External Disturbance Rejection Research Articles

Design and implementation of adaptive fuzzy‐RST digital speed control of PMSM drive

AbstractThis research focuses on the speed control design of permanent magnet synchronous motors (PMSMs) drive system. The purpose is to develop and compare advanced control strategies: RST digital (RSTD) control and adaptive fuzzy‐RST digital (AFRSTD) control. The three control schemes proposed, synthesized, and implemented in experimental test bench in order to be evaluated and compared are: conventional PI controller, RSTD controller, and AFRSTD controller based on the proposed fuzzy system which has to adjust the RSTD polynomial coefficients online using gain scheduling technique. The objective is to improve the performances of the PMSM drive system, in order to obtain high dynamic response, an efficiency of external disturbance rejection, and considerable control robustness against parameter variations. The experimental test bench is based on a dSPACE1104 board with a 1.1‐kW PMSM supplied by 10‐kHz space vector pulse width modulation (SVPWM) current regulated inverter used as a power amplifier consisted of 300 V, 5‐A IGBT, and Matlab/Simulink environment. Experimental results confirm that the AFRSTD controller presents better dynamic performances and significant robustness under parameter variation.

Fixed-time disturbance observer-based chattering-free sliding mode attitude tracking control of aircraft with sensor noises

The challenging attitude tracking control problem of aircraft with external disturbance and sensor noises is investigated. A disturbance observer-based control approach is presented. In this approach, a fixed-time disturbance observer is preliminarily developed. The external disturbance is estimated with the estimation error governed to zero after a fixed-time regardless of any initial state. Moreover, with measurement noises explicitly considered, a discrete tracking differentiator extracting the real signals from the polluted measurement is introduced into that fixed-time observer to improve its application potential. Invoking the estimation information, a sliding mode attitude controller is then synthesized. The main feature of the proposed approach is that the closed-loop attitude tracking system is guaranteed to be exponentially stable. External disturbance rejection is achieved, while its upper bound is not required to implement that approach. In contrast to the conventional sliding mode control schemes, the proposed controller is chattering-free. Numerical simulation and experimental tests are finally carried out to verify the effectiveness of the proposed approach.

A novel effective nonlinear state observer based robust nonlinear sliding mode controller for a 6 kW Proton Exchange Membrane Fuel Cell voltage regulation

This paper presents an effective strategy for controlling an Interleaved DC/DC Boost Converter (IBC) that is employed for reducing the current fluctuations in a 6 kW Proton Exchange Membrane Fuel Cell (PEMFC). The proposed design incorporates a new nonlinear control law combined with a nonlinear state observer, it aims at enhancing the durability of the Fuel Cells (FCs) and extending their lifetime. In this regard, a Nonlinear State Observer (NSO) is designed to simultaneously estimate current and voltage signals of the Fuel Cell Source (FCS) and a Nonlinear Sliding Mode Controller (NSMC) is constructed based on these estimates. The proposed sensorless control design is advantageous in avoiding current and voltage sensors redundancy to maintain low cost and complexity levels. Accurate output voltage tracking performance, tracking stability, and dynamic errors for a PEMFC-IBC are considered during changes of the internal model parameters in addition to effects of measurement uncertainties. A third advantage of this design is robustness and external disturbance rejection under large load variations. For these objectives, the observer and the controller parameters are optimally tuned using a recent Metaheuristic Particle Swarm Optimization Algorithm (MPSOA) inspired by the swarm intelligence for improving the dynamic performance of the controlled system. Furthermore, stability and tracking analysis properties of the closed-loop overall system are proved through Lyapunov theory for dynamic operating conditions. Finally, numerical simulations of a typical 6 kW PEMFC system validate the effectiveness of the proposed scheme with comparisons to contemporary approaches across the different cases.

