Conventional Disturbance Observer Research Articles

Disturbance Observer-Based Model Predictive Control for an Unmanned Underwater Vehicle

This work addresses the motion control problem for a 4-degree-of-freedom unmanned underwater vehicle (UUV) in the presence of nonlinear dynamics, parametric uncertainties, system constraints, and time-varying external disturbances. A disturbance observer-based control scheme is proposed, which is structured around the model predictive control (MPC) method integrated with an extended active observer (EAOB). Compared to the conventional disturbance observer, the developed EAOB has the ability to handle both external disturbances and system/measurement noises simultaneously. The EAOB leverages a combination of sensor measurements and a system dynamic model to estimate disturbances in real-time, which allows continuous estimation and compensation of time-varying disturbances back to the controller. The proposed disturbance observer-based MPC is implemented by feeding the estimated disturbances back into the MPC’s prediction model, which forms an effective adaptive controller with a parameter-varying model. The proposed control strategy is validated through simulations in a Gazebo and robot operating system environment. The results show that the proposed method can effectively reject unpredictable disturbances and improve the UUV’s control performance.

Autonomous Manipulation of an Underwater Vehicle-Manipulator System by a Composite Control Scheme With Disturbance Estimation

This article addresses an autonomous manipulation problem for an underwater vehicle-manipulator system (UVMS) operating in a free-floating way while subjecting to unknown continuous disturbance. More specifically, a composite control scheme composed of disturbance observer (DOB), predictor model network (PM-Net), and nonlinear model predictive control (NMPC), is devised to improve the control performance of UVMS (i.e., unicycle-like UVMS actuated only in the surge, heave, and yaw for vehicle body) in the case of disturbance, model mismatch, and input saturation. A RBF-DOB is formulated by combining a DOB and a Radial Basis Function (RBF) neural network to estimate disturbance at the current step. Then, the PM-Network, composed of a disturbance predictor network and state predictor network, is developed based on long short-term memory (LSTM) network that predicts UVMS state sequences considering model mismatch and disturbance. The NMPC is deployed as a feedback control law to endow the input saturation of the UVMS and produce optimal control action. Compared with conventional DOB control methods using feed-forward compensation of disturbance, the primary merit of the proposed approach is that the disturbance estimated by RBF-DOB is utilized in the PM-Net to predict future UVMS state sequences, which are exploited on the NMPC’s receding optimization. RGB0,0,0Finally, realistic simulation and relevant experiment are conducted to demonstrate the effectiveness of the proposed method. <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Note to Practitioners</i> —The motivation behind this article is the autonomous manipulation of an underwater vehicle-manipulator system subjected to unknown disturbance. However, it is not always feasible or straightforward to obtain the external disturbance and unmodeled dynamics for designing robust controllers. On the one hand, how to manipulate the disturbance into the designed controller to generate optimal control action rather than by using feed-forward compensation. On the other hand, the control input saturation often occurs in the UVMS control, especially under the disturbance rejection conditions, where it should be considered in the controller design. Currently, the predominant methods for UVMS control lack a control scheme that provides a complete and credible control strategy that takes the aforementioned issues into consideration. Motivated by the above analysis, this study provides a composite control scheme to deal with the dynamic uncertainties, unknown disturbance, and input saturation. RGB0,0,0The results of realistic simulation and relevant experiments demonstrate the effectiveness of the proposed method. Hopefully, our control method can provide valuable theoretical and technical guidance to practicing marine engineers for controller design.

Layered Composite Decoupling Control Based on Regional Dynamic Sparrow Search Algorithm

This paper addresses the issues of coupling and disturbances in a dual-tank water level control system within the context of process control in chemical water treatment at industrial facilities. In response to these challenges, a Layered Composite Decoupling Control system based on the Regional Dynamic Sparrow Search Algorithm (RDSSA-LCDC) is proposed. The utilization of an enhanced Regionally Dynamic Sparrow Search Algorithm (RDSSA) addresses the pitfalls of the Sparrow Search Algorithm (SSA), such as susceptibility to local optima and inadequate precision. RDSSA is employed for the parameter tuning of the system’s PID controller. Structurally, it incorporates a Hierarchical Composite Decoupling Control (LCDC) strategy, initially establishing a forward channel to construct an inner-layer decoupling model employing pre-feedback to rectify the lower-level system’s inputs, thereby mitigating inter-branch coupling. Subsequently, it develops an improved disturbance observer model based on pseudo-inverse compensation in the feedback channel, addressing conventional disturbance observer biases, and observing and suppressing system coupling and disturbances. Finally, within the dual-tank water level control system, various control schemes are simulated and compared, affirming the approach’s commendable decoupling, responsiveness, and disturbance rejection performance.

