Concept Of Feedback Linearization Research Articles

Neural-network-predictor-based control for an uncertain multiple launch rocket system with actuator delay

Development of multiple launch rocket system (MLRS) has been restricted for several decades due to the poor dispersion characteristics of rockets, which is caused by the orientation of the MLRS departing from that intended. Hence, it is vital to maintain the angles of MLRS at a desired value via a proper control strategy. In this paper, a new neural network predictive control is developed for orienting control of the MLRS with actuator delay. First, the dynamic model of motor-mechanism coupling system is established using Lagrange method and field-oriented control theory. Then, for cancelling the effects of nonlinearities and uncertainties, the concept of feedback linearization and a dynamic recurrent neural network are introduced. In addition, a modified Smith predictor is employed to maintain the desirable orienting performance in the occurrence of actuator delay. For the stability analysis, Lyapunov’s method is utilized to ensure uniform ultimate boundedness of the closed-loop system. The simulated and experimental results demonstrate the effectiveness of the proposed controller.

Design and Implementation of a Feedback Linearization Controlled IM Drive via Simplified Neuro-Fuzzy Approach

ABSTRACTThis research paper introduces an outline of a simplified version of single-input neuro-fuzzy controller (NFC) method via a decoupling-controlled intuitive feedback linearization (FBL) approach of induction motor (IM) model. The proposed NFC with FBL extensively reduces the torque and speed ripple along with better performance enhancement. A simplified state-space feedback linearization technique-based nonlinear IM model is designed and simulated in the stationary reference frame. Again, the parameter and plant uncertainties in the feedback-linearized model of the IM are continuous phenomenon which led to the design of a robust, simplified NFC to overcome these issues in the real-time industrial application. The proposed reduced membership function (MF) based simplified NFC is the integration of fuzzy logic and neural network concept with single input as an error (speed and torque) unlike two inputs error and change in error of conventional NFC. This has the advantage of improving the computational efficiency due to its simple structure and robustness over conventional NFC. This makes the system easy and simple to implement in a realistic situation. The performance and effectiveness of the proposed method using FBL concept of IM drive is analyzed using MATLAB software in different modes of operation and is distinguished with the conventional PI-controller and conventional NFC to show its superiority. The proposed system with the different control strategies is also validated by extensive experimental results using DSP 2812.

Slippage control in soft finger grasping and manipulation

Handling objects with robotic soft fingers without considering the odds of slippage are not realistic. Grasping and manipulation algorithms have to be tested under such conditions for evaluating their robustness. In this paper, a dynamic analysis of rigid object manipulation with slippage control is studied using a two-link finger with soft hemispherical tip. Dependency on contact forces applied by a soft finger while grasping a rigid object is examined experimentally. A power-law model combined with a linear viscous damper is used to model the elastic behavior and damping effect of the soft tip, respectively. In order to obtain precise dynamic equations governing the system, two second-order differential equations with variable coefficients have been designed to describe the different possible states of the contact forces accordingly. A controller is designed based on the rigid fingertip model using the concept of feedback linearization for each phase of the system dynamics. Numerical simulations are used to evaluate the performance of the controller. The results reveal that the designed controller shows acceptable performance for both soft and rigid finger manipulation in reducing and canceling slippage. Furthermore, simulations indicate that the applied force in the soft finger manipulation is considerably less than the rigid “one.”.

Fault-tolerant nonlinear adaptive flight control using sliding mode online learning

An expanded nonlinear model inversion flight control strategy using sliding mode online learning for neural networks is presented. The proposed control strategy is implemented for a small unmanned aircraft system (UAS). This class of aircraft is very susceptible towards nonlinearities like atmospheric turbulence, model uncertainties and of course system failures. Therefore, these systems mark a sensible testbed to evaluate fault-tolerant, adaptive flight control strategies. Within this work the concept of feedback linearization is combined with feed forward neural networks to compensate for inversion errors and other nonlinear effects. Backpropagation-based adaption laws of the network weights are used for online training. Within these adaption laws the standard gradient descent backpropagation algorithm is augmented with the concept of sliding mode control (SMC). Implemented as a learning algorithm, this nonlinear control strategy treats the neural network as a controlled system and allows a stable, dynamic calculation of the learning rates. While considering the system's stability, this robust online learning method therefore offers a higher speed of convergence, especially in the presence of external disturbances. The SMC-based flight controller is tested and compared with the standard gradient descent backpropagation algorithm in the presence of system failures.

Feedback Linearization Tracking Control of Vehicle Longitudinal Acceleration Under Low-Speed Conditions

This research addresses the modeling, design, and implementation of a longitudinal acceleration tracking control (LATC) system for a test vehicle at low speeds. An electronic throttle actuator for LATC system application is introduced first, which can be used to perform the switching of three functions arbitrarily: automatic LATC, manual drive-by-wire, and pure manual operation. Then, a nonlinear dynamics model for the test vehicle is proposed by using a state-space equation, and several major nonlinear components including the engine, torque converter, transmission, and electronic throttle actuator are considered simultaneously in this model. Furthermore, focusing on the electronic throttle actuator, the strong nonlinear factors induced by the Coulomb friction and torsion of the return spring are analyzed. In view of the nonlinearity of the proposed model, the concept of feedback linearization is employed to convert the nonlinear system into a linear canonical form, and the analysis of the stability caused by the model’s uncertainty is also discussed. Finally, an acceleration feedback linearization controller and a Kalman filter are introduced. They adopt the linear canonical form, which represents a simpler structure. The performance in tracking desired acceleration at low speeds is confirmed by both computer simulations and experiments.

