BaCLNS: A toolbox for fast and efficient control of Linear and Nonlinear Control Affine Systems

TL;DR

BaCLNS is a Python toolbox that automates the design, simulation, and analysis of backstepping control laws for linear and nonlinear control-affine systems, making advanced control techniques more accessible.

Contribution

It introduces a standardized, modular Python package that simplifies the derivation, simulation, and visualization of backstepping controllers for complex systems.

Findings

Successfully stabilizes linear and nonlinear systems

Handles complex nonlinear dynamics like chaotic systems

Demonstrates effectiveness through diverse examples

Abstract

Backstepping Control of Linear and Nonlinear Systems (BaCLNS) is a Python package developed to automate the design, simulation, and analysis of backstepping control laws for both linear and nonlinear control-affine systems. By providing a standardized framework, BaCLNS simplifies the process of deriving backstepping controllers, making this powerful control technique more accessible to engineers, researchers, and educators. The package handles complex system dynamics, ensuring robust stabilization even in the presence of significant nonlinearities. BaCLNS's modular design allows users to define custom control systems, simulate their behavior , and visualize the results all within a user-friendly environment. The effectiveness of the package is demonstrated through a series of illustrative examples, ranging from simple linear systems to chaotic nonlinear systems, including the Vaidyanathan Jerk System, the pendulum and the Van der Pol Oscillator.