Disturbance Observer Design Research Articles

Adaptive composite neural network disturbance observer-based dynamic surface control for electrically driven robotic manipulators

This paper presents an adaptive backstepping control scheme for electrically driven robotic manipulator (EDRM) system with uncertainties and external disturbances by using neural network disturbance observer (NNDO) and dynamic surface control (DSC) design technique. NNDO is employed to estimate the uncertainties and external disturbances such that the priori information of the unknown dynamics will not be needed. To overcome the problem of “explosion of complexity” inherent in the backstepping design method, the DSC technique is integrated into the adaptive backstepping control design framework, where the NNDOs with adaptive composite law are utilized to compensate the uncertainties and external disturbances of EDRM. Based on the Lyapunov stability theory, it can be proven that the closed-loop system is stable in the sense that all the variables are guaranteed to be uniformly ultimately bounded. The results of simulation and experimental tests demonstrate the approximation capability of NNDO and the effectiveness of the proposed adaptive DSC scheme.

Optimal Disturbance Observer Design for High Tracking Performance in Motion Control Systems

In this paper, a stability-driven optimal disturbance observer (DO) is proposed. The proposed method does not require any plant inverse dynamics to detect introduced disturbances or a stabilizing Q filter. It does not require additional compensators to resolve causality problems, due to the relative degree, or filters to solve instability problems of non-minimum phase plants. Using this method enables wideband and narrowband disturbances to be attenuated by simply multiplying the corresponding peak filters by the baseline weight function. Furthermore, the proposed DO guarantees the stability of closed-loop systems because the already designed outer-loop systems are considered as a target plant to be stabilized and because of the Lyapunov stability-based H∞ control. In the application example, it was confirmed that the proposed method is effective, and the position error signals were improved by 20.9% in commercial hard disk drives and 36.6% in optical image stabilization systems.

측정 잡음을 고려한 1기 무한모선 시스템의 고장 판별을 위한 DQN 기반 외란 관측기 설계

Increasing demand on electric power supply results in a need of an intelligent method for fast detection of various failures in the power system. This paper presents a reinforcement learning-based disturbance observer (DOB) design for the determination and protection against a line fault occurred in the single-machine infinite bus (SMIB) power system. Whilst a high gain disturbance observer could estimate the system states and the external disturbance successfully, the high gain of the observer can cause problems in the presence of the measurement noise. When measurement noise exists in the output, fault detection methods based on the estimated states may often result in false alarms. To solve the problem, this paper designs an adaptive DOB using Deep Q-Network (DQN) which is one of reinforcement learning algorithms. For the proposed observer design, this paper explains the definitions of the state, the action, and the reward for the reinforcement learning. Matlab simulations have been conducted based on the observer gains trained using the power angle data from the swing equation. The results show that the estimation performance of the proposed DQN-based observer can be satisfactory against both an external disturbance and the measurement noise.

Diesel Engine Airpath Controller Via Data Driven Disturbance Observer

This study presents a novel data driven disturbance observer design method and its integration with a recursive controller developed for diesel engine airpath control problem. Mass Air Flow (MAF) and Manifold Absolute Pressure (MAP) are identified with Multi-Input Single-Output NFIR models using experimental data. Heavy-duty diesel engine airpath with variable geometry turbine (VGT) and exhaust gas recirculation (EGR) valve is the main focus of the paper. Presented data driven disturbance observer and controller are implemented to a serial production level engine embedded software. The proposed controllers are compared with the available commercial controllers in dynamometer test cycles. Better overall performance is achieved with respect to the commercial controllers using proposed easy-to-tune controllers.

