Feedback Linearization Scheme Research Articles

Disturbance rejection tube model predictive levitation control of maglev trains

Magnetic levitation control technology plays a significant role in maglev trains. Designing a controller for the levitation system is challenging due to the strong nonlinearity, open-loop instability, and the need for fast response and security. In this paper, we propose a Disturbance-Observe-based Tube Model Predictive Levitation Control (DO-TMPLC) scheme combined with a feedback linearization strategy for the levitation system. The proposed strategy incorporates state constraints and control input constraints, i.e., the air gap, the vertical velocity, and the current applied to the coil. A feedback linearization strategy is used to cancel the nonlinearity of the tracking error system. Then, a disturbance observer is implemented to actively compensate for disturbances while a TMPLC controller is employed to alleviate the remaining disturbances. Furthermore, we analyze the recursive feasibility and input-to-state stability of the closed-loop system. The simulation results indicate the efficacy of the proposed control strategy.

Secrecy Capacity Region of the AWGN MAC with External Eavesdropper and Feedback.

For the point-to-point additive white Gaussian noise (AWGN) channel with an eavesdropper and feedback, it has already been shown that the secrecy capacity can be achieved by a secret key-based feedback scheme, where the channel feedback is used for secret sharing, and then encrypting the transmitted message by the shared key. By secret sharing, any capacity-achieving coding scheme for the AWGN channel without feedback can be secure by itself, which indicates that the capacity of the same model without the secrecy constraint also affords an achievable secrecy rate to the AWGN channel with an eavesdropper and feedback. Then it is natural to ask: is the secret key-based feedback scheme still the optimal scheme for the AWGN multiple-access channel (MAC) with an external eavesdropper and channel feedback (AWGN-MAC-E-CF), namely, achieving the secrecy capacity region of the AWGN-MAC-E-CF? In this paper, we show that the answer to the aforementioned question is no, and propose the optimal feedback coding scheme for the AWGN-MAC-E-CF, which combines an existing linear feedback scheme for the AWGN MAC with feedback and the secret key scheme in the literature. This paper provides a way to find optimal coding schemes for AWGN multi-user channels in the presence of an external eavesdropper and channel feedback.

Machine Learning-Based Linearization Schemes for Radio Over Fiber Systems

This work proposes a novel machine learning (ML)-based linearization scheme for radio-over-fiber (RoF) systems with external modulation. The proposed approach has the advantage of not requiring new training campaigns in case the Mach-Zehnder modulator (MZM) parameters are changed over time. Our innovative digital pre-distortion (DPD) was designed to favor enhanced remote areas (eRAC) scenarios, in which the non-linearities introduced by the MZM become more severe. It employs a multi-layer perceptron (MLP) artificial neural network (ANN) to model the RoF system and estimate its post-inverse response, which is then applied to the DPD block. We investigate the ML-based DPD performance in terms of adjacent channel leakage ratio (ACLR), normalized mean square error (NMSE), resultant signal root mean square error vector magnitude error (EVM <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$_\mathrm{RMS}$</tex-math></inline-formula> ), and complexity. Numerical results demonstrate that the intended DPD method is less complex and outperforms the orthogonal scalar feedback linearization (OSFL) scheme, which has been considered a state-of-the-art DPD technique. The proposal has the potential to effectively and efficiently compensate for the RoF nonlinear distortions, especially in a time-variant system, without needing new training campaigns.

Nonlinear Modeling and Feedback Control of Boom Barrier Automation

We address modeling and control of a gate access automation system. A model of the mechatronic system is derived and identified. Then, an approximate explicit feedback linearization scheme is proposed, which ensures almost linear response between the electronic driver duty cycle input and the delivered torque. A nonlinear optimization problem is solved offline to generate a feasible trajectory associated with a feedforward action, and a low-level feedback controller is designed to track it. The feedback gains can be conveniently tuned by solving a set of convex linear matrix inequalities, performing a multiobjective tradeoff between disturbance attenuation and transient response. The proposed control strategy is tested on an industrial device. The experiments show that it can effectively meet the requirements in terms of robustness, load disturbance rejection, and tracking performance.