A Persistent-Excitation-Free Method for System Disturbance Estimation Using Concurrent Learning

Observer-based methods are widely used to estimate the disturbances of different dynamic systems. However, a drawback of the conventional disturbance observers is that they all assume persistent excitation (PE) of the systems. As a result, they may lead to poor estimation precision when PE is not ensured, for instance, when the disturbance gain of the system is close to the singularity. In this paper, we propose a novel disturbance observer based on concurrent learning (CL) with time-variant history stacks, which ensures high estimation precision even in PE-free cases. The disturbance observer is designed in both continuous and discrete time. The estimation errors of the proposed method are proved to converge to a bounded set using the Lyapunov method. A history-sample-selection procedure is proposed to reduce the estimation error caused by the accumulation of old history samples. A simulation study on epidemic control shows that the proposed method produces higher estimation precision than the conventional disturbance observer when PE is not satisfied. This justifies the correctness of the proposed CL-based disturbance observer and verifies its applicability to solving practical problems.

Robust Voltage Control for Harmonic Suppression in Islanded Microgrids Using Compensated Disturbance Observer

In low voltage (LV) islanded microgrids, practical issues such as nonlinear and unbalanced loads, unmodeled dynamics, and parameter uncertainties can cause high harmonic distortions, or even instability. To harness these problems, it is proposed in this paper to model the deviations of the voltage of the point of common coupling as an unmeasurable pseudo-disturbance. Based on this strategy, a compensated disturbance observer (CDOB) is then proposed to suppress harmonics. The CDOB enhances the merits of conventional disturbance observer in a novel structure. It improves the robustness, stability, and dynamical response. The controller is applied on an LV microgrid consisting of multiple distributed energy resources feeding local and common loads, through feeder lines with notable impedances. Comparative simulations and experiments are conducted to illustrate the performance of the presented approach.

Performance Analysis of Learning-Based Disturbance Observer for Pulsed Superconducting Cavity Field Control

The use of Disturbance Observer-based (DOB) control is widespread in stabilizing the electromagnetic field in superconducting radio frequency cavities to facilitate beam acceleration in particle accelerators. Repetitive disturbances such as beam loading and Lorentz force cavity detuning are compensated by DOB control, and their suppression is enhanced through the incorporation of a learning scheme into the conventional disturbance observer. This paper evaluated the performance of a learning-based disturbance observer for compensating beam loading and cavity detuning in pulsed superconducting radio frequency cavities and proposes modifications for better field stability. A superconducting cavity baseband model for π-mode was simulated in Matlab/Simulink with a trapezoidal beam pulse as the input disturbance and different cavity detuning values to analyze the controllers’ performance. The simulations were conducted for multiple observer filter bandwidths to evaluate the performance of the learning-based disturbance observer under plant model uncertainties and different detuning values. The results demonstrate that the learning-based disturbance observer yields faster convergence to the reference input and lower tracking errors during the flat top of pulse voltage in comparison to conventional disturbance observer control.

Adaptive disturbance observer-based improved super-twisting sliding mode control for electromagnetic direct-drive pump

In this study, to enhance the frequency-flow characteristics of the novel electromagnetic direct-drive pump (EDDP). An adaptive disturbance observer-based improved super-twisting sliding mode control (ISTSMC-ADOB) is proposed to address the problem in which the response quality is deteriorated by factors such as parameter mismatch and disturbance. An adaptive disturbance observer (ADOB) is designed to achieve adaptive compensation, avoid the use of high-gain feedback, and extend the applicability of the conventional disturbance observer. An improved super-twisting sliding mode control (ISTSMC) based on the fast terminal sliding mode algorithm is designed to ensure faster convergence of the error in finite time. By combining the ADOB with the ISTSMC, the conservative parameter selection of the sliding mode control (SMC) is avoided, and the accuracy and robustness are further strengthened. The stability is analyzed based on Lyapunov. The results show that the proposed method effectively improves the steady-state accuracy, response speed, and robustness in trajectory tracking of the electromagnetic linear actuator for the EDDP. This further enhances the frequency-flow characteristics of the system.