Designing an interval type-2 fuzzy disturbance observer for a class of nonlinear systems based on modified particle swarm optimization

This paper presents a new interval type-2 fuzzy disturbance observer design for a class of nonlinear systems using modified particle swarm optimization. The design procedure has two main parts, including the selection of the initial structure of the type-2 fuzzy disturbance observer, and the optimization of the observer parameters using a modified particle swarm optimization algorithm. The modified particle swarm optimization algorithm has a better performance in terms of the accuracy and convergence rate compared with the standard particle swarm optimization and many other evolutionary algorithms. In this algorithm, the upper and lower bounds of the search space are defined for the parameters of each particle based on their values, and weaker particles are substituted with new particles. To accentuate the outstanding performance of the modified particle swarm optimization for the considered task, its performance is compared with five famous meta-heuristic optimization algorithms. In addition, utilizing interval type-2 fuzzy systems in the proposed observer provides more robustness compared with type-1 fuzzy systems. The effectiveness of the proposed fuzzy disturbance observer is shown through computer simulation and experimental results for the ball and beam system, while the system is subjected to sinusoid and square disturbances, and a comparison is drawn to indicate the superiority of the proposed fuzzy disturbance observer over the other observers.

Disturbance observer-based control for small nonlinear UAV systems with transient performance constraint

Small UAVs are a class of nonlinear systems with unknown dynamics and uncertainties. This paper proposes a disturbance observer-based (DOB) control scheme with transient performance design for such small UAV systems. In order to strictly guarantee both steady-state and transient observation performance, the idea of prescribed performance function (PPF) is incorporated into the disturbance observer design by transforming an estimation problem into a control problem. Then by utilizing backstepping technique to design the certain part of UAVs, virtual control is updated to compensate the mismatched items of the observed disturbances, where system stability is rigorously proved. Finally, comparative simulations with nonlinear UAV systems are conducted to validate the improved response and the robustness of the proposed control method.

An Iterative Approach for Accurate Dynamic Model Identification of Industrial Robots

Dynamic model has broad applications in motion planning, feedforward controller design, and disturbance observer design. Particularly, with the increasing application of model-based control in industrial robots, there has been a resurgence of research interest in accurate identification of dynamic models. However, on the one hand, most existing identification methods directly rely on least squares or weighted least squares (WLS), which suffer from outliers and could lead to physical infeasible solutions. On the other hand, nonlinearity of the friction model is seldom treated in a unified way with linear regression. Moreover, recent researches have shown that proper exciting trajectories are crucial to the identification accuracy, but few of previous works take measurement noise into consideration when optimizing the exciting trajectories. In this article, we propose an iterative approach which integrates WLS, iteratively reweighted least squares with linear matrix inequality constraints, and nonlinear friction models so that the above-mentioned issues can be properly solved altogether. Our research also reveals that performance can be improved by including priori knowledge of measurement noise in the optimization of exciting trajectories. The proposed approach is supported by experimental analysis of four different combinations within the framework on a 6-DoF industrial robot.

Novel robust disturbance observer

In this paper, a predictive disturbance observer (DOB) design is presented. The proposed DOB does not require a direct model of the process without the transport delay for prediction purposes. The primary advantage of the proposed DOB design is its simplicity due to usage of the prediction block (PB), which approximates the ideal anticipation object. Furthermore, the entire DOB becomes robust to external disturbances because the DOB is based on the approximation of the anticipation object. The response accuracy of the proposed predictive DOB is directly dependent on the inverse model parameters and prediction coefficients in the PB. Notwithstanding the simplification, convenient implementation, identification, and optimization structure, the proposed solution allows for direct implementation of process models describing discontinuous nonlinear time-invariant systems.

Finite‐time tracking control for a class of nonlinear systems with multiple mismatched disturbances

SummaryThis article investigates the finite‐time output tracking problem for a class of nonlinear systems with multiple mismatched disturbances. To efficiently estimate the disturbances and their derivatives, a continuous finite‐time disturbance observer (CFTDO) design method is developed. Based on the modified adding a power integrator method and CFTDO technique, a composite tracking controller is constructed such that the system output can track the desired reference signal in finite time. Simulation results demonstrate the effectiveness of the proposed control approach.

