Open Optimal Control Library for Matlab. Trajectory Optimization and non-linear Model Predictive Control (MPC) toolbox.

Optimal Control Strategies on Cart-pole System in Simscape Multibody Simulation

Adaptive dynamic programming

nosnoc is an open source software package for NOnSmooth Numerical Optimal Control.

Self-balancing robot analysis and LQG optimal controller design with MATLAB Simulink and Simscape Multibody

Code for the paper {Pang, Bo, and Zhong-Ping Jiang. "Reinforcement Learning for Adaptive Optimal Stationary Control of Linear Stochastic Systems." arXiv preprint arXiv:2107.07788 (2021)."}

This project solves linear-quadratic dynamic optimization (LQDO) problems using direct transcription (DT) and quadratic programming (QP)

This is a official code implementation for Nonlinear RISE based Integral Reinforcement Learning algorithms for perturbed Bilateral Teleoperators with variable time delay (Neurocomputing Journal).

月球软着陆制导、能量/燃料最优控制、最优控制间接法、微分变换求解两点边值问题、月球着陆制导控制

[IFAC 2023] "H2 suboptimal leader-follower consensus control of multi-agent systems" by Yuan Gao, Junjie Jiao, Sandra Hirche

University group project concerning the implementation of an iterative learning controller tested on a Cart-Pole system. The code has been implemented in Matlab.

Implementation of DDP algorithm for Optimal Control on a Bicycle Model for optimal lane change maneuvering and Skidpad track following.

This is the Github repository for a fault tolerant optimal ZNN controller with state constraints and precribed performance constraints described in the paper title "A Provably Constrained Neural Control Architecture With Prescribed Performance for Fault-Tolerant Redundant Manipulators

A simple and extensible Octave/Matlab library for Model Predictive Path Integral control scheme.

Optimal Control and Trajectory Tracking for the Ballbot (Nagarajan et al. 2014)

Successive Convexification with Continuous-Time Constraint Satisfaction

Calculates an optimal LQR controller for a noisy inverted pendulum and simulates the result.

ODESCA is a MATLAB tool for the creation and analysis of dynamic systems described by ordinary differential equations

This approach is used to solve data-driven optimal control problems by providing a Koopman operator based convex formulation

Project for 16-745 Optimal Control and Reinforcement Learning at CMU