Nonlinear Control Analysis Research Articles

A Nonlinear Adaptive Control and Robustness Analysis for Autonomous Landing of UAVs

A Nonlinear Adaptive Control and Robustness Analysis for Autonomous Landing of UAVs

Nonlinear Vibration Control and Stability Analysis of a Cantilever Composite Laminated Plate in Hygrothermal Environment

Nonlinear Vibration Control and Stability Analysis of a Cantilever Composite Laminated Plate in Hygrothermal Environment

Comparative performance analysis of fractional-order nonlinear PID controller for complex surge tank system: tuning through machine learning control approach

Comparative performance analysis of fractional-order nonlinear PID controller for complex surge tank system: tuning through machine learning control approach

Modeling and analysis of nonlinear backstepping controller for the crazyflie quadrotor trajectory tracking

This paper illustrates the Newton-Euler laws-based nonlinear dynamic model of a Crazyflie Quadrotor Unmanned Aerial Vehicle (CF-QUAV). It demonstrates the state-space-form equations that govern how the CF-QUAV moves around its frame (body). A Proposed nonlinear control strategy is used to regulate the height (z), position (x, y), attitude (roll and pitch), and heading (yaw) angles. This strategy is based on a Backstepping nonlinear controller defined by Lyapunov theory. The proposed controller can replace the Proportional-Integration-Derivative (PID) controller utilized in the CF-QUAV model to follow the desired trajectories gleaned from CF lab tests. In addition, the parameters of the proposed controller are tuned using the Genetic Algorithm (GA) in order to achieve the best performance and stability of the CF-QUAV model. Simulation-based experiments with statistical analysis are carried out to evaluate the performance of the proposed nonlinear controller and compare its performance and stability with the linear PID controller.

Advanced sensorless nonlinear control and stability analysis of single-stage PV systems connected to the grid via a 3L-NPC inverter

This paper proposes a novel control strategy for a single-stage photovoltaic (PV) system consisting of two PV panels connected to the grid via a three-level neutral point clamped converter topology with an LCL filter. This control method is based on a developed 5th order model containing sum and difference terms of the voltages of the two input capacitors. This allows decoupling the issues of maximum power point tracking and power factor correction from the issue of balancing the power exchange generated by the panels, which facilitates control design and improves system performances. The control problem under consideration is dealt with using a non-linear controller composed of three loops: (i) an inner loop is developed, based on backstepping and Lyapunov approaches, to correct the power factor by forcing the grid current to be sinusoidal and in phase with the grid voltage; (ii) an outer loop is designed, using a filtered proportional-integral controller, to regulate the DC bus voltage to a climate-dependent reference; (iii) a balancing loop is designed, using a proportional-integral controller, to cope with the neutral point voltage balancing problem. The proposed controller also includes a state observer that provides on-line estimation of the network state variables that are not accessible to measurements. Another important aspect of this work is the development of a formal, complete and rigorous analysis in order to describe the performance and analyse the stability of the closed-loop system using various analytical tools, including averaging theory, Routh criteria and indirect Lyapunov stability. A simulation in MATLAB/SIMULINK environment shows, on the one hand, the efficiency and robustness of the proposed nonlinear controller against changing climatic conditions and, on the other hand, the superiority of this control strategy compared to the one based on a PI linear inner loop controller for the studied system with an l- filter and an LCL filter.

Review and Performance Analysis of Nonlinear Model Predictive Control—Current Prospects, Challenges and Future Directions

Review and Performance Analysis of Nonlinear Model Predictive Control—Current Prospects, Challenges and Future Directions

Nonlinear dynamical systems to study epileptic seizures and extract average amount of mutual information from encephalographs – Part I

In this study, we apply the non-linear dynamical systems theory for the assessment built on recurrence-quantification analysis technique for characterizing—differentiating non-linear electro encephalograph (EEG) signals dynamics. The technique offers convenient quantifiable data plus information over normal, tumultuous, or probability and statistical stochastic properties of inherent systems dynamics theory. The R.Q.A-established processes as the quantifiable mathematical features of non-linear electroencephalograph signals dynamics. Average amount of mutual information (AAMI) applied to compute highly applicable feature-manifestation sub-sets out of R.Q.A-built centered-features. The chosen features were then fed into the computer using artificial intelligence based neural net-works for clustering the data of encephalograph-signals to identify ictic(i.e.,ictal), inter ictal, followed by state of controls. The study is implemented by validating R.Q.A with a data base for various issues of categorization. Results showed that the combination of five selected features created on AAMI attained the precision of100% and proves dominance of R.Q.A. Nonlinear dynamical control systems theory and analysis techniques centered on R.Q.A can be used as an appropriate methodology for distinguishing the non-linear systems dynamics of encephalograph signals data also epileptic seizures tracing.