Design of a Low-Order Harmonic Disturbance Observer with Application to a DC Motor Position Control

Among various tools implemented to counteract undesired effects of time-varying uncertainties, disturbance observer (DOB)-based controller has gained wide popularity as a result of its flexibility and efficacy. In this paper, a low-order DOB that is capable of compensating for the effects of a biased harmonic disturbance, as well as plant uncertainties is presented. The proposed low-order DOB can asymptotically estimate a harmonic disturbance of known frequency but unknown amplitude and phase, by using measurable output variables. An analysis carried out by using the singular perturbation theory shows that the nominal performance of the system can be recovered from a real uncertain system when the observer gain is sufficiently large. The observer gains that result in the performance recovery of the real uncertain system are obtained from the stability condition of the boundary-layer system. To test the performance of the proposed observer, computer simulations with a numerical example and laboratory experiments using a DC motor system have been carried out. The experimental results show that the proposed low-order DOB-based control scheme can provide enhanced performance.

Adaptive disturbance observer for trajectory tracking control of underwater vehicles

Complex and highly coupled dynamics, time-variance, unpredictable disturbances and lack of knowledge of hydrodynamic parameters, complicate the control of underwater vehicles. This paper deals with the adaptive disturbance observer design for the robust trajectory tracking problem for underwater vehicles in presence of unknown external disturbances and parametric uncertainties. First, the dynamics of the vehicle is transformed into the so-called regular form. Then, based on the Extended State Observer technique and High Order Sliding Modes Control, a disturbance observer is proposed. Furthermore, the gains of the observer are automatically adjusted by the introduction of an adaption law. The stability of the whole controller/observer scheme is proven using Lyapunov’s arguments. The adaptive disturbance observer aims to improve the Backstepping and nonlinear PD controllers. Real-Time experiments demonstrate the effectiveness of the proposed algorithm for the trajectory tracking task under several scenarios.

An H∞ Design of Disturbance Observer for a Class of Linear Time-invariant Single-input/Single-output Systems

In the paper, a generalized H∞ framework for design of a disturbance observer (DOB) is newly presented for a class of linear time-invariant single-input/single-output systems. Motivated by the systematic synthesis of a stabilizing controller through the H∞ optimization, we formulate the DOB design method into an H∞ design problem with weighting functions in the frequency domain. Thanks to its generality, the proposed method can be consistently applied either to the unstable systems or the non-minimum phase systems. Through the examples, the efficacy of the method is validated.

A Generalized Design Method for Learning-Based Disturbance Observer

This article presents a generalized disturbance observer (DOB) design framework that is applicable to both multi-input multi-output (MIMO) and/or nonminimum phase systems. The design framework removes conventional DOB's structure constraint, which allows minimizing the H-infinity norm of the dynamics from disturbance to its estimation error over a larger feasible set. The design procedure does not require explicit plant inverse, which is usually challenging to obtain for MIMO or nonminimum phase systems. Furthermore, the generalized DOB is augmented by a learning scheme, which is motivated by iterative learning control, to further enhance the estimation and suppression of the disturbance when it has repetitive components. Both numerical and experimental studies are performed to validate the proposed learning-based DOB design framework.

Frequency Response Data-based Disturbance Observer Design via Convex Optimization

To estimate and compensate disturbances effectively, disturbance observer (DOB) has been widely employed in industrial field. This paper is dedicated to designing DOB by directly utilizing frequency response data. By transforming all the non-convex constraints into convex form, the bandwidth of DOB is maximized through iterative convex optimization process. Simulation results have verified the effectiveness of the proposed method.

Nonlinear Signal-Filtering Technique With Real-Time Gain Booster for Feedback System Applications

This letter devises a novel signal-filtering technique subject to the feedback structure without the exact source signal dynamics information. The main idea of this result is comprised of two parts: first, the combination of the Luenberger and disturbance observer design techniques to improve the disturbance rejection capability in the feedback structure; second, the closed-form filtering gain-boosting mechanism updating the gain into the direction of the filtering error reduction. It is experimentally confirmed that the proposed filter contributes to lowering the current regulation performance degradation level from the filtering performance improvement using a 500-W permanent-magnet synchronous motor driven by the three-phase inverter.

