Adaptive Backstepping Sliding Mode Control for ABS with Nonlinear Disturbance Observer

This study presents a nonlinear observer that estimates structured and unstructured uncertainties based on a control methodology that is an adaptive backstepping sliding mode controller to aim wheel slip tracking of a car-like robot. In the vehicle system, the scaling factor for the lengthwise force between tire and road contact is considered as unknown, then adaptation law with Lyapunov-based analysis is derived for the unknown parameter. The lump uncertainties estimated values that are estimated by the nonlinear disturbance observer and the scaling factor estimated values are directly applied in the control input. The closed-loop system stability under the proposed controller is proven using Lyapunov's stability analysis. Then, the adaptive backstepping sliding mode controller's performance with the nonlinear disturbance observer is verified through simulations by comparing to the neural network (radial basis function) observer, which is estimated as the lump uncertainties on quarter-vehicle dynamics

Suboptimal Solutions for Time Varying Time Delayed MPC Controllers

Model Predictive Control (MPC) with constraints is still an interesting subject and offers many problems to work on. This study basically aims to understand the optimization process and the decrease of convex quadratic costs in a single model predictive controller. For those processes where the system dynamics change so slowly it is essential to obtain the control law as soon as possible to minimize the time delay on the controller side. This study proposes an early termination of the optimization process and the suboptimal solution to the quadratic programming. To define the early termination in the following chapters it is discussed and explained when, where. The implementation of the strategy is also illustrated with a case study and it is compared to the LQR controller for the regulator problem

Robust Discrete-Time Nonlinear Attitude Stabilization of a Quadrotor UAV Subject to Time-Varying Disturbances

A discrete-time improved input/output linearization controller based on a nonlinear disturbance observer is considered to secure the stability of a four-rotor unmanned aerial vehicle under constant and time-varying disturbances, as well as uncertain system parameters for its attitude behaviour. Due to the nature of the quadrotor system, it contains the most extreme high level of nonlinearities, system parameter uncertainties (perturbations), and it has to cope with external disturbances that change over time. In this context, an offset-less tracking for the quadrotor system is provided with the input/output linearization controller together with a discrete-time pre-controller. In addition, the robustness of the system is increased with a discrete-time nonlinear disturbance observer for time-varying disturbances affecting the system. The main contribution of this study is to provide highly nonlinearities cancellation to guarantee the aircraft attitude stability and to propose a robust control structure in discrete-time, considering all uncertainties. Various simulation studies have been carried out to illustrate the robustness and effectiveness of the proposed controller structure