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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.Extended_State_Observer
a disturbance rejection-based solution to the problem of robust output regulation of linear systems. The difference between the underlying plant and its nominal mathematical model is represented by two classes of disturbances. The first class is generated by an autonomous linear system while the other class has no specific dynamical structure. Robustness against the first disturbance class is achieved by the internal model principle. Next, in the framework of disturbance rejection control, an extended state observer (ESO) is designed to estimate and compensate for the second class of disturbances. As a result, the proposed output regulation method can deal with a vast range of uncertainties. The stability of the closed loop system is investigated and results on practical regulation are drawn. Keywords—Output regulation, extended state observer, disturbance rejection, linear system, robustnessCoupling_ABAQUS_MATLAB
we introduce a new framework for running the finite element (FE) packages inside an online Loop together with MATLAB. Contrary to the Hardware-in-the-Loop techniques (HiL), in the proposed Software-in-the-Loop framework (SiL), the FE package represents a simulation platform replicating the real system which can be out of access due to several strategic reasons, e.g., costs and accessibility. Practically, SiL for sophisticated structural design and multi-physical simulations provides a platform for preliminary tests before prototyping and mass production. This feature may reduce the new product’s costs significantly and may add several flexibilities in implementing different instruments with the goal of shortlisting the most cost-effective ones before moving to real-time experiments for the civil and mechanical systems. The proposed SiL interconnection is not limited to ABAQUS as long as the host FE package is capable of executing user-defined commands in FORTRAN language. The focal point of this research is on using the compiled FORTRAN subroutine as a messenger between ABAQUS/CAE kernel and MATLAB Engine. In order to show the generality of the proposed scheme, the limitations of the available SiL schemes in the literature are addressed in this paper. Additionally, all technical details for establishing the connection between FEM and MATLAB are provided for the interested reader. Finally, two numerical sub-problems are defined for offline and online post-processing, i.e., offline optimization and closed-loop system performance analysis in control theory. Keywords: software-in-the-loop; finite element; optimal placement; structural optimization; vibration control.MPC
Observer-Based Repetitive Model Predictive Control in Active Vibration SuppressionHybrid_Fuzzy_Kalman_Filter
Mixed Kalman-Fuzzy Sliding Mode State Observer in Disturbance Rejection Control of a Vibrating Smart Structure Atta Oveisi*1, Tamara Nestorović1 ​1Ruhr-Universität Bochum, Mechanik adaptiver Systeme, Institut Computational Engineering, D-44801, Bochum, Germany. E-Mail: [email protected] ABSTRACT In the controllers that are synthesized on a nominal model of the nonlinear plant, the parametric matched uncertainties and nonlinear/unmodeled dynamics of high order nature can significantly affect the performance of the closed-loop system. In this note, owing to the robust character of the sliding mode observer against modeling perturbations, measurement noise, and unknown disturbances and due to the non-fragile behavior of the Kalman filter against process noise, a mixed Kalman sliding mode state-observer is proposed and later enhanced by the addition of an intelligent fuzzy agent. In light of the proposed technique, the chattering phenomena and the conservative boundary neighboring layer of the high gain sliding mode observer are addressed. Then, a robust active disturbance rejection controller is developed by using static feedback of the estimated states using direct Lyapunov quadratic stability Theorem. The reduced order plant for control design purposes is subjected to some simulated square-integrable disturbances and is assumed to have mismatch uncertainties in system matrices. Finally, the robust performance of the closed-loop scheme with respect to the mentioned perturbation signals and modeling imperfections is tested by implementing the control system on a mechanical vibrating smart cantilever beam. Keywords: Fuzzy system; Nonlinear control; Active disturbance rejection; Kalman Filter; Vibration suppression.Anti-windup-Compensator
List of additional files available for the interested reader of "Vibration Control Subjected to Windup Problem: An Applied View on Analysis and Synthesis with Convex Formulation"turtlebot2_Localization
This is the localization of the Turtlebo2 by fusing imu, odometry, and GPS dataL2C_AttBot2
Low level controller for AttBot2PathPlanning_Classics
The path planning and graph search algorithmsEKF
implementation of extended kalman filter for sensor fusionturtlebot2_SLAM
This is an example of how to to integrate a fast SLAM algorithm with Turtlebot2occupancy_grid_mapping
This is a pseudo C++ package for doing mapping based on the occupancy gridNon-fragile_observer_based_Controller
Robust Non-Fragile Observer-based Controllerpseudo_particle_filter
An implementation of MCLSubspace_System_Identification
Frequency Domain Subspace Identification of Dynamical SystemsAttBot_Rasberry
AttBot2_SLAM
This is a package for SLAM based on hector_slam package together with AttBot 2.0L2C_GPS_Logger
GAN
generative adversarial networkAttBot2_Localization
The repository is a benchmark for localizing AttBot2.0 using robot_localization packageCNN
Convolution neural networkL2C_Act_AttBot2
Controller for AttBot2Particle_explosion
A graphic interface for particle explosion example based on SDLANN
Artificial neural networkRobot_arm_mover_Gazebo
ORPM
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