Mesbah Lab

All

23 repositories

HW-SW_CoDesign4CoC
Public
Code repository for the paper on A Practical Multi-Objective Learning Framework for Optimal Hardware-Software Co-Design of Control-on-a-Chip Systems by Kimberly J. Chan, Joel A. Paulson, and Ali Mesbah.
VHDL
•0•0•0•0•Updated Aug 7, 2024Aug 7, 2024
CAP-Sensor4Bio
Public
Jupyter Notebook
•0•0•0•0•Updated May 9, 2024May 9, 2024
.github
Public
0•0•0•0•Updated Feb 8, 2024Feb 8, 2024
colloid_char
Public
This code trains and implements a characterization framework based on deep learning for characterizing structural states of colloidal self-assembly systems.
control deep-learning characterization colloids self-assembly
Python
•0•0•0•0•Updated Feb 7, 2024Feb 7, 2024
SPINODE
Public
This code trains and implements a stochastic physics-informed neural ordinary differential equation (SPINODE) framework on a directed colloidal self-assembly test case.
control ode stochastic colloids self-assembly physics-informed-neural-networks
Jupyter Notebook
•0•1•0•0•Updated Feb 7, 2024Feb 7, 2024
SNSF-project-P2ELP2_184521
Public
Multivariable control strategy for a reactor system, efficient global solution method for a reaction system and rocket, solution methods for two approximate formulations of the Bayesian optimal experiment design (OED) problem, optimal control approach for a cold plasma system.
control plasma black-box-optimization model-uncertainty global-solutions
MATLAB
•0•0•0•0•Updated Feb 7, 2024Feb 7, 2024
LCSS_DataDrivenScenarioOptimization
Public
This code obtains closed-loop performance guarantees for automated controller tuning, which can be formulated as a black-box optimization problem under uncertainty.
control black-box-optimization
MATLAB
•0•1•0•0•Updated Feb 7, 2024Feb 7, 2024
PlasmaRL-APPJ
Public
This code trains and implements a reinforcement learning framework for control of the thermal effects of an atmospheric pressure plasma jet
reinforcement-learning plasma cappj
Python
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MIT License
•0•0•0•0•Updated Feb 7, 2024Feb 7, 2024
nsPCE-toolbox
Public
This code is a methods toolbox for constructing non-smooth polynomial chaos expansion (nsPCE) surrogate models. The codes for the nsPCE framework are applicable to non-smooth ODE models and particularly for dynamic flux balance analysis (DFBA) models.
methods dfba
MATLAB
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GNU General Public License v3.0
•0•1•0•0•Updated Feb 7, 2024Feb 7, 2024
Machine-Learning-for-Plasma-Diagnostics
Public
This code trains and implements machine learning models for real-time diagnostics of cold atmospheric plasma sources.
real-time plasma diagnostics machine-learning-models
Jupyter Notebook
•0•0•0•0•Updated Feb 7, 2024Feb 7, 2024
DFT-microkinetic
Public
A Study on the Role of Electric Field in Low-Temperature Plasma Catalytic Ammonia Synthesis via Integrated Density Functional Theory and Microkinetic Modeling
machine-learning plasma density-functional-theory active-learning
Fortran
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MIT License
•0•1•0•0•Updated Feb 7, 2024Feb 7, 2024
Plasma-Wafers
Public
Code for running APPJ experiments with silicon wafers
control plasma cappj silicon-wafers
Python
•0•0•0•0•Updated Feb 7, 2024Feb 7, 2024
Code-for-AL-PSST-Mesbah-lab
Public
Active learning-guided exploration of parameter space of air plasmas to enhance the energy efficiency of NO x production
machine-learning plasma neural-networks active-learning design-of-experiments
MATLAB
•0•0•0•0•Updated Feb 7, 2024Feb 7, 2024
Berkeley-Lam-2023-UNLOCK
Public
Lam collaboration for offset-free filter of model predictive control on CAPPJ system
control plasma mpc lam cappj
Jupyter Notebook
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MIT License
•0•0•0•0•Updated Feb 7, 2024Feb 7, 2024
APPJ-MacOS-Communication
Public
Control of the CAPPJ system using MacOS
plasma cappj
C++
•0•0•0•0•Updated Feb 7, 2024Feb 7, 2024
ML-for-plasmas
Public
This repository contains code that demonstrates the use of a variety of machine learning strategies for low temperature plasma systems.
machine-learning plasma methods
Jupyter Notebook
•0•1•0•0•Updated Feb 7, 2024Feb 7, 2024
arbo-controllers
Public
Here we visualize the need for robust BO against an adversary. Clearly the optimum design point changes depending the uncertain parameter x, so we should identify a region for which the decision variable x resides in an optimal region.
black-box-optimization bayesian-optimization adversarial-machine-learning
Jupyter Notebook
•0•0•0•0•Updated Feb 7, 2024Feb 7, 2024
Performance-Oriented-DNN-MPC
Public
Performance-oriented model learning for control via multi-objective Bayesian optimization
control mpc black-box-optimization mobo model-learning
Jupyter Notebook
•0•1•0•0•Updated Feb 7, 2024Feb 7, 2024
BO4Policy_Search_Plasma
Public
Towards Personalized Plasma Medicine via Data-efficient Adaptation of Fast Deep Learning-based MPC Policies
machine-learning control deep-learning plasma biological cappj
Jupyter Notebook
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MIT License
•0•0•0•0•Updated Feb 7, 2024Feb 7, 2024
LB-Multi-Stage-NMPC
Public
Learning-based multi-stage NMPC algorithm with guarantees on feasibility using robust control invariant sets
learning control mpc nmpc
MATLAB
•0•4•0•0•Updated Feb 7, 2024Feb 7, 2024
Mesbah-APPJ
Public
This is a cleaned-up version of APPJ_Control which was forked from Dogan Gidon's APPJ_Control repository. This will be the location of the latest info (until August 2024) about the atmospheric pressure plasma jet (APPJ) located in the Mesbah Lab at UC Berkeley. The repository contains condensed information from the previous iterations.
control plasma cappj
Python
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Other
•1•0•0•0•Updated Feb 7, 2024Feb 7, 2024
DNN_MPC_Plasma_FPGA
Public
Project files for a neural network (NN) implementation on an FPGA using Vivado HLS.
machine-learning neural-networks fpga-programming
Verilog
•0•0•0•0•Updated Feb 7, 2024Feb 7, 2024
SafeBOPlasma
Public
Safe Explorative Bayesian Optimization -- Towards Personalized Treatments in Plasma Medicine
control plasma methods black-box-optimization bayesian-optimization biological
Jupyter Notebook
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MIT License
•0•0•0•0•Updated Feb 7, 2024Feb 7, 2024