Disturbance Observer Approach Research Articles

Antidisturbance Control for Hidden Markovian Jump Systems: Asynchronous Disturbance Observer Approach

This paper investigates the anti-disturbance control issue for a class of Markovian jump systems (MJSs) with matched/mismatched disturbances by using disturbance observer approach. A key feature here is that the external disturbance is considered to be generated by a Markovian jump exogenous dynamics, in which the disturbance mode may not be synchronized with the system mode. Meanwhile, it is supposed that both system and disturbance modes can just be estimated via a hidden Markov mode detector. To overcome the possible obstacle in handling dual hidden Markov modes, a mapping technique for continuous-time Markov chain is provided firstly. Then, a novel asynchronous disturbance observer is developed to estimate the external disturbance by utilizing the detected mode. Based upon the estimated disturbance, asynchronous anti-disturbance controllers are investigated for matched and mismatched disturbance cases, respectively. By employing a decoupling technique with the idea of completing the square, sufficient conditions are established for guaranteeing the stability in probability of the resultant closed-loop systems. Finally, two numerical examples are provided to verify the effectiveness of the proposed asynchronous anti-disturbance control approaches under inaccessible system and disturbance modes.

Robust Composite H∞ Synchronization of Markov Jump Reaction-Diffusion Neural Networks via a Disturbance Observer-Based Method.

This article focuses on the composite H∞ synchronization problem for jumping reaction-diffusion neural networks (NNs) with multiple kinds of disturbances. Due to the existence of disturbance effects, the performance of the aforementioned system would be degraded; therefore, improving the control performance of closed-loop NNs is the main goal of this article. Notably, for these disturbances, one of them can be described as a norm-bounded, and the other is generated by an exogenous model. In order to reject the above one kind of disturbance, a disturbance observer is developed. Furthermore, combining the disturbance observer approach and conventional state-feedback control scheme, a composite disturbance rejection controller is specifically designed to compensate for the influences of the disturbances. Then, some criteria are established based on the general Lyapunov stability theory, which can ensure that the synchronization error system is stochastically stable and satisfies a fixed H∞ performance level. A simulation example is finally presented to verify the availability of our developed method.

Sliding-mode controller synthesis of robotic manipulator based on a new modified reaching law.

In this study, an adaptive modified reaching law-based switch controller design was developed for robotic manipulator systems using the disturbance observer (DO) approach. Firstly, a standard DO is employed to estimate the unknown disturbances of the plant, from which the control signal could be compensated. Then, an adaptive modified reaching law is established to dynamically adapt the switching gain of the sliding mode robust term and further guarantee the finite-time arrival of the established sliding surface. Additionally, the convergence of the error system is analyzed via the Lyapunov method. At last, the feasibility and effectiveness of the proposed control scheme are verified by using a two-joint robotic manipulator model. The simulation results show that the developed controller can achieve rapid tracking, reduce system chattering and improve the robustness of the plant. The main innovations of the work are as follows. 1) A new adaptive reaching law is proposed; it can reduce chattering effectively, and it has a fast convergence speed. 2) Regarding the nonlinear robotic manipulator model, a novel adaptive sliding-mode controller was synthesized based on the DO to estimate the unknown disturbance and ensure effective tracking of the desired trajectory.

Learning-based Control for Passive Flexible Multirotors (PFMs) with Physical Interaction Abilities

Flexible, deforming aerial vehicles have introduced a paradigm shift in existing research by enabling stable aerial-physical interactions. These vehicles harvest interaction energies to undergo a deformation of the vehicle body and absorb impacts, therefore retaining stability under the action of unknown external forces. The low-level control of such aerial vehicles gets complicated owing to the highly nonlinear and varying dynamics of a passive deforming chassis, coupled with the action of external forces resulting from interactions with the environments. In this work, we propose a morphology-aware Q-learning-based tracking controller that accounts for varying morphology and the various external interaction forces. We train this learning-based controller offline under various case scenarios and then augment an online rollout scheme to improve the tracking performance in case of model-mismatch. Simulation studies are presented that validate the proposed controller in comparison with a conventional disturbance observer approach with improved tracking performance and optimized control effort.

Disturbance Observer-Based Prescribed Performance Fault-Tolerant Control for a Multi-Area Interconnected Power System with a Hybrid Energy Storage System

The goal of this study is to develop a disturbance observer-based prescribed performance fault-tolerant controller (PPFTC) for a multi-area interconnected power system (MIPS) with a hybrid energy storage system (HESS). The mathematical model of the MIPS with HESS is introduced first. Then the load disturbance estimation is obtained using a disturbance observer (DO) approach. By introducing two additional functions, the tracking error is bounded to achieve the desired response. The PPFTC is further developed based on the DO ensuring that the area control error (ACE) of the MIPS asymptotically converges to zero. Finally, the effectiveness of the given PPFTC and DO are inspected through the use of the Lyapunov theory and simulated results.