Design of adaptive flight control law for center of gravity and mass variation and HIL real-time simulation verification

Considering the influence of the center of gravity (CG) and mass variations on flight dynamics, a nonlinear L1 adaptive control approach is presented in this paper and applied to design a flight controller to achieve the aim of improving the robustness of the flight system against sudden changes in the CG. Based on L1 adaptive control, this approach introduces a feedback linearization strategy to eliminate the known nonlinear dynamics of the aircraft and realize the rapid decoupling of the aircraft states. The nonlinear L1 adaptive control also addresses the problem of insufficient robustness in conventional L1 adaptive control due to overcoming its own known nonlinearities, and then improves the robustness to external disturbances. Additionally, the modified piecewise constant is employed to design the adaptive law to improve the estimation accuracy. Finally, the control performance and robustness of the designed flight control law are verified in the hardware in the loop (HIL) flight control semi-physical experimental platform. Experimental results indicate that the nonlinear L1 adaptive flight control law has strong robustness, which can effectively overcome the disturbance of the CG and mass sudden variations. Moreover, the designed controller takes into account the transient performance while ensuring the steady-state performance of the aircraft with CG change.

Nonlinear Control of a Two-Stage Single-Phase DC–AC Converter

In this article, a multi-input multi-output nonlinear control strategy for a two-stage single-phase dc–ac converter is introduced. The design technique is based on a multi-input multi-output feedback linearization strategy. A change of coordinates is used for obtaining a decoupled two-input two-output linear description. It allows us to design a linear controller in a transformed domain. Finally, this linear controller is expressed in original coordinates, resulting in the proposed nonlinear controller. Using this nonlinear controller allows improving the performance of the converter in presence of large excursions of reference and disturbance signals. The performance of the whole system is tested via simulation and experimental results using both linear and nonlinear loads.

Robust Nonlinear Controller Design for DC–AC Converter in Grid-Connected Fuel Cell System

This article presents a robust nonlinear controller for distributed fuel cell in the three-phase grid-connected system. A partial feedback linearization scheme is applied to linearize the grid-connected fuel cell system. The mismatches between the actual system and the dynamical model are considered uncertainties. The noise decoupling capability of the feedback linearized control scheme is also demonstrated. A loop-shaping-based <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$\text{H}_\infty$</tex-math></inline-formula> mixed-sensitivity controller is designed for the partially linearized plant of the grid-connected fuel cell system. Performance of the designed controller is investigated under power factor changes, three-phase short-circuit fault, parameter variation, and measurement noise in a hardware-in-loop simulation platform with OP 4510.

Shaking table control via real-time inversion of hydraulic servoactuator linear state-space model

In this work, a Model-Based Control method for a single horizontal degree of freedom shaking table is presented. The proposed approach relies on the real-time inversion of a previously identified linear state-space model of the hydraulic servoactuator which drives the table. The inputs to the model are the control command and the force exerted on servoactuator rod. The latter contains all the relevant information related to the external actions acting on the servoactuator, thus making control system performance independent from the specimen with which the table is loaded and enabling it to cope with specimen non-linear behavior and eventual external forces exerted on it. A parallel proportional integral derivative controller, which accounts for non-modeled dynamics and a feedback linearization scheme, aimed at minimizing servovalve flow non-linearity, complement the previous architecture. The effectiveness of the method has been assessed numerically. According to the simulation results, the performance of the proposed technique appears quite promising; however, several factors must be carefully considered to achieve successful actual implementation.

Sliding mode controller for extraction and supply of photovoltaic power using switched series parallel sources reduced switch count multilevel inverter