Stability Analysis of Nonlinear Model Predictive Control With Progressive Tightening of Stage Costs and Constraints

Stability Analysis of Nonlinear Model Predictive Control With Progressive Tightening of Stage Costs and Constraints

Analysis of nonlinear vibration control for a functionally graded material plate by NiTiNOL-steel wire ropes

Analysis of nonlinear vibration control for a functionally graded material plate by NiTiNOL-steel wire ropes

Nonlinear system control analysis and optimization using advanced Pigeon-Inspired optimization algorithm

The Pigeon-Inspired optimization (PIO) algorithm is a novel intelligent optimization algorithm inspired by birds’ behavior as their travel. This; behavior modeled to be used for solving many optimization problems in different fields. However; it always suffers from unstable behavior when used with nonlinear; time-varying systems. In; this paper, this algorithm is adapted to calculate the optimum controller gains for roll and pitch channels in a guided tactical missile. The; vehicle model is presented in a nonlinear; form and then shown in a linearized form for the sake of an autopilot design. The PIO; algorithm is supported and accompanied by an adaptive algorithm to determine the initial states and constraints for the PIO algorithm to enhance the behavior of the optimization algorithm to speed up the convergence rate to reach an optimum and feasible solution. Also; an estimation function is incorporated to estimate model parameters variation such as dynamic pressure, stability derivatives, and mass properties. Meanwhile; a comparative analysis is carried out with original PIO and particle swarm optimization algorithms, utilizing a non-linear; model with the presence of noise source and disturbance to ensure the ability of the algorithm to make the autopilot robust and stable against several sources of uncertainties.

Nonlinear Modelling,Control and Performance Analysis of HVDC Tielink Based Load Frequency Control with SMES

Nonlinear Modelling,Control and Performance Analysis of HVDC Tielink Based Load Frequency Control with SMES

Analysis of Optimal Oxygen Excess Ratio and Nonlinear Tracking Control of Vehicle PEMFC Air Supply System

To a large extent, the efficiency and durability of the proton exchange membrane fuel cell (PEMFC) depend on the effective control of air supply system. However, dynamic load scenarios, internal and external disturbances, and the characteristics of strong nonlinearity make the control of complex air supply systems challenging. This paper mainly studies the modeling of PEMFC air supply system and the design of a nonlinear controller for oxygen excess ratio tracking control. First, we analyze and calibrate the system’s optimal oxygen excess ratio control target and explore how the system temperature and humidity impact it, respectively; second, a second-order affine oriented control model which can represent the static and dynamic characteristics of the air supply system is derived, and a disturbance observer is designed to estimate and compensate the “lumped error” online. Then, aiming at the problem of unmeasurable cathode pressure, a state observer based on Kalman optimal estimation algorithm is proposed to realize the real-time estimation of cathode pressure; finally, a dynamic output feedback control system based on observer and backstepping nonlinear controller is proposed, and the comparison and evaluation of two control strategies based on constant oxygen excess ratio tracking and optimal oxygen excess ratio tracking are carried out. The simulation results show the effectiveness and superiority of the designed control system compared with the reference controller.

Design and Analysis of Nonlinear Controller for a Standalone Photovoltaic System Using Lyapunov Stability Theory

Abstract This paper presents the Lyapunov stability theory-based nonlinear controller design for a standalone photovoltaic (PV) system. The comparative analysis of different nonlinear controllers is also carried out. Due to the nonlinear I-V characteristics of photovoltaic systems, conventional hill-climbing methods like Perturbate and Observe and Incremental Conductance do not show reliable tracking of maximum power under various uncertainties. Therefore, these methods require nonlinear tools to meet control objectives and design specifications. Out of various nonlinear controlling techniques, the one presented in this paper is the sliding mode approach for maximum power point tracking (MPPT). In the context of Lyapunov stability theory, the sliding mode approach uses a switching manifold. In this approach, the system trajectories are made to follow the sliding surface and remain there forever to ensure the stability of equilibrium points. Two types of sliding mode controllers have been simulated, namely, conventional—sliding mode controller (CSMC) and terminal—sliding mode controller (TSMC). The results are analyzed and compared scientifically on various performance parameters including duty cycle ratio, ideal and PV output power, and time taken for error convergence, under varying dynamic conditions. All the control algorithms are developed in matlab/Simulink.

Substructure design optimization and nonlinear responses control analysis of the mega-sub controlled structural system (MSCSS) under earthquake action

Substructure design optimization and nonlinear responses control analysis of the mega-sub controlled structural system (MSCSS) under earthquake action

Analysis and comparison of nonlinear control for DC/DC buck converter in PV system

The use of DC power systems is increasingly widely used, so we need a system to convert DC power systems, one of which is a buck converter. The buck converter system requires a controller so that the output voltage generated is as desired without any disturbance when the buck is operating. This study examines improvements in buck converter performance using backstepping and SMC controllers. Backstepping controller and SMC are able to maintain stability where it can be shown by looking at the output voltage value of the buck converter. The results of a comparison of the simulation implementation of the backstepping controller and the SMC show that the recovery time of the SMC is faster than backstepping. From this comparison it is also seen that the amount of SMC voltage deviation is smaller than backstepping.