Predictive Controllers for Dual-Voltage Vector Current-Slope Sensorless IPMSM Drives

A rotor position estimation method based on a dual-voltage vector modulation technique for an IPMSM drive system is proposed in this paper. This method effectively increases the differences of the current slope in each switching state when compared to a single-voltage vector modulation technique, and it improves the current tracking capability of the current control as well as the accuracy of the rotor position estimation. The duty cycles of the dual-voltage vectors are systematically derived to generate the PWM switching states of the inverter. By measuring the current slope in each PWM switching state, the rotor position is easily estimated. In addition, the pulse width of the voltage vectors is not too narrow and does not require any extension or compensation. A predictive speed controller and a predictive current controller are designed and implemented to improve the dynamic responses of the drive system. All of the control algorithms, including dual-voltage vector modulation, rotor position estimation, and predictive control are realized through a DSP TMS-320F-2808. Experimental results show the proposed method provides an adjustable speed from 1 r/min to 2000 r/min with good performance, including transient responses, external load disturbance rejection, reversing speed, and tracking capability.

Disturbance-Observer-Based Control of DFIG in Island Mode for Microgrid Applications

This paper introduces a novel control approach for Doubly-Fed Induction Generator (DFIG) operating in island mode based on the cascaded control structure with disturbance estimation. The control of the DFIG is a challenging task due to its inherent nonlinearity, fast dynamics, and unpredictable disturbances acting on the system. The proposed control structure involves a nominal controller for plant and disturbance observer (DOB) in each of the inner and outer control loop. The first-order disturbance observers are designed to estimate the time-varying and unknown disturbances. With disturbance estimation, the nominal linear dynamics is obtained in both loops. This enables the same approach for designing controllers for the inner and outer loop which significantly simplifies implementation. The controllers are designed based on the demanded error dynamics and ensure stable operation of the system, while proposed DOBs estimate disturbances including external load. Finally, the effectiveness and quality of the proposed control structure were verified through numerical simulations in terms of external disturbances rejection and closed-loop tracking performance.

Distributed Nash Equilibrium Seeking for Aggregative Games With Nonlinear Dynamics Under External Disturbances.

In this paper, we study the distributed Nash equilibrium (NE) seeking problem for a class of aggregative games with players described by uncertain perturbed nonlinear dynamics. To seek the NE, each player needs to construct a distributed algorithm based on information of its cost function and the exchanging information obtained from its neighbors. By combining the internal model principle and the average consensus technique, we propose a distributed gradient-based algorithm for the players. This paper not only assures the NE seeking of aggregative games but also achieves the disturbance rejection of external disturbances.

Design and implementation of an interconnection and damping assignment–passivity-based control for grid-integrated hybrid renewable system with energy storage

This article introduces a unified Hamiltonian formulation for controlling grid-connected direct current microgrid via interconnection and damping assignment–passivity-based control. The direct current microgrid includes hydro–solar–wind hybrid renewable energy systems and battery/supercapacitor hybrid energy storage system. Hybrid renewable energy systems are integrated as a disturbed direct current source, while hybrid energy storage system is integrated via semi-active topology, where the battery is connected to the direct current bus through a bidirectional dc-to-dc converter. The proposed Hamiltonian approach allows us to design a control strategy for the bidirectional dc-to-dc converter and the grid-connected three-phase inverter to (1) reject power disturbances in the direct current bus via the supercapacitor and ensure smooth current in the battery as well as in the grid and (2) assign the system to a desired equilibrium after sharp changes. In the studied article, the stability of the system under the interconnection and damping assignment–passivity-based control controller is investigated. The interconnection and damping assignment–passivity-based control controller is compared with two conventional proportional–integral–based controllers through simulations under the MATLAB/Simulink environment. The main contributions in this article are the unified hybrid modelling for dc-to-dc power converter and grid-connected inverter using port-Hamiltonian approach, external disturbance rejection in the multi-source power system using interconnection and damping assignment–passivity-based control, and the assurance of global asymptotic stability of the closed-loop system.

External Disturbances Rejection for Vector Field Sensors in Attitude and Heading Reference Systems.

