The attitude dynamics of spacecraft are highly nonlinear, which makes it challenging to design control algorithms that can handle these nonlinearities. This study presents a novel data-driven synthesis method for using the LightGBM controller. controller is designed by supervised machine learning methodologies. training and testing datasets generated from input-output data closed-loop system un...

Many control applications require the use of both symbolic and numeric computation. An illustrative example is the analysis and controller design of a mechanical system. To begin with, we need to compute the equations of motion. To study local stability we need to compute its linearization. To apply control concepts like feedback linearization we may need to compute the inverse system. All thes...

This paper is concerned with the static output feedback (SOF) stabilization for discrete-time networked control systems (NCSs) with input and output signals quantization. A novel model of the systems is proposed by a sector bounded approach where the internal effects of network induced delay and signals quantization are considered. By using Lyapunov functional approach, together with introducin...

For output-feedback adaptive control of affine nonlinear systems based on feedback linearization and function approximation, the observation error dynamics usually should be augmented by a low-pass filter to satisfy a strictly positive real (SPR) condition so that output feedback can be realized. Yet, this manipulation results in filtering basis functions of approximators, which makes the order...

The objective of this paper is to construct a wind generator system (WGS) loss model that addresses the loss of the wind turbine and the generator. It aims to optimize the maximum effective output power and turbine speed. Given that the wind generator system has inertia and is nonlinear, the dynamic model of the wind generator system takes the advantage of the duty of the Buck converter and emp...

This paper presents a new control technique for the EDC thermal cracking furnace modeled by sets of ordinary differential equation (ODE) and 2D-partial differential equations (PDEs). The dynamics of coupled 2DPDEs-ODE model have been divided into 2 subsystems, set of state variables of the internal and external cracking coil. With the concept of input-output (I/O) linearization, these inner and...

Model-based nonlinear controllers like feedback linearization and control Lyapunov functions are highly sensitive to the model parameters of the robot. This paper addresses the problem of realizing these controllers in a particular class of hybrid models–systems with impulse effects–through a parameter sensitivity measure. This measure quantifies the sensitivity of a given model-based controlle...

in this paper, the unified power flow controller (upfc) is enhanced with a chaotic particle swarm optimization (cpso) damping controller in order to mitigate the low frequency oscillations (lfo) in a single machine infinite bus (smib) power system. the designed damping controller is an optimized lead-lag controller, which extracts the speed deviation of the generator rotor and generates the out...

3 System Control 12 3.1 PID Controller . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12 3.2 Direct Inverse Control and Optimal Control . . . . . . . . . . . . 12 3.3 Feedback Linearization . . . . . . . . . . . . . . . . . . . . . . . . 13 3.4 Nonlinear Predictive Control . . . . . . . . . . . . . . . . . . . . 13 3.5 Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . ...

During the last decade, there has been a growing interest in developing nonlinear model-based control methods. This interest has led to substantial progress mainly within the two frameworks of model predictive control (MPC) and differential geometric control. MPC is an optimization-based control methodology which explicitly accounts for process constraints and in general leads to a controller w...