Development and Evaluation of Speed Harmonization using Optimal Control Theory: A Simulation-Based Case Study at a Speed Reduction Zone
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Connected and automated vehicles↗
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Multi-Objective Optimal Control of the 6-DoF Aeroservoelastic Common Research Model with Aspect Ratio 13.5 Wing
A new 6-DoF aeroservoelastic (ASE) Common Research Model (CRM) provided by The Boeing Company with aspect ratio 13.5 and 17 control surfaces per wing is utilized to demonstrate combined tracking and optimal multi-objective control. The multi-objective controller is derived on the closed loop tracking controller, and utilizes state and gust estimates provided by an extended state observer. Various methods of model reduction useful for control and estimation are presented. A computationally efficient MATLAB/Simulink simulation is presented which includes actuator dynamics, rate and deflection saturation limits, and gust disturbance inputs. The platform is used to demonstrate excellent 6-DoF tracking control performance coupled with the multi-objective controller, which is shown to effectively reduce structural mode movement, wing root bending moment, and drag. State and gust estimation is also shown to perform well, even when derived and/or implemented with significantly fewer states than the original full-sized model.
Drew, Michael C.↗
Power Optimal Control Allocation for Distributed Electric Propulsion in a Series/Parallel Hybrid Powertrain
This paper describes a thrust allocation scheme that minimizes power consumption in an electrified powertrain with Distributed Electric Propulsion. It takes advantage of an observation about component efficiency maps, that efficiency is often highest at high torque/high speed conditions. This optimal approach is demonstrated to satisfy total thrust and net yaw axis torque requirements, making it suitable for utilizing differential thrust for maneuvering.
electrified aircraft propulsion↗
Power Optimal Control Allocation for Distributed Electric Propulsion in a Series/Parallel Hybrid Powertrain
This paper describes a thrust allocation scheme that minimizes power consumption in an electrified powertrain with Distributed Electric Propulsion. It takes advantage of an observation about component efficiency maps, that efficiency is often highest at high torque/high speed conditions. This optimal approach is demonstrated to satisfy total thrust and net yaw axis torque requirements, making it suitable for utilizing differential thrust for maneuvering.
electrified aircraft propulsion↗
Power Optimal Control Allocation for Distributed Electric Propulsion in a Series/Parallel Hybrid Powertrain
This paper describes a thrust allocation scheme that minimizes power consumption in an electrified powertrain with Distributed Electric Propulsion. It takes advantage of an observation about component efficiency maps, that efficiency is often highest at high torque/high speed conditions. This optimal approach is demonstrated to satisfy total thrust and net yaw axis torque requirements, making it suitable for utilizing differential thrust for maneuvering.
electrified aircraft propulsion↗
An optimal controller for an electric ventricular-assist device: theory, implementation, and testing
This paper addresses the development and testing of an optimal position feedback controller for the Penn State electric ventricular-assist device (EVAD). The control law is designed to minimize the expected value of the EVAD's power consumption for a targeted patient population. The closed-loop control law is implemented on an Intel 8096 microprocessor and in vitro test runs show that this controller improves the EVAD's efficiency by 15-21%, when compared with the performance of the currently used feedforward control scheme.
Therapy, Computer-Assisted/standards↗
Analysis of the Effect of Vehicle Platooning on the Optimal Control of a Heavy Duty Engine Thermal System
One promising method for reducing fuel consumption and emissions, particularly in heavy duty trucks, is platooning. As the distance between vehicles decreases, the following vehicles will experience less aerodynamic drag on the front of the vehicle. However, reducing the velocity of the air contacting the front of the vehicle could have adverse effects on the temperature of the engine. To compensate for this effect, the energy consumption of the engine cooling system might increase, ultimately limiting the overall improvements obtained with platooning. Understanding the coupling between drag reduction and engine cooling load requirement is key for successfully implementing platooning strategies. Additionally, in a Connected and Automated Vehicle (CAV) environment, where information of the future engine load becomes available, the operation of the cooling system can be optimized in order to achieve the maximum fuel consumption reduction. In this paper, a control-oriented physics-based model for the engine cooling loop of a Volvo engine is developed and validated against road data. Starting from the validated model, an optimal control problem for the coolant system is formulated considering the tradeoff between the tracking of the engine temperature setpoint and the corresponding fuel consumption under different trailing distances. To compare the coolant system performance, Dynamic Programming (DP) is used to determine the global optimal solution for the coolant system actuator. The coupling between optimal cooling system operation and reduction in ram air are evaluated by comparing the results obtained from the DP under different platooning conditions against the unrestricted scenario. In addition, the paper analyzes the changes in the tradeoff between fuel consumption and setpoint tracking for different vehicle distances. This analysis will provide useful insight on the sensitivity of the coolant system controller calibration to the platoon distance.
32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
Qudit Entanglers Using Quantum Optimal Control
Not Available
71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
Learning error distribution kernel‐enhanced neural network methodology for multi‐intersection signal control optimization
Traffic congestion has substantially induced significant mobility and energy inefficiency. Many research challenges are identified in traffic signal control and management associated with artificial intelligence (AI)-based models. For example, developing AI-driven dynamic traffic system models that accurately capture high-resolution traffic attributes and formulate robust control algorithms for traffic signal optimization is difficult. Additionally, uncertainties in traffic system modeling and control processes can further complicate traffic signal system controllability. To partially address these challenges, this study presents a novel, hybrid neural network model enhanced with a probability density function kernel shaping technique to formulate traffic system dynamics better and improve comprehensive traffic network modeling and control. The numerical experimental tests were conducted, and the results demonstrate that the proposed control approach outperforms the baseline control strategies and reduces overall average delays by 11.64% on average. By leveraging the capabilities of this innovative model, this study aims to address major challenges related to traffic congestion and energy inefficiency toward more effective and adaptable AI-based traffic control systems.