The attitude and heading reference system (AHRS), which consists of tri-axial magnetometer, accelerometer, and gyroscope, has been widely adopted for three-dimensional attitude determination in recent years. It provides an economical means of passive navigation that only relies on gravity and geomagnetic fields. However, despite the advantages of small size, low cost, and low power, the magnetometer and accelerometer are susceptible to external disturbances, such as the magnetic interference from nearby ferromagnetic objects and current-carrying conductors, as well as the motional acceleration of the carrier. To eliminate such disturbances, a vector-based parallel structure is introduced for the attitude filter design, which can avoid the mutual interference between gravity and geomagnetic vectors. Meanwhile, an approach to estimate and compensate the external disturbances in real time for magnetometer and accelerometer is also presented. Compared with existing designs, the proposed filter architecture and external disturbance rejection algorithm can feasibly and effectively cooperate with mainstream data fusion techniques, including complementary filter and Kalman filter. According to experiment results, in the case that large and persistent external disturbances exist, the proposed method can improve the accuracy and robustness of attitude estimation, and it outperforms the existing methods such as switching filter and adaptive filter. Furthermore, through the experiments, the critical role of fading factor in handling the external disturbance is revealed.

Improved Linear Active Disturbance Rejection Controller Control Considering Bus Voltage Filtering in Permanent Magnet Synchronous Generator

In the permanent magnet direct drive wind power generation system, the direct current (DC) bus voltage signal of the converter is usually used as the feedback of the voltage outer loop. Because of the existence of random white noise and the measurement error when the sensor collects the DC bus voltage signal, it is necessary to filter the bus voltage signal through the first-order inertial link. The time constant of the first order inertial link is usually 10ms-15ms. In the traditional voltage external loop second-order active disturbance rejection controller (ADRC) system, the influence of the bus voltage filter is not considered in the design of ADRC, which results in the phase lag and amplitude offset between the feedback of the controller and the real bus voltage. This will make the performance of the system affected by the time constant of the first-order inertial link. In this paper, an improved ADRC considering the bus voltage filter is proposed. The filtered bus voltage is expanded into a new state variable. The voltage before the filter is estimated by using the fourth-order linear expansion state observer (LESO) and used as the feedback. The simulation results show that the improved ADRC system has better control performance.

Position-based motion control for parallel manipulators under parametric uncertainties and with finite-time external disturbance rejection

We consider the task of motion control for non-prehensile manipulation using parallel kinematics mechatronic setup, in particular, stabilization of a ball on a plate under unmeasured external harmonic disturbances. System parameters are assumed to be unknown, and only a ball position is measurable with a resistive touch sensor. To solve the task we propose a novel passivity-based output control algorithm that can be implemented for unstable linearized systems of an arbitrary relative degree. In contrast to previous works, we describe a new way to parametrize harmonic signal generators and an estimation algorithm with finite-time convergence. This scheme enables fast disturbance cancellation under control signal magnitude constraints.

SYNTHRSIS OF QUADROTOR ROBUST GUIDANCE AND CONTROL SYSTEM VIA PARAMETERIZATION OF ALL STABILIZING Н-INFINITY STATE-FEEDBACK GAINS

The main purpose of the research is to develop the quadrotor robust control system adapted to the rejection of external disturbances. The methodology of control system synthesis is based on the parameterization of all stabilizing H-infinity static state feedback gains with applications to output feedback design. The main feature of the article is the development of the above-mentioned method relative to the quadrotor. The main results of the article are synthesized control laws and simulation of the closed-loop dynamics. The basic practical implication is the usage of synthesized control laws in guidance of the quadrotor motion in path following of circular and linear-piecewise reference tracks. Originality and value of the article are caused by the necessity to improve the quality of control by quadrotor motion.

Hybrid Coarse and Fine Controller Tuning Strategy for Magnetic Levitation System

The magnetic levitation system requires a finely tuned controller to suspend a ball in the air. Any imbalance in the force balance condition might result in high fluctuations causing the ball to fall out of levitation. A hybrid tuning strategy based on successful levitation and minimization of vibrations has been designed and tested in real time. The proportional–integral–derivative controller has been tuned in two stages. The parameters of the controller have been calculated by the traditional pole placement technique for coarse tuning and evaluation of bounds. Nature-based non-traditional optimization techniques have been used to minimize the integral of the absolute error within this threshold limit for finer tuning. This novel strategy has been employed to find the best combination of the controller parameters such that levitation is ensured by coarse tuning and error is minimized by fine tuning. Real-time robustness analysis has also been done by means of rejection of external disturbance induced manually in the levitated stage.

