Weifeng Chen

A unified trajectory optimization framework for lunar ascent

This paper presents a unified trajectory optimization framework for lunar ascent. Compared with prevailing and emerging studies on lunar ascent trajectory optimization with simplified lunar ascent process and simple constraints, our method formulates in detail the lunar ascent process with complex constraints in a unified manner. The kinematics and dynamics model of lunar ascent with mission-specific constraints explicitly expressed through equalities or inequalities form the fuel-optimal lunar ascent trajectory optimization problem. A proper direct trajectory optimization method is chosen to transcribe the original trajectory optimization problem into a nonlinear programming (NLP) problem solved by a highly efficient NLP solver. The homotopy-based backtracking initial value strategy is designed to enhance convergence of the solving process. First, a two-phase trajectory optimization problem including vertical-rise phase and orbit-insertion phase is solved in the proposed unified framework. Subsequently, to obtain terrain clearance, we directly incorporate terrain description into the lunar ascent problem to obtain the optimal lunar ascent trajectory. Simulation results indicate that the proposed unified trajectory optimization framework has enough adaptability to efficiently handle complex lunar ascent scenarios. The proposed framework may benefit future autonomous lunar ascent missions.

Interfacing IPOPT with Aspen Open Solvers and CAPE-OPEN

CAPE-OPEN (CO) is brought forward as the standard for the next generation of process system simulation platform. In this work, the IPOPT algorithm and interface developed by (Lang and Biegler, 2005) is extended. IPOPT is encapsulated and is embedded into Aspen Plus through Aspen Open Solvers (AOS) Interface. A scaling module based on starting point is developed for scaling the models from Aspen Plus before optimization. The validity of AOS compliant IPOPT is tested by solving the economic optimization problem of depropanizer and debutanizer multi-column system and the reconciliation problem of large-scale air separation system. Compatibility of Aspen Plus for CO solvers is extended based on AOS interface through COM technology. In order to demonstrate validity of the extended compatibility, CO compliant IPOPT is integrated with Aspen Plus. It is tested by the same examples as AOS compliant IPOPT. Further analysis is made on effect of model scale on efficiency loss since the introduction of CO.

An approach for simultaneous estimation of reaction kinetics and curve resolution from process and spectral data: Simultaneous estimation of reaction kinetics and curve resolution

Parameter estimation of reaction kinetics from spectroscopic data remains an important and challenging problem. This study describes a unified framework to address this challenge. The presented framework is based on maximum likelihood principles, nonlinear optimization techniques, and the use of collocation methods to solve the differential equations involved. To solve the overall parameter estimation problem, we first develop an iterative optimization‐based procedure to estimate the variances of the noise in system variables (eg, concentrations) and spectral measurements. Once these variances are estimated, we then determine the concentration profiles and kinetic parameters simultaneously. From the properties of the nonlinear programming solver and solution sensitivity, we also obtain the covariance matrix and standard deviations for the estimated kinetic parameters. Our proposed approach is demonstrated on 7 case studies that include simulated data as well as actual experimental data. Moreover, our numerical results compare well with the multivariate curve resolution alternating least squares approach.

Three-Dimensional Trajectory Optimization for Lunar Ascent Using Gauss Pseudospectral Method

In this paper, the problem of fuel-optimal lunar ascent trajectory optimization using constant-thrust propulsion is considered. The whole lunar ascent process is divided into two phases: vertical-rise phase and orbit-insertion phase, respectively. Considering the influence of rotation of the moon, a three-dimensional kinematics and dynamics model for lunar ascent is established. The fuel-optimal lunar ascent trajectory optimization problem is posed as a two-phase constrained nonlinear trajectory optimization problem solved by using Gauss pseudospectral method. Initial guesses for this trajectory optimization problem are obtained by solving a subproblem where the angular rate of pitch angle and yaw angel is not constrained. Four scenarios of the two-phase lunar ascent trajectory optimization problem are designed. The simulation results show that all state and control variables satisfy the related constraints and practical engineering condition in each scenario. The developed direct trajectory optimization framework has the adaptability to address various scenarios of the two-phase lunar ascent mission.

Three-Dimensional Aircraft Conflict Resolution Based on Smoothing Methods

The development of an automated and optimal conflict predicting and resolution strategy is one of the most important components in successfully implementing the Next Generation Air Transportation System concept. The conflict resolution problem, which occurs between multiple aircraft described by a three-degree-of-freedom nonlinear point-mass model, is the focus of this study. A novel method for handling nondifferentiable disjunctive conflict avoidance constraints is developed by using smoothing functions, which are constructed by integrating a probability density function. Thus, the conflict resolution problem is posed as an optimal control problem and discretized into a nonlinear programming problem via the direct transcription approach with a Radau collocation point. The approximation error obtained using the smoothing functions is examined through sensitivity analysis. An estimable linear relationship is established between the approximation error and the smoothing parameter, which indicates that the a...

Sensitivity embedded homotopy-based backtracking method for chemical process simulation

Considering the constant fluctuation of raw material costs and user demand, frequent and wide-range off-design operation is necessary. The process simulation with equation-oriented approach at multiple operation conditions is difficult because of the complexity and nonlinearity of chemical processes. In this study, the homotopy-based backtracking method (HBM) for simulation is modified with prediction step, which can be calculated by applying sensitivity analysis. The theory foundation for the proposed sensitivity embedded homotopy-based backtracking method (S-HBM) is established. Numerical results of the argon sidearm column show that the performance of S-HBM is better than that of HBM.

Sensitivity-based Mnemonic Enhancement Optimization (S-MEO) for Real-time Optimization of Chemical Process

Abstract Real-time optimization (RTO) has become a standard practice to improve production benefits during the past years. The efficiency of solving optimization problems is critical because a large computational delay leads to the possible loss of validity and availability of RTO. In this study, the Mnemonic Enhancement Optimization (MEO) strategy of initialization for RTO has been extended by taking advantage of optimal sensitivity. The approximation precision and the solution information database accumulation efficiency of the proposed sensitivity-based MEO are briefly analyzed. The numerical results tested with a high-pressure column of a cryogenic air separation unit were in agreement with the theoretical analysis.