A Practical Disturbance Rejection Control Scheme for Permanent Magnet Synchronous Motors

This paper proposes a novel disturbance rejection control scheme for permanent magnet synchronous motor (PMSM) drives. Based on the framework of modified disturbance observer (DOB)-based control, the final topology of the proposed disturbance rejection proportional–integral (DR-PI) controller includes a pre-filter and a controller in a proportional–integral (PI) form. The proposed DR-PI control scheme is practical with a straightforward gain tuning rule. Note that the gain selection method is the main issue of not only conventional PI controllers but also advanced methods such as DOB-based controllers. In addition, by starting from the framework of modified DOB, this paper also proves that the PI controller with an pre-filter possesses a disturbance rejection ability similar to a DOB-based control method. To the best of our knowledge, this is the first time that such a simple and effective PI controller is designed for the speed control of PMSMs as well as theoretically proven to have a perfect disturbance rejection ability. This paper shows the steps of selecting the parameters of the proposed controller in terms of the parameters of a desired plant model, disturbance observer and compensator. Hence, unlike a traditional DOB case, in this approach, one can simultaneously tune the controller and observer at the same time. The appearance of the pre-filter from the modified DOB scheme solves an overshoot problem, thus the general motor operation is significantly improved, which is validated by experiments. The experimental evidence under two scenarios of load torque change and speed change prove the effectiveness of the proposed method compared to conventional PI and DOB control (DOBC) schemes. All the experiments were implemented on a 300 W PMSM of a setup manufactured by Lucas-Nuelle GmbH with a digital signal processor.

Extended sliding mode observer based robust adaptive backstepping controller for electro-hydraulic servo system: Theory and experiment

This paper firstly presents an extended sliding mode observer (ESMO) for the electro-hydraulic servo systems (EHSSs) to deal with nonlinear factors like the external disturbance, parameter uncertainties as well as unmodeled characteristics in the EHSS. The model for the EHSS is established by taking these nonlinear factors into consideration and then the statespace representation is obtained. According to the state space, the ESMO for the EHSS is presented, the equivalence principle is properly utilized to simplify the ESMO and some saturation functions are employed to eliminate high frequency interferences caused by the chattering phenomenon. Based on estimated values from the ESMO, a robust adaptive backstepping controller (RABC) is presented in detail with taking some parameter uncertainties into consideration to further improve the tracking performance. The proposed controller has the following advantages: (1) utilizing the ESMO to cope with these nonlinear factors; (2) parameter online adaptive laws are employed in the RABC design to further improve the tracking performance. In order to verify the performance of the proposed controller, an experiment bench was established. Two sine waves reference signal (one amplitude 0.01 m, 1 Hz; the other 0.015 m, 2 Hz) are employed to verify the performance of the controller. Comparative experimental results show that: (1) the tracking performance of the proposed controller is better than that of a DOs based BC, a BC and a PI controller; (2) estimation values from the ESMO contains fewer noise than two conventional disturbance observers (DOs), which will decrease the control input ripples.

Robust attitude control of a quadrotor unmanned aerial vehicles using optimized disturbance observer

AbstractThis article proposes a method of realizing robust attitude stabilization control of a quadrotor UAV using the disturbance observer (DOB), where Q–filter is optimally designed considering performances of attenuating disturbance and estimation noise, and robust stability against parameter variations and sampling duration delay due to discrete time control in microcontroller. Disturbance rejection performance mainly depends on the bandwidth determined by cut‐off frequency of DOB's Q–filter. However, extension of the Q–filter's bandwidth must be restricted due to the requirement of robust stability against parameter uncertainty and sampling duration delay in onboard microcontroller for flight control of quadrotor. In order to optimize the disturbance rejection performance under the restriction of bandwidth, an norm minimization problem is defined considering the frequency bands of disturbance and noise. The optimization problem is transformed into standard control design problem by pseudo loop factorization method so as to resolve the structural constraint of Q–filter. Then, stability of the discrete time system configured by digital controller is tested in relation with the time constant of the designed DOB's Q–filter under different inertia moment values. The comparisons between simulation results by different control methods validate that the robust control method using proposed DOB provides a better performance of disturbance attenuation than that using conventional DOB.