Motion control of self-driving vehicles on rough roads

Control of self-driving vehicles is one of the-up-to-date tasks. Vehicles are non-linear dynamic systems with a large number of parameters. When it is supposed to move on a rough road with a lot of abrupt turns, significant unpredictable and unmeasurable disturbances emerge and the control quality degrades significantly. We implemented model predictive path integral (MPPI) control to deal with significant unmeasured disturbances. To approve efficiency of the proposed controller, we conducted simulation of complex car motion on a plane under the control of PID, and MPPI controllers. Performance of controllers is comparatively equal in stable modes, when reference position and velocity do not change. MPPI controllers outperform PID ones in unstable modes due to their ability to predict a vehicle behavior. Also, MPPI is the best choice for the rejection of significant external disturbances.

Model-based model predictive control for a direct-driven permanent magnet synchronous generator with internal and external disturbances

This paper deals with the critical issue in a direct-driven permanent magnet synchronous generator (PMSG)-based wind energy conversion system (WECS): the rejection of internal and external disturbances, including the uncertainties of external environment, rapid wind speed changes in the original parameters of the generator caused by mutative operating conditions. To track the maximum power, a maximum power point tracking strategy based on model predictive controller (MPC) is proposed with extended state observer (ESO) to attenuate the disturbances and uncertainties. In real application, system inertia and the system parameters vary in a wide range with variations of wind speeds and disturbances, which substantially degrade the maximum power tracking performance of wind turbine. The MPC design should incorporate the available model information into the ESO to improve the control efficiency. Based on this principle, a model-based MPC with ESO control structure is proposed in this paper. Simulation study is conducted to evaluate the performance of the proposed control strategy. It is shown that the effect of internal and external disturbances is compensated in a more effective way compared with the ESO-based MPC approach and traditional proportional integral differential (PID) control method.

Micrometeoroid Events in LISA Pathfinder

Abstract The zodiacal dust complex, a population of dust and small particles that pervades the solar system, provides important insight into the formation and dynamics of planets, comets, asteroids, and other bodies. We present a new set of data obtained from direct measurements of momentum transfer to a spacecraft from individual particle impacts. This technique is made possible by the extreme precision of the instruments flown on the LISA Pathfinder spacecraft, a technology demonstrator for a future space-based gravitational wave observatory. Pathfinder employed a technique known as drag-free control that achieved rejection of external disturbances, including particle impacts, using a micropropulsion system. Using a simple model of the impacts and knowledge of the control system, we show that it is possible to detect impacts and measure properties such as the transferred momentum, direction of travel, and location of impact on the spacecraft. In this paper, we present the results of a systematic search for impacts during 4348 hr of Pathfinder data. We report a total of 54 candidates with transferred momenta ranging from 0.2 to 230 μNs. We furthermore make a comparison of these candidates with models of micrometeoroid populations in the inner solar system, including those resulting from Jupiter-family comets (JFCs), Oort Cloud comets, Halley-type comets, and asteroids. We find that our measured population is consistent with a population dominated by JFCs, with some evidence for a smaller contribution from Halley-type comets, in agreement with consensus models of the zodiacal dust complex in the momentum range sampled by LISA Pathfinder.

Super-twisting ZNN for coordinated motion control of multiple robot manipulators with external disturbances suppression

This paper considers the coordination motion control of multiple robot manipulators by developing a unified framework of super-twisting zeroing neural network (ST-ZNN), and proposes a novel external disturbances suppression model. The proposed ST-ZNN model makes new progresses of both theory and practice by overcoming two limitations in the conventional ZNN (CZNN) models, i.e., the convergence time tending to be infinitely large and the rejection of external disturbances staying at the stage of asymptotic convergence. Then, the global stability, finite-time convergence, and robustness against external disturbances are rigorously proven in the theory. Finally, illustrative coordination motion control tasks, comparisons and performance tests demonstrate the effectiveness and superiority of the proposed ST-ZNN model for coordination motion control of multiple robot manipulators.

