Output Linearization Research Articles

A nonlinear control scheme based on input–output​ linearized method achieving PFC and robust constant voltage output for boost converters

This paper presents an input–output linearization (IOL) control strategy to achieve PFC (power factor correction) and output voltage constant in a boost converter. The method transforms the nonlinear system to a linear one in new coordinates by the appropriate nonlinear coordinate transformation and state feedback, ultimately allowing the controller to be designed according to the classical linear control theory. An example implementation is simulated using PSIM software. The simulation results show that the phases of input voltage and input current are consistent, and the output voltage remains constant under load step changes. A set of experimental devices are set up to verify the control method, and the results are consistent with the simulation. Thus, the method is proved to be effective in achieving PFC and provides robust constant voltage output in the boost converter.

More Efficient Wind Energy Conversion System Using Shunt Active Power Filter

Wind energy takes first place in many countries among other renewable energy. However, the power quality problems such as nonlinear and unbalanced loads, unbalanced grid, can increase the mechanical vibrations as well as the risk of overheating in Wind Energy Conversion System (WECS). Therefore, the objective of this work is the use of robust flying capacitor converter in order to enhance the WECS efficiency by minimizing mechanical vibrations and reducing thermal stress with minimum voltage stress of power switches. To this end, this paper proposes a WECS based on doubly fed induction generator (DFIG) with the stator connected directly to non-ideal power grid, grid side converter (GSC) with flying capacitor topology and robust input output linearization control used to regulate the dc side capacitor voltage and also compensate the current harmonics in power grid in order to avoid excessive heating and mechanical vibrations in WECS. Simulation using MATLAB demonstrate that the proposed approach improves the power quality by reducing the total harmonic distortion (THD) of grid current to a value which satisfies the limits of IEEE standard, and allows the 8 KW DFIG to operate with reduced mechanical vibration and minimum heating stress in addition to the generation of power.

Adaptive neural network control of second-order underactuated systems with prescribed performance constraints

Abstract This paper studies the trajectory tracking control problem of second-order underactuated system subject to system uncertainties and prescribed performance constraints. By combining radial basis function neural networks (RBFNNs) with input–output linearization methods, an adaptive neural network-based control approach is proposed and the adaptive laws are given through Lyapunov method and Taylor expansion linearization approach. The main contributions of this paper are that: (1) by introducing weight performance function and transformation function, the states never violate the prescribed performance constraints; (2) the control scheme takes the unknown control gain direction into consideration and the singular problem of control design can be avoided; (3) through rigorously stability analysis, all signal of closed-loop system are proved to be uniformly ultimately bounded. The effectiveness of the proposed control scheme was verified by comparative simulation.

Objective holographic feedbacks linearization control for boost converter with constant power load

As a typical load, the constant power load (CPL) is different from the resistive load and has destabilizing negative impedance characteristics, influencing the system stability. The boost converter with the output voltage as the feedback control variable is a non-minimum phase nonlinear system because its linear approximation has a right-half-plane (RHP) pole. The non– minimum phase system limits the application of control techniques such as input–output linearization (IOL). This paper presents an objective holographic feedbacks linearization control strategy (OHFLC) for DC power systems with constant power loads, bypassing non-minimum phase systems to stabilize the system. The analysis of the proposed method’s pole-zero points indicates that it is based on placing the pole-zero points of the system on their corresponding desired positions through feedback so as to achieve satisfactory dynamic and static performance of the control system. Finally, simulation and experimental verification demonstrate that the presented control approach provides superior dynamic response and robustness than the traditional proportional-integral (PI) control.

Input-output linearized spacecraft formation control via differential drag using relative orbital elements

The derivation, implementation, and performance assessment of a differential drag based algorithm, designed for spacecraft formation control using a relative orbital elements formulation, is presented. In contrast to similar approaches found in literature, the underlying motion dynamics model used to derive the control law includes J 2 perturbation as well as atmospheric drag perturbation based on a nonlinear density model. The basic idea of the control algorithm is to algebraically transform the nonlinear plant into a linear substitute. The resulting control law can be interpreted as combined feedforward and feedback PID control, applied to the linear substitute model. Motion dynamics and perturbations are accounted for in a feedforward branch while a PID feedback branch undertakes the cancellation of errors caused by model uncertainties and unmodeled physics. For linearized plant models, the computation of a feedforward branch is straight forward from the state transition matrix. In the nonlinear case proposed in this paper, the inclusion of a feedforward signal is achieved using the input-output linearization technique, yielding a nonlinear and globally valid control law. Sample numerical simulations are presented to support the validity of the controller and to demonstrate its performance compared to a simple PID controller. Simulation results show enhanced tracking performance of the mean along-track separation reference signal and reduced control effort. Moreover, input–output linearization enables the control of a large set of operating points using one set of control parameters.