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.

A New Adaptive Disturbance/Uncertainty Estimator Based Control Scheme For LTI Systems

This paper introduces a new adaptive disturbance/uncertainty estimator based control scheme for LTI systems. The aim of the proposed method is to update the nominal model directly used by the conventional disturbance observer based control architecture and approximate it to the perturbed/uncertain system using machine learning approaches. This enhances the disturbance rejection performance of the system remarkably. The performance deterioration capacity of lumped disturbances, which are the mixed effect of disturbances entering through the control channels and modeling uncertainties, are decomposed in our approach and handled separately. For this study, harmonic disturbance model and constant unstructured uncertainty model are considered, and ϵ-Support Vector Regression approach is used together with an online adaptation algorithm. A numerical example is given to demonstrate the merits and effectiveness of the proposed approach. Simulation results show that the proposed method outperforms the conventional disturbance/ uncertainty estimator based control architecture by increasing disturbance estimation performance of the system.

Generalised dual‐filter disturbance observer for nonminimum‐phase systems

To reject the disturbances of the nonminimum-phase systems, the generalised dual-filter disturbance observer is proposed. The conventional disturbance observer methods inevitably lead to nonminimum-phase systems' instability. To stabilise the system, the forward plant and dual filters are introduced. The stability constraints are transferred to the dual filters. Based on any stable designs of the close-loop controller, the dual filters can be easily designed. The simulations effectively verify that the disturbance rejection performances of the proposed method are triple those of the closed-loop nonminimum-phase system, and the original system's tracking capabilities and stability margins are few affected.

Robust tracking control in the inertia phase for generalised disturbance

To solve the problem of shift shock during the inertia phase caused by generalized disturbances in wheel loaders and other construction instruments, a robust double closed-loop tracking control method based on an improved disturbance observer (DOB) has been proposed. In this method, the inner loop robustly suppresses disturbance and the outer loop realizes trajectory tracking. The improved DOB based on a nominal disturbance value (NDV) can enhance the disturbance suppression ability of the inner loop when a large part of the generalized disturbance is determinable. The model matching method transforms the outer loop into a transfer function to meet the expected performance. A disturbance compensation controller eliminates the nominal disturbance in the system. A feedforward compensation controller eliminates the influence of reference inputs in the system. Considering the inertia phase of a fixed-axis automatic transmission of a wheel loader, the proposed method was applied to the driveline simulation platform of a specific type of wheel loader. Random loads under actual working conditions were considered as the input load of the simulation platform. The simulation results indicated that the DOB based on the NDV method has better disturbance suppression capability, more accurate tracking capability and smaller shift shock than the conventional DOB method. The proposed control method exhibits robustness under 10%, 50% and 90% of the maximum load. The highest shift shock is 4.94% of the manual shift shock and it is effectively reduced. Thus, robust and smooth inertia phase shift control of the automatic transmission can be realized. This study presents an effective method for solving robust disturbance suppression control problems and tracking control problem under large generalized disturbances.

Robotic Biceps Exercise Machine: Hardware Using Series Elastic Actuator and Control With Disturbance Observer

Resistance training is a popular form of exercise owing to its health-related and athletic performance benefits. Robotic exercise machines using human-robot interaction are a promising solution for designing resistance training programs that successfully achieve training gains. We propose a robotic biceps exercise machine that generates a variable resistance force profile and controls the interaction force corresponding to the profile through a range of motion of exercises. A series elastic actuator measures and controls the resistance force. A novel cascade control structure comprising an inner velocity and outer force control is presented. The inner loop disturbance on the dynamics and outer loop disturbance on the kinematics are eliminated by a disturbance observer (DOB) in each loop. The performance of the proposed force control scheme is validated by comparisons with the conventional DOB and proportional-integral (PI) control schemes. Additionally, the resistance force profile and interaction force of a conventional robotic biceps exercise machine are analyzed experimentally.

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.