Application of an Intelligent Control on Economics Dynamic System: The Attractive Invariant Ellipsoid Approach

In this paper, we explore the application of attractive ellipsoid methodology (Poznyak et al. in Attractive ellipsoids in robust control. Springer, Berlin, 2014) on a new demand and supply model. The balance between the demand and supply is expressed by the Lin and Yang model (Li and Yang in Int J Bifurc Chaos 27(01):1750016, 2017), described by differential equations, even if in the such a demand-supply model, other factors change and have significant effect on demand-supply dynamics. Analysis is compared with the situation when the prices of most products do not stay close to their equilibrium values and the Li and Yang demand and supply model is described by both ordinary differential equation and differential algebraic equation system. To achieve a specific economic goal, we will be able to design a management strategy based on minimum size of the invariant attractive ellipsoid, associated with the dynamic system, with a good performance in the rejection of external disturbances. We can consider a new transformed problem instead of the original problem with respect to solvability and related questions. Theoretical results are illustrated by an example.

A Robust Controller for Multivariable Model Matching System Utilizing a Quantitative Feedback Theory: Application to Magnetic Levitation

This paper proposes a systematic feedback controller design methodology for multi-input multi-output (MIMO) uncertain systems using the quantitative feedback theory (QFT). To achieve this goal, the model matching problem was considered and the inversion feedforward controller was designed to improve control performance while reducing the demand on feedback control alone. The proposed method is formulated based on the concept of equivalent disturbance attenuation (EDA) approach in which the uncertain system problem is converted into an external disturbance rejection problem based on a nominal system. This proposed approach exhibiting non-sequential design method result in the suboptimal solution showing design simplicity and computational efficiency compared to the existing method. In order to validate the effectiveness of the proposed control methodology, the MIMO magnetic levitation system as adopted and control performances such as time response were presented in both time and frequency domains.

Sliding mode control of an active power filter with photovoltaic maximum power tracking

Nowadays, the increase in solar energy installations as a source of energy is growing considerably. The connection to the grid of these installations generally injects all the power obtained from the panel as active power, making zero the reactive power. The same power injection system can be used to achieve a unit power factor if the active filter feature is integrated in it. In this paper, an active power filter (APF) that can control both, the MPP (maximum power point) of a photovoltaic system (PV) and the power factor of a nonlinear load connected to the grid using a three phase DC/AC power inverter with new sliding mode controllers is presented. Perturbation–observation (P&O) is the used MPPT algorithm and three Sliding Mode Controllers (SMC) are used to regulate the DC voltage of the PV and the current d and q components of the active filter using the PQ theory. With a SMC, no exact knowledge of the model parameters is required and it offers good behavior against unmodeled dynamics, insensitivity to parameter variations and good rejection of external disturbances. The space vector pulse wide modulation (SVPWM) of 7 and 5 segments is implemented in order to check the efficiency and grid current ripple. Several experimental tests have been carried in different conditions, concluding that the presented system provides an efficient maximum power tracking and a good power filter characteristic.

Versatile and robust bipedal walking in unknown environments: real-time collision avoidance and disturbance rejection

Autonomous navigation in complex environments featuring obstacles, varying ground compositions, and external disturbances requires real-time motion generation and stabilization simultaneously. In this paper, we present and evaluate a strategy for rejection of external disturbances and real-time motion generation in the presence of obstacles and non-flat ground. We propose different solutions for combining the associated algorithms and analyze them in simulations The promising method is validated in experiments with our robot Lola. We found a hierarchical approach to be effective for solving these complex motion generation problems, because it allows us to decompose the problem into sub-problems that can be tackled separately at different levels. This makes the approach suitable for real-time applications and robust against perturbations and errors. Our results show that real-time motion planning and disturbance rejection can be combined to improve the autonomy of legged robots.