Robust adaptive dynamic surface back-stepping tracking control of high-order strict-feedback nonlinear systems via disturbance observer approach

In this study, we propose an adaptive tracking dynamic surface back-stepping control based on Nussbaum disturbance observer for uncertain high-order strict-feedback MIMO nonlinear systems with external disturbances, unknown parameters and modelling uncertainties. It is assumed that the control action is affected by input saturation; so to compensate the resulted undesirable effects, the tanh(.) function is used as an approximation to the saturation function. To tackle the unknown external disturbances and uncertainties, a Nussbaum disturbance observer is proposed. Moreover, an appropriate adaptive law is presented to deal with the unknown parameters. Then, the dynamic surface control method is used to overcome the inherent problem ‘explosion of complexity’ that appeared in the conventional back-stepping method. The Lyapunov stability analysis proves that the closed-loop system is semi-globally uniformly bounded. At last, reasonable effectiveness and applicability of the adaptive tracking dynamic surface control are illustrated by simulation results.

Disturbance observer approach for fuel-efficient heavy-duty vehicle platooning

ABSTRACTHeavy-duty vehicle platooning has received much attention as a method to reduce fuel consumption by keeping inter-vehicle distance short. When a platoon follows a fuel-optimal velocity profile calculated using preview road slope information, significant improvement in the fuel economy occurs. To calculate the optimal velocity in the existing method, however, platoon should acquire expensive road slope data in advance. As an alternative, we propose a road slope estimation method, which enables platoon to calculate the optimal velocity profile without the usage of actual road slope data. Other major challenges in platoon operation include overcoming the effect of the vehicle model uncertainties and external disturbances for ensuring the control performance. The most significant part of the disturbances arises from slopes along a route. Existing method for reducing the effect of the slope employs a feed-forward type compensation in the control loop by combining the vehicle position acquired from GPS and the slope database. However, this method exhibits limitations: the mass of the vehicles in the platoon is uncertain which lowers the accuracy of the feed-forward compensation, and the platoon requires the pre-acquired slope database. To overcome these limitations, we propose an alternative method employing disturbance observer. Simulations of various scenarios are conducted to show the efficacy of the proposed method using the actual road slope data of a Swedish highway.

Tracking control of multiple unmanned aerial vehicles incorporating disturbance observer and model predictive approach

This paper studies the disturbance observer-based model predictive control approach to deal with the unmanned aerial vehicle formation flight with unknown disturbances. The distributed control problem for a class of multiple unmanned aerial vehicle systems with reference trajectory tracking and disturbance rejection is formulated. Firstly, a local distributed controller is designed by using the model predictive control method to achieve stable tracking, where the local optimization problem is solved by an adaptive differential evolution algorithm. Then, a feedforward compensation controller is introduced by using a disturbance observer to estimate and compensate disturbances, and improve the ability of anti-interference. Besides, the stability of the proposed composite controller is analyzed as well. Finally, the simulation examples are provided to illustrate the validity of proposed control structure.

Robust Feedback-Linearization Technique for Grid-Tied LCL Filter Systems Using Disturbance Estimation

In this paper, feedback linearization (FBL) technique together with disturbance observer (DO) approach is proposed to mitigate the effect of the resonant frequency of grid-tied LCL filter systems. The state-feedback control law is employed to achieve stabilization of the LCL filter system under a wide range of resonant frequency variation. The DO is designed to counteract the effect of model uncertainty and unknown disturbance aiming to achieve asymptotic stability under FBL control. Specifically, the observer is designed to estimate an additional input, representing uncertainty and unknown disturbance, from measurable variables. Then, the FBL control utilizes the disturbance estimate to compensate for its effect. An interesting feature of the composite controller is its ability to meet the transient response specifications even in the presence of model uncertainty and external disturbance. The composite controller was implemented for simulation and experimental evaluation, and performance testing. High performance with respect to disturbance rejection and parameter variation has been demonstrated.