The reduced switch count multilevel inverter (RSC-MLI) is the latest trend in power electronic converters due to reduction in the switch count and cost. However, a large number of RSC-MLIs have not yet reached to the application level because of the absence of modularity, unequal load-sharing among DC sources and the absence of switching redundancies. On the other hand, multilevel dc-link (MLDCL) and switched series parallel sources (SSPS) RSC-MLI topologies are modular structures with adequate switching redundancies and can be an alternative to conventional cascaded H-bridge (CHB) for grid-connected photovoltaic (PV) systems. Therefore, in this paper, a comprehensive comparison among CHB, MLDCL and SSPS topologies has been carried out for grid connected PV application. Based on the outcome, an asymmetric 11 kV three-phase 11-level SSPS RSC-MLI is chosen. In this combination, a common non-linear sliding mode controller (SMC) is developed for generating maximum PV power from asymmetric single-stage PV sources by linearizing the non-linear PV system using an effective feedback linearization scheme. The PV power extracted is delivered to the grid by controlling SSPS RSC-MLI using another SMC. The performance of the system under wide variations of insolation levels is verified in MATLAB and further validated in hardware-in-the-loop OPAL-RT controller.

A Shake Table Frequency-Time Control Method Based on Inverse Model Identification and Servoactuator Feedback-Linearization

Shake tables are one of the most widespread means to perform vibration testing due to their ability to capture structural dynamic behavior. The shake table acceleration control problem represents a challenging task due to the inherent non-linearities associated to hydraulic servoactuators, their low hydraulic resonance frequencies and the high frequency content of the target signals, among other factors. In this work, a new shake table control method is presented. The procedure relies on identifying the Frequency Response Function between the time derivative of pressure force exerted on the actuator’s piston rod and the resultant acceleration at the control point. Then, the Impedance Function is calculated, and the required pressure force time variation is estimated by multiplying the impedance by the target acceleration profile in frequency domain. The pressure force time derivative profile can be directly imposed on an actuator’s piston by means of a feedback linearization scheme, which approximately cancels out the actuator’s non-linearities leaving only those related to structure under test present in the control loop. The previous architecture is completed with a parallel Three Variable Controller to deal with disturbances. The effectiveness of the proposed method is demonstrated via simulations carried over a non-linear model of a one degree of freedom shake table, both in electrical noise free and contaminated scenarios. Numerical experiments results show an accurate tracking of the target acceleration profile and better performance than traditional control approaches, thus confirming the potential of the proposed method for its implementation in actual systems.

An Adaptive Partial Feedback Linearizing Control Scheme: An Application to a Single Machine Infinite Bus System

A new form of nonlinear control scheme is presented in this brief where the concepts of feedback linearization and adaptive control schemes are combined together to design an adaptive partial feedback linearizing controller. The newly proposed scheme is exercised on a single machine infinite bus (SMIB) power system in order to design its excitation controller in order to eliminate the parameter sensitivity problems of the feedback linearization scheme. The SMIB system is first linearized using the partial feedback linearization technique and the parameters appearing in the feedback linearized model are estimated using the adaptive control scheme. The proposed adaptive partial feedback linearizing excitation controller of the SMIB system uses the estimated values of parameters. The stability of the SMIB system is also analyzed using the Lyapunov stability theory while using the proposed scheme. Simulation studies are carried out to demonstrate the effectiveness of the proposed control scheme over an existing partial feedback linearizing scheme.

Robust Nonlinear Adaptive Feedback Linearizing Decentralized Controller Design for Islanded DC Microgrids

This paper presents a robust nonlinear decentralized control scheme for islanded dc microgrids, where the main control objectives are to achieve the desired voltage at the common dc bus and to maintain the power balance. The proposed control scheme uses the partial feedback linearization scheme to simplify the dynamical models of different components in dc microgrids. In this paper, the dc microgrid includes a solar photovoltaic unit, a fuel cell system, and a battery energy storage system along with dc loads. The robustness of the proposed controller against parametric uncertainties is ensured by the parameter, appearing in the control inputs as unknown, which is then estimated through adaptation laws. The inherent noise decoupling capability of the feedback linearization scheme is used to provide robustness against external disturbances in dc microgrids. The performance of the proposed controller is evaluated on a dc microgrid through simulation and experimental studies in order to demonstrate the effectiveness and robustness under different operating conditions, while considering the effects of parametric uncertainties and external disturbances. Simulation results are also compared with an existing proportional-integral controller.