An Adaptive Observer-Based Controller Design for Active Damping of a DC Network With a Constant Power Load

This article explores a nonlinear, adaptive controller aimed at increasing the stability margin of a direct-current (dc), small-scale, electrical network containing an unknown constant power load (CPL). Due to its negative incremental impedance, this load reduces the effective damping of the network, which may lead to voltage oscillations and even to voltage collapse. To overcome this drawback, we consider the incorporation of a controlled dc–dc power converter in parallel with the CPL. The design of the control law for the converter is particularly challenging due to the existence of unmeasured states and unknown parameters. We propose a standard input–output linearization stage, to which a suitably tailored adaptive observer is added. The good performance of the controller is validated through experiments on a small-scale network.

Adaptive neural network control of nonlinear systems with unknown dynamics

In this study, an adaptive neural network control approach is proposed to achieve accurate and robust control of nonlinear systems with unknown dynamics, wherein the neural network is innovatively used to learn the inverse problem of system dynamics with guaranteed convergence. This study focuses on the following three contributions. First, the considered system is transformed into a multi-integrator system using an input–output linearization technique, and an extended state observation technique is used to identify the transformed states. Second, an iterative control learning algorithm is proposed to achieve the neural network training, and stability analysis is given to prove that the network’s predictions converge to ideal control inputs with guaranteed convergence. Third, an adaptive neural network controller is developed by combining the trained network and a proportional-integral controller, and the long-standing challenge of model-based methods for control determination of unknown dynamics is resolved. Simulation results of a virtual control mission and an aerospace altitude tracking mission are provided to substantiate the effectiveness of the proposed techniques and illustrate the adaptability and robustness of the proposed controller.

Design of Decoupling Fuzzy Logic Controller for Quadrotor UAV

This article first briefly introduces the quadrotor UAV model based on the Newton-Euler method, including kinematics model, dynamic model and force and moment model, and then proposes a decoupling fuzzy controller, which can effectively decouple the position and the orientation of the quadrotor UAV, i.e., the inner loop uses the input and output linearization method to control orientation, and the outer loop uses a fuzzy logic controller to control the position of the quadrotor UAV. Finally, we use Matlab to model the quadrotor UAV and design the decoupling fuzzy controller to control the quadrotor UAV. The results show that the tracking performance is good, which proves the feasibility of the controller algorithm.

Nonlinear coordinated control design of generator excitation and static var compensator for power system via input-output linearization

This paper proposes a nonlinear coordinated controller for a single machine infinite bus power system. The later consists of a synchronous generator connected to the infinite bus via transmission lines, which are equipped with a static var compensator. The proposed control strategy aims to control simultaneously the excitation system of the synchronous generator and the static var compensator in order to improve transient stability and voltage regulation. The input output linearization theory and pole-assignment technique are employed to design the nonlinear controller. The controller’s performance in single machine infinite bus power system is then examined using simulation studies when the studied power system is subjected to three-phase short circuit with a 100ms duration. The results validate the efficiency of the proposed controller, which is based mainly on the good regulation of the static var compensator voltage with removing the static error after fault elimination.

Nonlinear Position Control Using Differential Flatness Concept with Load Torque Observer for Electro Hydraulic Actuators with Sinusoidal Load Torque

We propose a nonlinear position control using a differential flatness concept with a load torque observer to compensate for the sinusoidal load torque in electro-hydraulic actuators (EHAs) EHAs. In an EHA with a rotational joint, the load torque is a sinusoidal disturbance, whose magnitude can be estimated via a load torque observer. In the proposed load torque observer, the load torque can be estimated without requiring its maximum frequency to be known. The position controller tracks position and comprises an inner-loop load pressure controller and an outer-loop position controller. The former tracks the desired pressure via near input–output linearization. The desired pressure is developed using the differential flatness of the mechanical system in the EHA. The feedback plus feedforward outer-loop position controller is designed to track the desired position and to compensate for the load torque. The stability of the closed-loop system is mathematically proven using the input-to-state stability property.