Disturbance-Observer-Based Frequency Regulation Scheme for Low-Inertia Microgrid Systems

This paper presents a disturbance observer approach for frequency regulation for a low-inertia microgrid system consisting of various distributed energy resources (DERs). The mismatch in load and generation is estimated using the disturbance observer and is used as a supplement to the classical integral controller to vary the set points of various controlled DERs. Since the disturbance-observer-based approach is an algorithm based on local frequency measurement, it reduces the capital expenditure in implementing additional sensors. Further, in case of microgrids, the communication infrastructure is mostly built with public networks, which can introduce random delays. Therefore, the performance of the proposed scheme is also tested in the presence of random communication delays. A sensitivity analysis is also presented to show that the performance of the proposed control scheme is much better than the integral controller even when there are variations in the system parameters. Finally, the proposed approach is tested in a laboratory-scale microgrid setup in which the frequency of a synchronous generator is controlled using the disturbance-observer-based approach. The results obtained in the experimental setup show that the proposed approach can be easily implemented in a real system in order to achieve adequate frequency control.

Adaptive Neural Network Control of Underwater Robotic Manipulators Tuned by a Genetic Algorithm

This paper describes a novel approach for the control of underwater robots that can handle uncertainties and disturbance problems, which are commonly met in underwater environments. The considered system is an underwater manipulator with n-degrees of freedom. The approximation capability of an adaptive neural network is exploited to estimate uncertainties in system dynamics. Drag and lift forces are considered as an external disturbance, and a disturbance observer approach which has been proved to be effective with on-land robotic systems, is applied to compensate for it. The objective of the controller designed is to track a desired trajectory. To find the optimal gain parameters of this controller, a classical Genetic Algorithm is employed. Extensive simulation studies carried out on a two degrees of freedom manipulator indicate the efficacy of the proposed approach, proving that the disturbance observer originally developed for on-land systems can also be used effectively for underwater robotic systems. Finally, the performance of the proposed controller, tuned by the Genetic Algorithm is compared with that of a controller, tuned manually. The results show that the reliance on a well-known classic Genetic Algorithm for the tuning of the controller parameters not only saves time, but also provides better values of the parameters.

Guaranteeing almost fault-free tracking performance from transient to steady-state: a disturbance observer approach

In this paper, we propose an output-feedback fault-tolerant controller (FTC) for a class of uncertain multi-input single-output systems under float and lock-in-place actuator faults.Of particular interest is to recover a fault-free tracking performance of a (pre-defined) nominal closed-loop system, during the entire time period including the transients due to abrupt actuator faults.As a key component, a high-gain disturbance observer (DOB) is employed to rapidly compensate the lumped disturbance, a compressed expression of all the effect of actuator faults (as well as model uncertainty and disturbance) on the system.To implement this high-gain approach, a fixed control allocation (CA) law is presented in order to keep an extended system with a virtual scalar input to remain of minimum phase under any patterns of faults.It is shown via the singular perturbation theory that the proposed FTC, consisting of the high-gain DOB and the CA law, resolves the problem in an approximate but arbitrarily accurate sense.Simulations with the linearized lateral model of Boeing 747 are performed to verify the validity of the proposed FTC scheme.

Decentralised disturbance-observer-based adaptive tracking in the presence of unmatched nonlinear time-delayed interactions and disturbances

ABSTRACTThis paper proposes an approximation-based nonlinear disturbance observer (NDO) approach for decentralised adaptive tracking of uncertain interconnected pure-feedback nonlinear systems with unmatched time-delayed nonlinear interactions and external disturbances. Compared with the existing approximation-based NDO approach for uncertain interconnected nonlinear systems where the centralised design framework was proposed, the main contribution of this paper is to develop a decentralised and memoryless NDO-based adaptive control scheme in the presence of unknown time-varying delayed interactions and disturbances unmatched in the control inputs. The recursive design methodology is derived to construct the decentralised NDO and controller where the function approximators used in the decentralised NDO are employed to design the decentralised adaptive controller. From the Lyapunov stability theorem using Lyapunov--Krasovskii functionals, it is shown that all signals of the closed-loop system are semi-globally uniformly ultimately bounded and the tracking errors converge to an adjustable neighbourhood of the origin.

A new approach for periodic disturbance rejection in input-time-delay systems

An innovative approach combining equivalent-input-disturbance (EID) theory with the internal model principle is applied to achieve periodic disturbance rejection in input-time-delay systems. The EID estimator, which exhibits the synthetic effect of the time-delay and the periodic disturbance as an input-dependent disturbance, is constructed by inserting appropriate time-delay elements to compensate for the total influence of the input-time-delay and the periodic disturbance. A sufficient stability criterion is derived based on the separation theorem and the small-gain theorem. A design algorithm is developed for the system based on the stability criterion. Design and simulation results for the example are also employed to compare our method with the disturbance observer approach, and to demonstrate the validity of our method.

