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a-recurrent-neural-network-based-fuzzy-sliding-mode-control-for-4-dof-rov-movements

code

adaptive-fuzzy-sliding-mode-control

adaptive fuzzy sliding mode control for robot manipulator

adigator

Matlab Algorithmic Differentiation Toolbox

adigator2

afismc

a new observer-based adaptive fuzzy integral sliding mode controller (AFISMC) is proposed based on the Lyapunov stability theorem. The plant under study is subjected to a square-integrable disturbance and is assumed to have mismatch uncertainties both in state- and input-matrices. In addition, a norm-bounded time varying term is introduced to address the possible existence of un-modelled/nonlinear dynamics. Based on the classical sliding mode controller (SMC), the equivalent control effort is obtained to satisfy the sufficient requirement of SMC and then the control law is modified to guarantee the reachability of the system trajectory to the sliding manifold. The sliding surface is compensated based on the observed states in the form of linear matrix inequality (LMI). In order to relax the norm-bounded constrains on the control law and solve the chattering problem of SMC, a fuzzy logic (FL) inference mechanism is combined with the controller. An adaptive law is then introduced to tune the parameters of the fuzzy system on-line. Finally, by aiming at evaluating the validity of the controller and the robust performance of the closed-loop system, the proposed regulator is implemented on a real-time mechanical vibrating system.

attitude-optimal-backstepping-controller-based-quaternion-for-a-uav

Implementation of Attitude Optimal Backstepping Controller for UAV

bie3d

MATLAB tools for boundary integral equations in 3D (Laplace, time-domain wave equation, etc)

casadi

CasADi is a symbolic framework for numeric optimization implementing automatic differentiation in forward and reverse modes on sparse matrix-valued computational graphs. It supports self-contained C-code generation and interfaces state-of-the-art codes such as SUNDIALS, IPOPT etc. It can be used from C++, Python or Matlab/Octave.

cbf

An open source repository for control, planning and navigation about control barrier functions.

cbf-clf-helper

Matlab Interface for Control Barrier Function (CBF) and Control Lyapunov Function (CLF) based control methods.

clf-cbf-qp

Matlab class/functions to simulate a system implementing a control lyapunov-control barrier function quadratic program controller

control-barrier-function-example

Control Barrier function example

decmk-ftc-copter

FTC, quadcopter, adaptive integral sliding mode control, position tracking, python

disturbance_observer

In this note, disturbance rejection control (DRC) based on unknown input observation (UIO), and disturbance-observer based control (DOBC) methods are revisited for a class of MIMO systems with mismatch disturbance conditions. In both of these methods, the estimated disturbance is considered to be in the feedback channel. The disturbance term could represent either unknown mismatched signals penetrating the states, or unknown dynamics not captured in the modeling process, or physical parameter variations not accounted for in the mathematical model of the plant. Unlike the high-gain approaches and variable structure methods, a systematic synthesis of the state/disturbance observer-based controller is carried out. For this purpose, first, using a series of singular value decompositions, the linearized plant is transformed into disturbance-free and disturbance-dependent subsystems. Then, functional state reconstruction based on generalized detectability concept is proposed for the disturbance-free part. Then, a DRC based on quadratic stability theorem is employed to guarantee the performance of the closed-loop system. An important contribution offered in this article is the independence of the estimated disturbance from the control input which seem to be missing in the literature for disturbance decoupling problems. In the second method, DOBC is reconsidered with the aim of achieving a high level of robustness against modeling uncertainties and matched/mismatched disturbances, while at the same time retaining performance. Accordingly, unlike the first method, DRC, full information state observation is developed independent of the disturbance estimation. An advantage of such a combination is that disturbance estimation does not involve output derivatives. Finally, the case of systems with matched disturbances is presented as a corollary of the main results.

eddycurrents-gui

Eddy currents in metallic plate calculation.

event-triggered-controller

Simple examples for Event-triggered control for network controlled system

fastnmpc

fault-estimation-and-ftc-strategies-applied-to-vtol-aerial-vehicles

This project is used to estimate, isolate and diagnose faults for a quadcopter and a PVTOL and also use a methods to control the system by tolerating the fault. Both quadcopter and PVTOL systems have nonlinear dynamics. The ways for fault estimation in this project consist of nonlinear AO and linear PIO for the PVTOL and qLPV PIO for the quadcopter

fem-with-python

Materials for introductory Finite Element course

freefem-sources

FreeFEM source code

fuzzy-robot-type2

An implementation of Fuzzy Logic Control Type 2 for Mobile Robot

fuzzy-sliding-mode-controller

codes for fuzzy sliding mode controller

greenfunction

greenpepper

greensfunction

Green's Function for Lamb's Problem

iclocs

Imperial College London Optimal Control Software (ICLOCS)

laplace-equation

laplace-sequationsolver

learngit

learngit1