Dynamically Scaled Generalized Inversion for Asymptotic Stabilization of Underactuated Spacecraft Dynamics

Abstract Novel concept of feedback linearization is introduced for smooth asymptotic stabilization of underactuated spacecraft equipped with one and two degrees of actuation. The concept is based on generalized inversion, and is aimed at asymptotically realizing a perturbation from the unrealizable feedback linearizing transformation. A desired stable second-order linear dynamics in a norm measure of the angular velocity components about the unactuated axes is prescribed. Evaluation of this dynamics along the vector field defined by the underactuated Euler's dynamical equations of angular motion results in a relation that is linear in the control variables. This relation is used to assess realizability of the desired unactuated dynamics, resulting in necessary and sufficient conditions for asymptotic stabilizability of underactuated spacecraft. Generalized inversion of the relation produces a control law that is composed of particular and auxiliary parts. The generalized inverse in the particular part is scaled by a dynamic factor that depends on the spacecraft angular velocity components about the spacecraft actuated axes, such that the generalized inverse converges uniformly to the standard Moore-Penrose generalized inverse as the transient response decays, resulting in asymptotic realization of the desired unactuated stable linear dynamics. The null-control vector in the auxiliary part of the control law is chosen for asymptotic stable perturbed feedback linearization of the actuated subsystem.

Cascaded feedback linearization and its application to stabilization of nonholonomic systems

In this paper, a new cascaded feedback linearization problem is formulated and a set of conditions on the cascaded feedback linearizability are established for a class of two-input affine nonlinear systems. The proposed cascaded feedback linearization method enlarges the classes of nonlinear systems which can be dealt with using the feedback linearization technique. In particular, the proposed design can be applied to address the feedback stabilization problem for a few classes of nonlinear systems which have uncontrollable linearization and do not satisfy the standard feedback linearization conditions. As an illustrative application, the proposed cascade feedback linearization concept is used to solve the feedback stabilization problem of nonholonomic systems within the framework of continuously differentiable state feedback control. Simulation results are provided to illustrate the proposed method.

Application of a new multi-variable feedback linearization method for improvement of power systems transient stability

This article investigates the application of a multi-variable nonlinear controller to the model of a power system. The proposed controller is based on the feedback linearization concept and its main goal is improvement of transient stability and voltage regulation at post-fault conditions. It will be shown that the controller enhances first swing stability and system damping under large disturbances as well as improves terminal voltage regulation. The response of the system is simulated on a test system in the presence of three-phase short circuit at terminal of the synchronous generator and compared to the performance of the standard IEEE type-1 voltage regulator, PSS and PID speed regulator.

Photovoltaic Power Conditioning System With Line Connection

A photovoltaic (PV) power conditioning system (PCS) with line connection is proposed. Using the power slope versus voltage of the PV array, the maximum power point tracking (MPPT) controller that produces a smooth transition to the maximum power point is proposed. The dc current of the PV array is estimated without using a dc current sensor. A current controller is suggested to provide power to the line with an almost-unity power factor that is derived using the feedback linearization concept. The disturbance of the line voltage is detected using a fast sensing technique. All control functions are implemented in software with a single-chip microcontroller. Experimental results obtained on a 2-kW prototype show high performance such as an almost-unity power factor, a power efficiency of 94%, and a total harmonic distortion (THD) of 3.6%

High-Performance Online UPS Using Three-Leg-Type Converter

A high-performance single-phase online uninterruptible power supply (UPS) is proposed. The UPS is composed of a three-leg-type converter which operates as a battery charger and an inverter. The first leg is controlled to charge the battery, and the third leg is controlled to make the output voltage. The common leg is controlled in line frequency. The charger and the inverter are controlled independently. The charger has the capability of power-factor correction while charging a battery. The inverter regulates output voltage and limits output current under an impulsive load. The three-leg-type converter reduces the number of switching devices. As a result, the system has less power loss and a low-cost structure. In the determination of the charger voltage, the nominal voltage is derived using the feedback linearization concept and then a perturbed voltage is determined for the reactive power control. The disturbance of input voltage is detected using a fast sensing technique of the input voltage. Experimental results obtained with a 3-VA prototype show a normal efficiency of over 87% and an input power factor of over 99%.

AN ADAPTIVE NONPARAMETRIC CONTROLLER FOR A CLASS OF NONMINIMUM PHASE NON-LINEAR SYSTEM

This paper addresses the problem of controlling a class of unknown nonlinear systems with unstable inverse, by using a generalized minimum variance approach. We highlight the limitations of the classic cost function used in this context and we propose a new one based on the Generalized Feedback Linearization concept. The adaptive control algorithm uses a nonparametric model, which provides an estimate of the mean and variance of the system output. Simulation examples illustrate the main characteristics and limitation of the proposed approach.