Approximation-based disturbance observer approach for adaptive tracking of uncertain pure-feedback nonlinear systems with unmatched disturbances

ABSTRACTThis paper presents an approximation-based nonlinear disturbance observer (NDO) methodology for adaptive tracking of uncertain pure-feedback nonlinear systems with unmatched external disturbances. Compared with existing control results using NDO for nonlinear systems in lower-triangular form, the major contribution of this study is to develop an NDO-based control framework in the presence of non-affine nonlinearities and disturbances unmatched in the control input. An approximation-based NDO scheme is designed to attenuate the effect of compounded disturbance terms consisting of external disturbances, approximation errors and control coefficient nonlinearities. The function approximation technique using neural networks is employed to estimate the unknown nonlinearities derived from the recursive design procedure. Based on the designed NDO scheme, an adaptive dynamic surface control system is constructed to ensure that all signals of the closed-loop system are semi-globally uniformly ultimately bounded and the tracking error converges to a neighbourhood of the origin. Simulation examples including a mechanical system are provided to show the effectiveness of the proposed theoretical result.

Estimating structural deformations for inferential control: a disturbance observer approach

Abstract: Increasingly stringent requirements for motion systems lead to a situation where the positioning performance can often not be measured directly and therefore has to be estimated. A typical example is a wafer stage, where the performance is desired at the point-of-exposure on the wafer but the sensors are located at the edge of the wafer stage. Increasingly stringent performance requirements necessitate taking structural deformations, caused by actuation or disturbance forces, into account. The aim of this paper is to develop a disturbance observer approach including an observer relevant model identification approach and to experimentally validate this approach on a prototype motion system. The experimental results confirm that the proposed disturbance observer approach leads to an improved estimation of the unmeasured performance variables.

An Adaptive Disturbance Observer for Precision Control of Time-Varying Systems

Abstract: In this paper, a new adaptive disturbance observer (ADOB) approach is introduced to overcome the inherent interference problem between a disturbance observer (DOB) and a parameter adaptation algorithm (PAA); the PAA is applied to estimate the parameters of the nominal plant model inverse, such that the disturbance estimated by the DOB is remained small. Namely, the proposed ADOB is equivalent to an adaptive control method that recursively minimizes the l 2 norm of the disturbance estimated by a DOB. Since the bounded l 2 norm of the disturbance estimate can be interpreted as the guaranteed stability of the DOB loop, the stability of the proposed ADOB can be proved theoretically, as well as practically. In addition, the proposed method directly seeks the parameters of a nominal plant model inverse, and thus the model inversion process is no longer necessary. The proposed ADOB is verified by theoretical analyses and experimental results in this paper.

Robust Missile Autopilots With Finite‐Time Convergence

AbstractThis paper presents a new longitudinal autopilot to address the finite‐time tracking problem for uncertain agile missiles. The proposed autopilot is essentially a composite control scheme, which is obtained through the finite‐time control methodology and the nonlinear disturbance observer (NDOB) approach. The key idea in this scheme is that the NDOB is adopted to estimate the aerodynamic uncertainties and external disturbances in an integrated manner. With the aid of the finite‐time bounded function and the Lyapunov function method, the finite‐time stability of the closed‐loop system is established, which shows that the angle‐of‐attack response will converge to the external command signal in finite time. Numerical simulation results are presented to demonstrate the superiority of the proposed scheme.

내부 모델 기반 외란 관측기를 이용한 수직 1축 머니퓰레이터의 속도 제어기 설계

This paper deals with a robust speed control problem of a vertical one-link manipulator in the presence of parameter uncertainties and unknown input disturbance. Uncertain load weight causes an additional sinusoidal disturbance in the rotation of the link. In order to improve the robustness against parameter uncertainties and external input disturbances, this paper employs an internal model-based disturbance observer approach. Comparative computer simulations are performed to test the performance of the proposed controller. The simulation results show the enhanced performance of the proposed method.

Sliding-mode-based disturbance observer approaches for vehicle steering control

Disturbance observer estimates a disturbance on the control input channel by using past measurements instead of estimating the disturbance itself and is a very powerful method to improve vehicle motion dynamics. This study proposes two new disturbance observer approaches for vehicle steering control, which are based on Sliding Mode Control (SMC) theory. The controllers estimate the equivalent input extended-disturbance in the control input channel. The extended-disturbance includes modelling and parameter uncertainties of the vehicle in addition to external yaw disturbances caused by side wind, µ-split braking, etc., The steering controllers have been tested on a Fiat Doblo Van modelled in CarSim environment. The sliding-mode-based disturbance observer approaches developed in this work are the first known applications to vehicle steering control. The performances of the proposed vehicle steering control systems have been compared with the performances of the Inverse-Model-based Disturbance Observer (IMDO) approach, which is a well-known disturbance observer method for motion control.