Experimental verification of a hybrid control scheme with chaotic whale optimization algorithm for nonlinear gantry crane: A comparative study

This paper proposes an experimental verification of a hybrid partial feedback linearization (PFL) and deadbeat (DB) control scheme as in Hamdy et al. (2018) with chaotic whale optimization algorithm (CWOA) for a nonlinear gantry crane (GC) system. The PFL linearizes the nonlinear model to end up with a linear closed-loop system. The DB controller is utilized for the desirable accelerated response without any oscillation or undesirable effects on the internal dynamics stability. The CWOA is used to tune the controller parameters. A sliding-mode observer (SMO) is utilized to estimate the unmeasured states. Using this hybrid scheme, a better payload sway elimination can be obtained. Finally, the experimental results are presented to illustrate the efficiency and the effectiveness of the proposed scheme with a comparative study.

Gibbon-inspired Robust Asymmetric Brachiation along an Upward Slope

This paper investigates the robust control of an underactuated brachiating robot. The control schemes are motivated by the applications that require robots to move through lattice structures, such as the inspection and maintenance of power transmission lines and towers. Inspired by the pendulum-like movements that enable gibbons' arboreal locomotion, the controllers are designed to synchronize the brachiator with a virtual oscillator. Two controllers are proposed: a model-dependent feedback linearization scheme and a sliding-mode scheme that is independent of the system model. These controllers are tasked to drive a robotic brachiator in two cases with different geometries: symmetric geometry, where its links have equal lengths, and asymmetric geometry, where its links have different lengths. The numerical results illustrate that the proposed schemes are robust to the arbitrary initial conditions of the brachiator, the motor torque limitation at the elbow joint, as well as the geometry of the brachiator. Furthermore, they are able to perform successful fast swing-up and dynamic brachiating along a structural member with an upward slope in a unified control framework for both symmetric and asymmetric geometries.

The synchronisation of two floating memristor-based oscillators and the circuit design

The synchronisation between two floating memristor-based Colpitts oscillators is studied in this paper. Firstly, the mathematical and circuit models of Colpitts oscillator based on a floating memristor with a diode bridge structure are built. On this basis, numerical simulations on the features of both the independent memristor and the floating memristor are conducted and compared using MATLAB software. Secondly, circuit simulation is made on the synchronisation of two floating memristor-based systems by using MULTISIM software. Finally, the physical circuit on the synchronisation of the two coupling Colpitts systems based on the diode bridge memristors is implemented by using the linear error feedback scheme and improved by the capacitor coupling scheme and the adaptive nonlinear feedback control scheme, respectively. The experimental results by the oscilloscope and simulation results show that approximate synchronisation is achieved.

Nonlinear Three-Port Representation of PAs for Embedded Self-Calibration of Envelope-Dependent Dynamic Biasing Implementations

This paper proposes a three-port power amplifier (PA) representation based on distinct sets of nonlinear complex polynomials that describe a combiner, a nonlinear baseband-to-RF converter and a nonlinear RF amplifying function, for processing the PA's input modulated signal and any envelope-dependent dynamic biasing signal. This novel representation of PA nonlinearities simplifies computation and renders possible analytical formulations to describe a 3-port PA system. It allows accurate prediction of the PA's output distortion components as a function of an input multi-tone excitation and a multi-tone dynamic biasing signal. The representation is intended for a context proposed, to the best of the authors' knowledge for the first time, and envisioned as promising for future mobile communication equipment - the automatic optimization of linearity performance in Radio Frequency Integrated Circuit (RFIC) PAs under any modulated excitation and employing envelope-dependent biasing, through implementation of embedded self-calibration within the transmitter front-ends. In this context, the representation introduced here compares favorably in terms of accuracy with respect to Volterra-based approaches and allows a simpler characterization, while the literature often points to the complexity inherent to Volterra-based approaches. The proposed representation allows the optimization of the PA's dynamic biasing for linearity improvement from one mobile unit to another through embedded self-calibration starting from quasi-static measurements alone of the PA's input/output power. Its applicability is highlighted through benchmarking against experimental results demonstrating accurate PA characterization for multiple PA platforms under different dynamic biasing techniques. In one implementation using an industry-designed GaAs PA, it accurately predicts the dynamic biasing adjustments to achieve more than 4dB reduction in the output intermodulation distortion (IMD3). In another implementation using the recently introduced positive envelope feedback linearization scheme, the proposed representation allows, for the first time, analytically predicting the condition of closed-loop stability and the requirements for the feedback components with experimental verification.