Improved single-phase line-interactive UPS

An improved single-phase line-interactive uninterruptible power supply (UPS) is proposed for low-power applications with low cost. The proposed UPS is comprised of two push-pull converters based on a low-voltage battery for reduced cost: one in series with the input and the other in parallel with the load. In the presence of input power, the UPS acts as an output voltage regulator and at the same time as an active filter while charging the battery. In case of loss of input power, the UPS supplies a regulated sinusoidal voltage to the load, drawing power from the battery. The series converter compensates only a small percentage of the input voltage carrying the input current and, therefore, a reduced rating is made. The parallel converter always supplies a nominal voltage and makes a seamless transition to backup mode. In the voltage determination of the parallel converter, the nominal voltage is derived using the feedback linearization concept and then a perturbed voltage is determined for the reactive power control or output voltage regulation. Experimental results obtained from a 1-kVA prototype are discussed.

On the Robust Nonlinear Motion Position and Force Control of Flexible Joints Robot Manipulators

The design of a robust nonlinear position and force controller for a flexible joints robot manipulator interacting with a rigid environment is presented. The controller is designed using the concept of feedback linearization, sliding mode techniques, and LQE estimation methodologies. It is shown that the nonlinear robot manipulator model is feedback linearizable. A robust performance of the proposed control approach is achieved by accounting for the system parameters uncertainties in the derivation of the nonlinear control law. An upper bound of the error introduced by parametric uncertainties in the system is computed. Then, the feedback linearizing control law is modified by adding a switching action to compensate the errors and to guarantee the achievement of the desired tracking performance. The relationship between the minimum achievable boundary layer thickness and the parametric uncertainties is derived. The proposed controller is tested using an experimental flexible joints robot manipulator, and the results demonstrate its potential benefits in reducing the number of sensors required and the complexity of the design. This is achieved by eliminating the need for nonlinear observers. A robust performance is obtained with minimum control effort by taking into account the effect of system parameter uncertainties and measurement noise.

A power-factor controller for single-phase PWM rectifiers

A novel power-factor controller for single-phase pulsewidth modulated rectifiers is proposed. The unity power-factor controller for a sinusoidal input current is derived using the feedback linearization concept. Two active switches and two diodes are utilized for AC-to-DC power conversion. Experimental results obtained on a 4 kW prototype are discussed.

Model-Based Motion and Force Control for Flexible-Joint Robot Manipulators

Two model-based control algorithms to control the motion and force of flexible-joint robot manipulators are presented. Both algorithms are based on the feedback-linearization concept, and utilize a fourth-order feedback-linearizable model of the flexible-joint manipulators. The first algorithm, dynamic hy brid controller, deals with the problem where the flexible-joint robot is constrained by a rigid environment, and aims at di rect control of the contact forces. A constraint frame is derived that enables decoupling of the system into a position subsystem and a force subsystem. A nonlinear feedback-control law is designed to first decouple and linearize the constrained flexible- joint manipulator system, then impose desired closed-loop characteristics in each subsystem independently. The second algorithm, impedance controller, aims at regulating the rela tionship between the contact force and the difference between the commanded and true positions of the end point. A desired target impedance is designed for the end point of the flexible- joint robot manipulator in the reference frame. A nonlinear feedback controller is designed to linearize the system and to impose the target impedance. The same controller is used when the robot is performing compliant and free motions. An experimental two-link, flexible-joint robot manipulator in con tact with a straight wall is used to evaluate and compare the performance of the two controllers.

An Introduction to the Theory of Exact Stochastic Feedback Linearization for Nonlinear Stochastic Systems

In the design of feedback control laws for nonlinear systems, the concept of exact feedback linearization has emerged as a promising technique. In its current form, the concept of feedback linearization is limited to deterministic systems. The purpose of this paper is to extend this concept to a class of nonlinear stochastic systems. The results of this paper open up a new avenue towards designing nonlinear controllers for stochastic systems.

Nonlinear excitation control of a synchronous generator with implicit terminal voltage regulation

The objective of this paper is to design nonlinear excitation controllers for single-machine infinite-bus power systems. Because of the nonlinear nature of such systems, nonlinear controllers are more effective in providing larger stability margins than their linear counterparts. To take advantage of well-developed linear control techniques, the concept of feedback linearization is used. A characterization of the region over which the linearizing state transformation is guaranteed to be diffeomorphic is provided. Also, a new formulation for the linear controller design is provided to solve the problem of the terminal voltage regulation. Simulation results of a single-machine infinite-bus power system indicate that in the presence of major disturbances the proposed controller outperforms existing linear and nonlinear controllers in maintaining the system's stability, in damping the rotor angle oscillations, and in reaching the desired performance during postfault operations.

Geometric methods for nonlinear process control. 1. Background

We review the mathematical and systems theory background, including linear results, tools from differential geometry, nonlinear inversion, and zero dynamics. The concept of feedback linearization of nonlinear systems is introduced at the end