrete-time descriptions of feedback dynamics and we exploit this feature to derive a superior hybrid protocol for arbitrary nonunit measurement efficiency that switches between quantum and semiclassical protocols. Lastly, we show using simulations incorporating experimental imperfections that deterministic entanglement of remote superconducting qubits may be achieved with current technology using the continuous-time feedback protocol alone.
Coherent pulse stacking (CPS) is a new time-domain coherent addition technique that stacks several optical pulses into a single output pulse, enabling high pulse energy from fiber lasers. We develop a robust, scalable, and distributed digital control system with firmware and software integration for algorithms, to support the CPS application. We model CPS as a digital filter in the Z domain and implement a pulse-pattern-based cavity phase detection algorithm on an field-programmable gate array (FPGA). A two-stage (2+1 cavities) 15-pulse stacking system achieves an 11.0 peak-power enhancement factor. Each optical cavity is fed back at 1.5kHz, and stabilized at an individually-prescribed round-trip phase with 0.7deg and 2.1deg rms phase errors for Stages 1 and 2, respectively. Optical cavity phase control with nanometer accuracy ensures 1.2% intensity stability of the stacked pulse over 12 h. The FPGA-based feedback control system can be scaled to large numbers of optical cavities.
The problem of transferring a rocket vehicle from a given circular orbit to a larger coplanar circular orbit in minimum time, using a constant low-thrust rocket engine, is considered. Parameters are chosen to correspond to a transfer from the earth's orbit in heliocentric space to the orbit of Mars. A path satisfying the first order necessary conditions of variational calculus is shown to be locally minimizing by application of a set of second order conditions. A physical explanation is offered to justify the retrothrust period occurring during the flight. A neighboring optimum feedback control law, based on estimated time-to-go, is applied to this problem. State variable and terminal constraint feedback gains are calculated while one of the second order conditions, involving the backward integration of a matrix Riccati equation, is being tested.
Three-Phase Power-Factor Controller develops a control signal for each motor winding. As motor loading decreases, rms value of applied voltage is decreased by feedback-control circuit. Power consumption is therefore lower than in unregulated operation. Controller employs phase detector for each of three phases of delta-connected induction motor. Phase-difference sum is basis for control.
This paper describes a new controller for automatic attitude maneuvers of the Space Shuttle Orbiter. The controller incorporates a new solution algorithm for partially linearized, fuel-optimal maneuvers for RCS jet controlled spacecraft. These solutions provide model trajectories and jet commands that are easily tracked using a feed-forward, feedback controller structure. The result is a substantial performance improvement over the current Orbiter attitude maneuver controller. The paper discusses optimal maneuvers for this type of vehicle, giving detail of the solution algorithm. Closed-loop controller design and implementation is discussed. Detailed performance results are presented.
An approach in which the manipulator inverse is used as a feedforward controller is employed in the adaptive control of manipulators in order to achieve trajectory tracking by the joint angles. The desired trajectory is applied as an input to the feedforward controller, and the controller output is used as the driving torque for the manipulator. An adaptive algorithm obtained from MRAC theory is used to update the controller gains to cope with variations in the manipulator inverse due to changes of the operating point. An adaptive feedback controller and an auxiliary signal enhance closed-loop stability and achieve faster adaptation. Simulation results demonstrate the effectiveness of the proposed control scheme for different reference trajectories, and despite large variations in the payload.