A Local Separation Principle via Dynamic Approximate Feedback and Observer Linearization for a Class of Nonlinear Systems

A separation principle for a class of nonlinear systems inspired by the techniques of feedback linearization and observer design with linear error dynamics is discussed. The output feedback construction combines strategies for approximate feedback linearization and observer design, which are of interest per se , yielding a dynamic control law that ensures a linear, spectrally assignable, behavior from the certainty equivalence input mismatch to the extended state of the system and the observer. The first ingredient, namely the approximate feedback linearization strategy, can be applied, under mild conditions, also to nonlinear systems that are linearly uncontrollable—or that do not possess a well-defined relative degree in the case of a given output function—yet providing a chain of integrators of length equal to the dimension of the state in the transformed coordinates. Interestingly, a systematically designed nonlinear inner loop enables the use of linear design techniques, $\text{e.g.}$ , pole placement. The observer design, on the other hand, employs an additional dynamic extension that allows us to assign the local dynamic behavior of the error dynamics independently from its zeros, differently from the classic high-gain observer design. The paper is concluded by presenting several numerical simulations, including an output tracking control problem for the Ball and Beam model that does not possess a well-defined relative degree.

Maximum Power Point Tracking of DFIG with DC-Based Converter System Using Coordinated Feedback Linearization Control

This paper presents a coordinated feedback linearization strategy (CFLS) for DC-based doubly-fed induction generator (DFIG) system to track the maximum power point. The stator and rotor of DFIG are connected to DC grid directly by two voltage source converters. Compared with a traditional DFIG system, the DC-based DFIG system has more system inputs and coupling, which increases the difficulty of vector control strategy. Accordingly, CFLS is proposed to make DFIG operate at the maximum power point (MPP), and two aspects are improved: first a single-loop control is adopted to make DFIG operate steady and accurate under coordinated the control of RSC and SSC. Second system control laws are obtained by the feedback linearization strategy that achieves DC-based DFIG system decoupling fully during the MPPT and system control. Simulations are carried out the comparison between CFLS and conventional vector control (VC), and it shows that the control performance of CFLS is superior.

Partial Feedback Linearizing Model Predictive Controllers for Multiple Photovoltaic Units Connected to Grids through a Point of Common Coupling

In this paper, partial feedback linearizing model predictive controllers are designed for grid-connected systems comprising multiple photovoltaic (PV) units where these units are connected through a point of common coupling (PCC). The proposed controllers are designed for voltage source inverters (VSIs) based on comprehensive dynamical models of grid-connected PV systems with the proposed topology. The proposed partial feedback linearization scheme decouples multiple PV units in the forms of several reduced-order subsystems and enables linear controller design through the linear continuous-time receding horizon model predictive control scheme. The proposed partial feedback linearization scheme also considers dynamic interactions among multiple PV units as external noises or disturbances and decouples these noises. This paper includes the noise decoupling capability of the partial feedback linearization for grid-connected PV systems with multiple PV units which are connected through a PCC. Simulation results clearly demonstrate the effectiveness of the proposed scheme under different operating conditions as compared to an existing proportional integral controller.

A hybrid partial feedback linearization and deadbeat control scheme for a nonlinear gantry crane

This paper presents the design of a hybrid partial feedback linearization and deadbeat control scheme for a nonlinear gantry crane with friction to control its position and sway angle. The partial feedback linearization is used to linearize the nonlinear model and to stabilize its internal dynamics. In many crane applications, it's necessary to accelerate the system response. As a result, this will cause oscillation in the position as well as the sway angle. So, the deadbeat controller is added to get the desirable accelerated response without any oscillation or adverse effects on the internal dynamics stability. By using Lyapunov stability method, the proposed scheme is proved to be globally stable, with converging tracking errors to the desired performance. The simulation results are accomplished to evaluate the effectiveness of the proposed scheme and to demonstrate its reliability to control crane systems with comparative results.