Robust-Backstepping Missile Autopilot Design Considering Time-Varying Parameters and Uncertainty

Missile autopilots for aerodynamic angle control and acceleration control are designed for fin-controlled missiles during the boost phase. In the boost phase, the speed change and the parameter variation of the missile are fast and large. To deal with the time-varying characteristics of the missile, the time-varying parameters are considered in nonlinear dynamics, and the parametric uncertainties are modeled. A state-feedback controller is designed for aerodynamic angle control based on a robust-backstepping scheme. Also, an output feedback controller is designed for acceleration control, where the acceleration dynamics are derived using input–output linearization. Numerical simulations are performed to demonstrate the performance of the proposed controllers.

On active disturbance rejection control for nonlinear systems with multiple uncertainties and nonlinear measurement

SummaryThe paper proposes a novel control design for nonlinear systems with multiple uncertainties and nonlinear measurement. The output linearization is utilized to handle the nonlinearities in system dynamics and measurement. Firstly, the integrator chain for nonlinear systems with multiple uncertainties is analyzed. Based on the fundamental integrator chain form, the equivalent total effect of multiple uncertainties is summarized as total disturbance. By timely estimating and compensating for the total disturbance, an active disturbance rejection control design to handle both multiple uncertainties and nonlinear measurement is proposed. Moreover, the transient performance of the corresponding closed‐loop system is rigorously studied, which theoretically reveals the high consistence of the tracking performance despite various multiple uncertainties.

Control of biomass grate boilers using internal model control

A new model-based control strategy for biomass grate boilers is presented in this paper. Internal model control is used to control four outputs of the plant and to achieve a control structure with fewer control parameters needing to be experimentally tuned. A nonlinear state–space model describing the essential behaviour of the biomass grate boiler is used for controller design. The inverse system dynamics representing the main part of internal model control are designed with the help of this model. In doing so the properties of differentially flat systems are used. Due to a time delayed input, the inverse system is determined only for three input output channels. The stabilization of the inverse system dynamics, however, is a challenging task. A stabilization method with the help of the time delayed input is suggested and a stability analysis is given. The new control strategy has only three parameters to be tuned, representing a major reduction of complexity in comparison to existing model-based approaches. Finally, experimental results of the implemented control strategy on representative biomass grate boiler with a nominal capacity of 180 kW are presented and compared to an existing model-based control strategy based on input output linearization. The experimental evaluation proves that it is possible to operate the biomass boiler in all load ranges with high efficiency and low pollutant emissions.

Two-degree-of-freedom MIMO control for hydraulic servo-systems with switching properties

Today’s automotive industry is faced with the challenge of increasing the energy efficiency of passenger cars to meet ever tightening emissions regulations. An approach to overcome these challenges is the electrification of auxiliary units of the vehicle, such as the pump drive of a hydraulic servo-system for clutch actuation in automatic transmissions (AT) or dedicated hybrid transmissions (DHT). In this context, the model-based derivation of a nonlinear feedforward control law by application of input–output linearization to a non-flat system, is presented. The underlying model, which shows switching behaviour, is derived by simplification of a physical model of the investigated hydraulic servo-system with switching properties. The control objective consists in providing the required system pressure and volume flow for fast and accurate clutch actuation through operation of several servo-valves and an electric pump drive without using a hydraulic accumulator. In this context, planning of feasible trajectories is discussed for the investigated numerically and physically stiff multi-input multi-output system (MIMO). Additionally, a nonlinear two-degree-of-freedom control concept is designed by extension of the derived nonlinear feedforward controller with a PID feedback loop. The presented control schemes for trajectory tracking are examined in simulation and validated on testbed using real hydraulic hardware.

Field Weakening Operation Control Strategies of PMSM Based on Feedback Linearization

Based on current research into the mathematical model of the permanent magnet synchronous motor (PMSM) and the feedback linearization theory, a control strategy established upon feedback linearization is proposed. The Lie differential operation is performed on the output variable to obtain the state feedback of the nonlinear system, and the dynamic characteristics of the original system are transformed into linear dynamic characteristics. A current controller based on the input–output feedback linearization algorithm is designed to realize the input–output linearization control of the PMSM. The current controller decouples the d–q axis current from the flux linkage information of the motor and outputs a control voltage. When the motor speed reaches above the base speed, the field-forward and straight-axis current components are newly distributed to achieve field weakening control, which can realize the smooth transition between the constant torque region and weak magnetic region. Simulation and experimental results show the feasibility and viability of the strategy.