Disturbance-Observer-Based Control for Dual-Stage Grid-Tied Photovoltaic System Under Unbalanced Grid Voltages

This paper presents the design and experimental validation of disturbance observer (DO)-based control for grid-tied photovoltaic (PV) inverters fed by a dc–dc boost converter considering unbalanced grid voltages. The control scheme uses multiples controllers that are developed based on employing DO technique along with a feedback-linearizing (FBL) control. The main controller is designed to regulate the active and reactive powers injected into the grid via controlling the grid-tied inverter. Under unbalanced grid voltages, the active and reactive power is composed of a dc component as well as an ac component that oscillates at twice the grid frequency. Therefore, the unknown perturbation, representing the mismatch between the nominal and actual system, can be treated as a sum of a constant offset and a sinusoidal disturbance. To ensure accurate control of the active/reactive power, a DO is designed to estimate the unknown perturbation, which is then canceled by a FBL control. By considering the control input limitation in the observer synthesis, an antiwindup compensator arises naturally in the control law, which attenuates the effect of the windup phenomenon during control saturation. Moreover, a simplified representation of the DO is proposed to facilitate real-time implementation. The proposed approach for the power control can be used in both balanced and unbalanced systems since it can reject constant and sinusoidal disturbances. Experimental tests were performed to investigate the ability of the proposed control scheme to achieve good transient and steady-state performances.

1기 무한모선 시스템의 선로 고장판별을 위한 강화학습 기반 외란관측기 설계

1기 무한모선 시스템의 선로 고장판별을 위한 강화학습 기반 외란관측기 설계

Disturbance Observer Design for Nonlinear Systems Represented by Input–Output Models

A new approach to the design of nonlinear disturbance observers (DOBs) for a class of nonlinear systems described by input–output differential equations is presented in this paper. In contrast with established forms of nonlinear DOBs, the most important feature of this new type of DOB is that only measurement of the output variable is required, rather than the state variables. An inverse simulation model is first constructed based on knowledge of the structure and parameters of a conventional model of the system. The disturbance can then be estimated by comparing the output of the inverse model and the input of the original nonlinear system. Mathematical analysis demonstrates the convergence of this new form of nonlinear DOB. The approach has been applied to disturbance estimation for a linear system and a new form of linear DOB has been developed. The differences between the proposed linear DOB and the conventional form of frequency-domain DOB are discussed through a numerical example. Finally, the nonlinear DOB design method is illustrated through an application involving a simulation of a jacketed continuous stirred tank reactor system.

비선형 동적시스템에 대한 비선형 미분 외란관측기를 이용한 유한시간 Dynamic Surface 제어기 설계

This study proposes a finite-time dynamic surface control (DSC) combined with a nonlinear differentiator disturbance observer for nonlinear systems, in which dynamics are partially known. The nonlinear differentiator disturbance observer, virtual stabilizing controllers, and final controller were designed based on finite-time convergent theorem via the recursive steps in conventional DSC system. In conclusion, the study results show that the filtered output error due to the first-order filter in a conventional DSC, which is the source of controller design complexity and stability, can be bypassed; this is because stability is provided by a finite-time Lyapunov function comprised of newly defined variables instead of the tracking error variables used in conventional DSCs. Thus, the controller design procedure and stability analysis can be more intuitive than those of a conventional DSC. Another important study result is the design of a nonlinear differentiator disturbance observer for nonlinear systems to estimate uncertainty in finite-time. The study shows that very competitive results can be achieved using the proposed method, as shown by the simulation results for an articulated manipulator system.

Composite anti-disturbance control for uncertain Markovian jump systems with actuator saturation based disturbance observer and adaptive neural network

This paper studies the problem of composite control for a class of uncertain Markovian jump systems (MJSs) with partial known transition rates, multiple disturbances and actuator saturation. Compared with the existing results, a novel robust composite control scheme is put forward by virtue of adaptive neural network technique. For MJSs, the partial unknown information on transition rates and the actuator saturation influence the design of disturbance observer and the robust H∞ controller. Firstly, without taking account of external disturbances, the network reconstruction error and saturation, a novel robust adaptive control strategy is established to ensure that all the signals of the closed-loop system are asymptotically bounded in mean square. Secondly, the solvability condition for ensuring the robust H∞ performance is given by using a modified adaptive law, where the saturation is treated as a disturbance-like signal. Finally, the simulations for a numerical example and an application example are performed to validate the effectiveness of the proposed results.