Large-scale nonlinear programming using IPOPT: An integrating framework for enterprise-wide dynamic optimization

By Lorenz T. Biegler, Victor M. Zavala. Computers and Chemical Engineering, 2009

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Safety-Critical Model Predictive Control with Discrete-Time Control Barrier Function (2020, methodology): “We use the solver IPOPT [22] in MPC-CBF/MPC-DC/DCLF-DCBF problems [23].”
An Introduction to Trajectory Optimization: How to Do Your Own Direct Collocation (2017, background): “Most non-linear programming solvers, such as SNOPT [50], IPOPT [10], and FMINCON [36], require that the user-defined objective and constraint functions be consistent.”
GPOPS-II (2014, methodology): “…− II utilizes in an efﬁcient manner the full capabilities of a much wider range of NLP solvers (for example, full Newton NLP solvers such as IPOPT [Biegler and Zavala 2008] and KNITRO [Byrd et al. 2006]) and, as a result, is capable of solving a much wider range of optimal control problems as…”
Predictive Control for Linear and Hybrid Systems (2017, background): “, [21, 55, 256, 105, 209, 212, 284, 61, 25] requires the simultaneous analysis of several issues such as speed of computation, storage demand and real time code verifiability.”