Dynamic Extension Algorithm-Based Tracking Control of STATCOM Via Port-Controlled Hamiltonian System

In this article, a novel passivity-based control strategy is proposed for the exponentially stable tracking controller design of static synchronous compensator (STATCOM) system, which is a single input and single output. The STATCOM is not an input-affine system but a special port-controlled Hamiltonian system form. Hence, it is regularized by using a dynamic extension algorithm so that the proposed tracking control strategy is designed in an input–output linearization framework with a bounded solution to the driven zero dynamics equation. The proposed control strategy is proposed with consideration of the performance and stability of the input–output linearized dynamics. Simulation results show that the proposed control strategy improves the transient performance of the system compared to the previous results even in the lightly damped operating range.

Input–output linearization of non-linear time-varying delay systems: the single-input single-output case

Abstract This paper deals with the input–output linearization of non-linear time-varying delay systems. We introduce an extension of the Lie derivative for time-varying delay systems and derive sufficient conditions for the existence of a causal and bounded non-linear feedback linearizing the input–output behaviour of the system. Sufficient conditions ensuring the internal stability after output stabilization are also presented. Finally, several examples illustrating our main results are discussed.

Shared invariance control for constraint satisfaction in multi-robot systems

In systems involving multiple intelligent agents, e.g. multi-robot systems, the satisfaction of environmental, inter-agent, and task constraints is essential to ensure safe and successful task execution. This requires a constraint enforcing control scheme, which is able to allocate and distribute the required evasive control actions adequately among the agents, ideally according to the role of the agents or the importance of the executed tasks. In this work, we propose a shared invariance control scheme in combination with a suitable agent prioritization to control multiple agents safely and reliably. Based on the projection of the constraints into the input spaces of the individual agents using input–output linearization, shared invariance control determines constraint enforcing control inputs and facilitates implementation in a distributed manner. In order to allow for shared evasive actions, the control approach introduces weighting factors derived from a two-stage prioritization scheme, which allots the weights according to a variety of factors such as a fixed task priority, the number of constraints affecting each agent or a manipulability measure. The proposed control scheme is proven to guarantee constraint satisfaction. The approach is illustrated in simulations and an experimental evaluation on a dual-arm robotic platform.

Beyond Snap-In: A Hybrid Nonlinear Control Approach for Actuators Possessing a Square-Law Characteristic

The undesired square-law characteristics in micro-electrostatic actuators and magnetic solenoids results in a limited stable range, which reduces their application fields and performance. This research investigated the isomorphic dynamics in these actuators and observed that the nonlinear drive force and the uncertain time delay are the challenges for the full range position controller design. A hybrid nonlinear control scheme includes an input–output linearization controller and a feedback posicast compensator for targeting these problems with abundant stability margin. The experimental results show that the stable range has been extended from 33% to 80%. Furthermore, it is the first literature report of this type of actuator that can track sinusoidal motion beyond the conventional stable range with an amplitude of 70% of the total range. This contribution can significantly enhance the performance of micro-sensors or expand the usage of electrostatic/magnetic actuators in motion-control systems.

Design of a central feedforward control of torque vectoring and rear-wheel steering to beneficially use tyre information

ABSTRACT This paper presents the design of a central feedforward control for the two chassis control systems rear-wheel steering (RWS) and torque vectoring (TV) which have related areas of intervention in lateral dynamics. A control strategy is presented in order to follow desired target values consisting of yaw acceleration and sideslip angle velocity. Central attention is given to the use of additional tyre information with the aim of enhancing vehicle handling and stability. With the knowledge of the mounted tyre type, an adaption law for the desired target values is derived. Although the focus is based on the usage of new tyre information, this modelling approach basically has the potential to reduce the need for coordination among the two systems RWS and TV, exploiting the synergies between both of them. Starting from an extended single-track model an exact Input–output linearisation method is used to design the feedforward control. This is followed by a proof of stability for the external and the internal dynamics of the controller. For the subsequent investigation, in a preliminary step, real-world in vehicle tests are carried out under varying tyre types with a wide spreading of characteristics. This serves as a basis to identify the most important tyre parameters for the controller and to derive the target goals. Finally, the controller is implemented in a 14-DOF non-linear entire vehicle model in Matlab/Simulink, that serves for simulations with a virtual vehicle plant. The performance of the presented feedforward control is assessed by specified objective criteria for steady-state and transient open-loop manoeuvres in lateral dynamics. These criteria are used to investigate the effectiveness of the control design with the aim to achieve the defined target motion. In addition to that, the manoeuvre results also serve to evaluate the control effort, involved in the coordinated cooperation of both systems.