Multirate iterative learning disturbance observer with robustness to frequency deviation for high precision attitude stabilization of flexible spacecraft subject to complex disturbances

High precision attitude stabilization of spacecraft is essential for the operation of precision instruments onboard. However, attitude vibrations of spacecraft are inevitably induced by complex disturbances. Disturbance observer based control scheme (DOBC) is a promising anti-disturbance technique, while it is restricted by the inadequate estimation performance of conventional disturbance observers for complex disturbances when taking structural complexity and noise sensitivity into account. To achieve high performance attitude stabilization of spacecraft subject to complex disturbances, a multirate iterative learning disturbance observer (MILDO) based controller is designed in this paper. Firstly, an augmented disturbance model is constructed in view of the periodicities of disturbances with known fundamental frequencies. Then, a generic proportional-derivative type MILDO (PD-MILDO) is designed by using previous disturbance estimates to update current estimates. The gain tuning method and the disturbance estimation performance of PD-MILDO are also presented. It is demonstrated that accurate disturbance estimation for low-frequency disturbance and multiple periodic disturbances can be achieved by PD-MILDO. Besides, the robustness of PD-MILDO to undesired frequency deviation can be significantly improved by introducing the proportional-derivative correction terms. Based on MILDO, a feedback controller is then designed to stabilize the spacecraft attitude. In the concept of DOBC, the controller and observer can be tuned independently. Finally, the effectiveness of the proposed control scheme is verified by simulations.

선택적 외란 제거를 위한 외란 관측기의 Q 필터 설계

In a disturbance observer (DOB), introduced disturbances are monitored by a plant inverse model and a Q filter compensates the improper inverse model and is designed to stabilize closed loop systems. Therefore, the filter bandwidth is usually trimmed to control the attenuation rate of the disturbance. However, the conventional DOB cannot reduce selective disturbances but only lumped disturbances. To selectively reduce the disturbances, this note proposes a new Q filter design method. Through a mathematical derivation, it is verified that the Q filter design problem belongs to the category of the inverse function design of the introduced disturbance spectrum. Using numerical simulations, it is shown that the proposed method reduces selective disturbances and lumped disturbances.

A Robust High-Order Disturbance Observer Design for SDRE-Based Suboptimal Speed Controller of Interior PMSM Drives

This paper proposes a robust high-order disturbance observer (HODO) for the state-dependent Riccati equation (SDRE)-based suboptimal speed controller of an interior permanent magnet synchronous motor (IPMSM) drive. The conventional disturbance observers (DOs) cannot accurately estimate the fast time-varying disturbances of an IPMSM during the transient-state because the disturbances are assumed to change slowly, so the inaccurately estimated disturbances lead to conservative robust control. Unlike the conventional DOs, the proposed HODO guarantees the fast convergence of the estimated error for an IPMSM drive by accurately estimating the fast time-varying disturbances and their all high-order derivatives. Also, it is specifically applicable to the SDRE based suboptimal speed controller which cannot completely eliminate the steady-state error in the presence of mismatched disturbances and uncertainties. Finally, the simulation results via a MATLAB/Simulink package and the experimental results via a prototype IPMSM test-bed having TI TMS320F28335 DSP are presented to verify the faster dynamic response, smaller steady-state error, and more robust response of the SDRE speed controller with the proposed HODO compared with the conventional 1st-order DO, conventional generalized proportional integral observer (GPIO), and conventional SDRE observer.

Sensorless Control of a Linear Permanent-Magnet Motor Based on an Improved Disturbance Observer

Linear permanent-magnet (PM) motors incorporate the merits of high efficiency, simple mechanism, and low cost, which have a bright future in urban rail transit. However, the position sensor costs are huge, which is the main barrier against a wider implementation. In this paper, a type of modified disturbance observer is newly proposed to improve the precision. Two disturbance observers are utilized to estimate the back electromotive force. Then, position information is detected by a phase-locked loop. Finally, the linear PM motor runs with the feedback of estimated position and speed instead of position encoder measuring. The algorithm avoids designing filters and injecting signals. Experimental results based on a linear primary PM vernier motor demonstrate the accuracy and dynamic performance. The comparisons in the aspect of the robustness to measurement errors certify that the modified disturbance observer is superior to the conventional disturbance observer.