More Like this

1. Performance Optimization and Guidance of a Low-Altitude Skid-to-Turn Vehicle. Part II: Optimal Guidance

   https://doi.org/10.2514/6.2019-0355  

   Dennis, Miriam ; Rao, Anil V. ( January 2019 , 2019 AIAA Guidance, Navigation, and Control Conference, San Diego)

   The problem of guidance and control of an air-to-surface low-altitude skid-to-turn vehicle is considered. The objective is to steer the vehicle to a ground target from an initial state such that the vehicle remains at a constant low altitude for as long as possible and performs a bunt maneuver (negative sensed-acceleration load) rapidly at the end of the trajectory in order to attain terminal target conditions. The vehicle is modeled as a point mass in motion over a flat Earth, and the vehicle is controlled using thrust magnitude, angle of attack, and sideslip angle. The guidance and control problem is posed as a decreasing-horizon optimal control problem and is re-solved numerically at constant guidance cycles. The work described in this paper is the second part of a two-part sequence on trajectory optimization and guidance of a skid-to-turn vehicle. In both cases, the objective is to minimize the time taken by the vehicle to complete a bunt maneuver subject to the following constraints: dynamic, boundary, state, path, and interior-point event constraints. In the second part of this two-part study, a numerical guidance law is employed to re-solve the optimal control problem on a shrinking horizon. An assessment is made as to the time required to re-solve the optimal control problem both in the absence and presence of a time delay, where the time delay is the amount of time required to solve the numerical approximation of the optimal control problem at the start of each guidance cycle. The results of this study identify that in the absence and presence of a time delay, the size of the mesh on subsequent guidance cycles decreases, the time required to solve the reduced-horizon optimal control problem is small compared to the guidance cycle duration time, and the terminal conditions are met with sufficient accuracy. Thus, the results show that the guidance law presented in this paper has the potential to solve optimal control problems in real-time. 

   more » « less
2. Desensitized Trajectory Optimization for Hypersonic Vehicles

   https://doi.org/10.1109/AERO50100.2021.9438511  

   Makkapati, Venkata Ramana ; Ridderhof, Jack ; Tsiotras, Panagiotis ; Hart, Joseph ; van Bloemen Waanders, Bart ( March 2021 , IEEE Aerospace Conference)

   This paper addresses trajectory optimization for hypersonic vehicles under atmospheric and aerodynamic uncertainties using techniques from desensitized optimal control (DOC), wherein open-loop optimal controls are obtained by minimizing the sum of the standard objective function and a first-order penalty on trajectory variations due to parametric uncertainty. The proposed approach is demonstrated via numerical simulations of a minimum-final-time Earth reentry trajectory for an X-33 vehicle with an uncertain atmospheric scale height and drag coefficient. Monte Carlo simulations indicate that dispersions in the final position footprint and the final energy can be significantly reduced without closed-loop control and with little tradeoff in the performance metric set for the trajectory. 

   more » « less
3. Implicit Trajectory Planning for Feedback Linearizable Systems: A Time-varying Optimization Approach

   https://doi.org/10.23919/ACC45564.2020.9147997  

   Zheng, Tianqi ; Simpson-Porco, John ; Mallada, Enrique ( July 2020 , American Control Conference)

   We develop an optimization-based framework for joint real-time trajectory planning and feedback control of feedback-linearizable systems. To achieve this goal, we define a target trajectory as the optimal solution of a time-varying optimization problem. In general, however, such trajectory may not be feasible due to , e.g., nonholonomic constraints. To solve this problem, we design a control law that generates feasible trajectories that asymptotically converge to the target trajectory. More precisely, for systems that are (dynamic) full-state linearizable, the proposed control law implicitly transforms the nonlinear system into an optimization algorithm of sufficiently high order. We prove global exponential convergence to the target trajectory for both the optimization algorithm and the original system. We illustrate the effectiveness of our proposed method on multi-target or multi-agent tracking problems with constraints. 

   more » « less
4. Distributed Unconstrained Optimization with Time-varying Cost Functions

   https://doi.org/10.23919/ECC57647.2023.10178122  

   Esteki, Amir-Salar ; Kia, Solmaz S. ( June 2023 , European Control Conference (ECC))

   This paper proposes a novel solution for the distributed unconstrained optimization problem where the total cost is the summation of time-varying local cost functions of a group networked agents. The objective is to track the optimal trajectory that minimizes the total cost at each time instant. Our approach consists of a two-stage dynamics, where the first one samples the first and second derivatives of the local costs periodically to construct an estimate of the descent direction towards the optimal trajectory, and the second one uses this estimate and a consensus term to drive local states towards the time-varying solution while reaching consensus. The first part is carried out by a weighted average consensus algorithm in the discrete-time framework and the second part is performed with a continuous-time dynamics. Using the Lyapunov stability analysis, an upper bound on the gradient of the total cost is obtained which is asymptotically reached. This bound is characterized by the properties of the local costs. To demonstrate the performance of the proposed method, a numerical example is conducted that studies tuning the algorithm’s parameters and their effects on the convergence of local states to the optimal trajectory. 

   more » « less
5. Control Co-Design Optimization of Spacecraft Trajectory and System for Interplanetary Missions

   https://doi.org/10.2514/1.A35680  

   Harris, Gage W. ; He, Ping ; Abdelkhalik, Ossama O. ( February 2024 , Journal of Spacecraft and Rockets)

   This paper develops a control co-design (CCD) framework to simultaneously optimize the spacecraft’s trajectory and onboard system (rocket engine) and quantify its benefit. An open-loop optimal control problem (two-finite burn Mars missions) is used as the benchmark, and the engine design considers the combustion equilibrium and nozzle geometry. The objective function is the fuel burn. The design variables are the trajectory control parameters (such as burn times, burn directions, and time of flight), initial fuel mass, and engine design parameters (such as throat area, mixture ratio, and chamber pressure). The constraints include the final velocities and positions of spacecraft. Single-point optimizations are conducted for three departure dates in May, July, and September 2020. A multipoint optimization is also performed to balance the engine performance for these dates with 49 design variables and 20 constraints. It is found that the CCD optimizations exhibit 22–28% more fuel burn reduction than the trajectory-only optimization with fixed engine parameters and 16–20% more fuel burn reduction than the decoupled trajectory-engine optimization. The proposed CCD optimization framework can be extended to more spacecraft trajectory control parameters and onboard systems and has the potential to design more efficient spacecraft missions. 

   more » « less