PythonLinearNonLinearControl is a library implementing the linear and nonlinear control theories in python.
Official implementation for the paper "Full-Order Sampling-Based MPC for Torque-Level Locomotion Control via Diffusion-Style Annealing". DIAL-MPC is a novel sampling-based MPC framework for legged robot full-order torque-level control with both precision and agility in a training-free manner.
Iterative Linear Quadratic Regulator with auto-differentiatiable dynamics models
Open Source Optimization of Dynamic Multidisciplinary Systems
iterative Linear Quadratic Regulator with support for constraints on input and state variables via barrier functions—Numba-accelerated.
GPU-friendly, auto-differentiable LQR solver with JAX.
A Stochastic Shortest Path Algorithm for Optimizing Spaced Repetition Scheduling
A unified end-to-end learning and control framework that is able to learn a (neural) control objective function, dynamics equation, control policy, or/and optimal trajectory in a control system.
Code for our nips19 paper: You Only Propagate Once: Accelerating Adversarial Training Via Maximal Principle
OpTaS: An optimization-based task specification library for trajectory optimization and model predictive control.
A library for using direct collocation in the optimization of dynamic systems.
An optimization framework that links CasADi, Ipopt, ACADOS and biorbd for Optimal Control Problem
An implementation of iLQR for trajectory synthesis and control
Deep Neural Network architecture as a predictive optimal controller for {HVAC+Solar cell + battery} disturbance afflicted system vs classic Model Predictive Control
Implementing trajectory optimization on bipedal system
Python implementation of Krotov's method for quantum optimal control
Model Predictive Control for a quadrotor in static and dynamic environments
Toolset for control, calibration and characterization of physical systems
Differential Dynamic Programming (DDP) with automatic symbolic differentiation
A modular and scalable simulation framework for ultra-rapid prototyping of self-adaptive, stochastic and robust Nonlinear Model Predictive Control for Autonomous Vehicle Motion Control
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