Nonlinear Controllability Assessment of Aerial Manipulator Systems using Lagrangian Reduction

This paper analyzes the nonlinear Small-Time Local Controllability (STLC) of a class of underatuated aerial manipulator robots. We apply methods of Lagrangian reduction to obtain their lowest dimensional equations of motion (EOM). The symmetry-breaking potential energy terms are resolved using advected parameters, allowing full $SE(3)$ reduction at the cost of additional advection equations. The reduced EOM highlights the shifting center of gravity due to manipulation and is readily in control-affine form, simplifying the nonlinear controllability analysis. Using Sussmann's sufficient condition, we conclude that the aerial manipulator robots are STLC near equilibrium condition, requiring Lie bracket motions up to degree three.

Nonlinear Control and Internal Stability Analysis of Series-Connected Boost DC/DC Converters in PV Systems With Distributed MPPT

Distributed maximum power point tracking photovoltaic (PV) systems based on series-connected dc/dc converters are one of the most promising PV configurations for an enhanced security and efficiency in distributed generation systems. Most of the works reported so far in the literature for control and stability analysis of these configurations are based on small-signal ac models. This could be a significant limitation, as this kind of linearization produces a good approximation of the nonlinear model of series-connected dc/dc converters only at the operating point. However, PV systems must be controlled for a large set of operating points with a satisfactory performance and robustness. Moreover, stability analysis of series-connected dc/dc converters has not yet been widely discussed in previous research. Therefore, this article presents a nonlinear model of series-connected boost dc/dc converters and develops control and stability analysis to fill the gap in this emerging topic. A systematic experimental and numerical investigation is performed in order to validate the effectiveness of the proposed control approach in this study.

Design of a Nonlinear Roll Mechanism for Airplanes Using Lie Brackets for High Alpha Operation

A nonlinear controllability analysis for fixed-wing aircraft has been performed in an earlier effort by the authors, which revealed a novel roll mechanism due to a nonlinear interaction between elevator and aileron control inputs. In this effort, we perform a detailed investigation of this novel roll mechanism, called Lie Bracket Roll Augmentation (LIBRA). First, we show the nonlinear flight physics associated with the LIBRA mechanism. Second, using the Fliess functional expansion, we perform a theoretical study of the effectiveness (degree of controllability) of the LIBRA mechanism in comparison to the conventional mechanism (using ailerons only). Third, to simulate the airplane response to a LIBRA input, we cast the problem of executing the LIBRA mechanism as a nonholonomic motion planning problem. In such a problem, a Lie bracket input is applied to generate motion along an unactuated direction. A Lie bracket input represents a nonlinear interaction between two (or more) control inputs to steer the system along a direction that is not directly actuated by any of these inputs (or their linear combinations). In this language, the LIBRA mechanism is simply a Lie bracket interaction between the elevator and aileron control inputs. We modify existing nonholonomic motion planning algorithms for systems with drift to be more feasible for flight control applications with bounded controls. We show that the LIBRA novel roll mechanism is superior compared to the conventional one during stall, where the aileron sensitivity degrades. In particular, the novel roll mechanism can provide an order of magnitude enhancement in the rolling capability over the conventional roll mechanism near stall.

Research and Analysis of Nonlinear Predictive Model Identification Control Based on Pumped Storage Unit in Construction Site

In this paper, a generalized predictive control method for the speed control system of pumped storage units is proposed, which is suitable for different working conditions of the power generation direction of pumped storage units. Through a combination of mechanism modeling and data-driven model order and parameter reduction strategy to determine the time delay and order of the instantaneous linear prediction model of the speed control system of pumped storage unit. According to the operation state and control target of the unit, the design scheme of the generalized predictive control frequency regulation mode and the opening regulation mode are given respectively, and the dynamic analysis of the control process under different operation conditions is carried out according to the actual parameters of the speed regulation system of a single 300MW pumped storage unit of a pumped storage power station in Central China, which verifies the effectiveness of the control method.

Comparative Analysis of Linear and Nonlinear Control of Wave Energy Converter for a Force Control Application

The aim of wave energy converters (WECs) is to harvest the energy from the ocean waves and convert into electricity. Optimizing the generator output is a vital point of research. A WEC behaves as a nonlinear system in real ocean waves and a control that approximates the behaviour of the system is required. In order to predict the behaviour of WEC, a controller is implemented with an aim to track the referenced trajectory for a force control application of the WEC. A neural model is implemented for the system identification and control of the nonlinear process with a neural nonlinear autoregressive moving average exogenous (NARMAX) model. The neural model updates the weights to reduce the error by using the Levenberg-Marquardt back-propagation algorithm for a single-input-single-output (SISO) nonlinear system. The performance of the system under the proposed scheme is compared to the same system under a PI-controller scheme, where the PI gains have been tuned accordingly, to verify the control capacity of the proposed controller. The results show a good tracking of dq (direct-quadrature) axes currents by regulating the stator currents, and hence a force control is achieved at different positions of the translator. The dynamic performance of the control is verified in a time domain analysis for the displacement of the translator.