Wang, Hong [Oak Ridge National Laboratory (ORNL), ↗
TRAVOLTA: GPU acceleration and algorithmic improvements for constructing quantum optimal control fields in photo-excited systems
Not Available
97 MATHEMATICS AND COMPUTING↗
Application of the SDC optimal control algorithm to low-thrust escape and capture including fourth body effects
An application of the new optimization algorithm called Static/Dynamic Control (SDC) to design low-thrust escape and capture trajectories is presented.
low-thrust optimization escape capture↗
Simultaneous control of the electron temperature and safety factor profiles in DIII-D using model-based optimal control techniques
Future tokamak power plants will likely operate using a single, well-defined plasma scenario, either in steady state or for very long pulse lengths. In order to enhance the robustness of the scenario, feedback controllers for a variety of plasma properties will be necessary to counteract any disturbances and ensure safe operation. However, only a limited set of actuators will be available to control many different quantities. Because of this, it is necessary to develop controllers that are able to regulate multiple plasma properties using a limited set of actuators. To this end, a controller has been developed for the simultaneous regulation of both the electron temperature and safety factor profiles in DIII-D. This algorithm uses a linear quadratic integral control synthesis approach based on a linearized model of the dynamics of the two profiles. Two neural network surrogate models, NubeamNet and MMMnet, are included to improve the fidelity of the model. Furthermore, the controller has been tested in simulation using COTSIM, and has demonstrated the ability to simultaneously track changes in both the electron temperature and safety factor targets, including changes in both the magnitude and the shape of the profiles.
70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
Wave forecast and its application to the optimal control of offshore floating wind turbine for load mitigation
Control algorithms play an important role in energy capture and load mitigation for offshore floating wind turbines (OFWTs). One of the advanced and effective control techniques is the feedforward or model predictive control approach, which requires the forecast of incoming environment conditions. For OFWTs, wave loading is one of the dominant sources to excite structural responses. This study is thus motivated to develop forecasting algorithms for wave elevations and wave excitation forces with the purpose of applying feedforward controllers on OFWTs. Two forecasting algorithms, the approximate Prony Method based on ESPRIT (Estimation of Signal Parameters via Rotational Invariance Techniques) and SVM (Support Vector Machine) regression, are developed and validated using wave records from tank tests. Utilizing the forecasted wave elevations and wave excitation forces, a feedforward LQR controller is designed to mitigate structural loads of an OFWT system.
17 WIND ENERGY↗
A procedure for optimal control of flexible surface vibrations
The vibration controller design for a thin flexible surface with a given boundary is formulated as an unconstrained optimization problem. It is shown that this formulation is equivalent to a system of uncoupled optimization problems each of which is a linear regulator design problem for a second-order modal system. The regulator solutions give the gains on the modal amplitude and velocity associated with each modal system. For the constrained control case corresponding to a finite number of actuators, an approximation to the optimal distributed control is given. For the case of a limited number of physical sensors, a dual approach yields a system of second-order observers or filters. Simulations indicate that the constrained controller has a satisfactory performance as long as the number of actuators is more than half the number of controlled modes.
Caglayan, A. K.↗
Optimal control of linear stochastic systems with measurement errors
Statistical feedback optimization of linear stochastic systems with measurement errors
Deyst, J. J., Jr.↗
Halo Orbit Mission Correction Maneuvers Using Optimal Control
This paper addresses the computation of the required trajectory correction maneuvers (TCM) for a halo orbit space mission to compensate for the launch velocity errors introduced by inaccuracies of the launch vehicle.
Halo Orbit trajectory error correction optimal con↗
A Singular Differential Equation Stemming from an Optimal Control Problem in Financial Economics
We consider the ordinary differential equation <##> } x 2 u ″ = a x u ′ + b u −<!-- ??? --> c } }( u ′ −<!-- ??? --> 1 } }) 2 , x ∈<!-- ??? --> }( 0 , x 0 }) , $$ x^2 u''=axu'+bu-c /bigl(u'-1/bigr)^2, /quad x/in(0,x{sub 0}), $$ x{sup 2}u{sup ″}=axu{sup ′}+bu−c(u{sup ′}−1){sup 2}, x∈(0,x{sub 0}), </##> with <##> } a ∈<!-- ??? --> } }R , b ∈<!-- ??? --> } }R $ a/in/mathbb{R}, b/in/mathbb{R} $ a∈R,b∈R </##>, c>0 and the singular initial condition u(0)=0, which in financial economics describes optimal disposal of an asset in a market with liquidity effects. It is shown in the paper that if a+b<0 then no continuous solutions exist, whereas if a+b>0 then there are infinitely many continuous solutions with indistinguishable asymptotics near 0. Moreover, it is proved that in the latter case there is precisely one solution u corresponding to the choice x{sub 0}=∞ which is such that 0≤u(x)≤x for all x>0, and that this solution is strictly increasing and concave.
71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