Improved Disturbance Observer Research Articles

Disturbance observer based fixed-time tracking control for unmanned aerial helicopters

In this paper, a fixed-time tracking control scheme based on the fixed-time disturbance observer is proposed for a 6-DOF unmanned aerial helicopter (UAH) with flight path constraints and composite disturbances. The composite disturbances are composed of external disturbances and system uncertainties. By using the hyperbolic tangent function, an improved disturbance observer is developed to estimate composite disturbances. Furthermore, a fixed-time back-stepping control method is employed for the position and attitude loops, which enables the UAH to track the expected path within the flight path constraints. Simulation results are given to demonstrate the effectiveness and advantages of the proposed scheme.

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 sliding mode‐based single‐loop control strategy for permanent magnet synchronous motor drives

AbstractA simple control structure with high anti‐disturbance ability is proposed here for permanent magnet synchronous motor (PMSM) drives. The conventional cascade structure, with an outer speed loop and an inner current loop, is simplified and merged into one single‐loop controller. To enhance the dynamic performance and efficiency of the PMSM drives, an enhanced adaptive reaching law (EARL) is proposed for the single‐loop control strategy. In comparison with conventional reaching laws, the EARL can increase the convergence speed, adapt the gain to fit the system state, and reject the chattering phenomena of conventional sliding mode control. Moreover, an improved disturbance observer (DOBS) is developed to work with the main controller. The DOBS aims to enhance the estimation accuracy of real‐time unknown disturbances in the PMSM system, thereby further improving the disturbance rejection capability through feedforward compensation for the single‐loop control strategy. The EARL and DOBS thus enhance the robustness of the control strategy and ensure high dynamic performance at various motor operating conditions. The performance and efficiency of the proposed control are validated through simulations and experimental studies.

Mixture Basis Function Approximation and Neural Network Embedding Control for Nonlinear Uncertain Systems with Disturbances

A neural network embedding learning control scheme is proposed in this paper, which addresses the performance optimization problem of a class of nonlinear system with unknown dynamics and disturbance by combining with a novel nonlinear function approximator and an improved disturbance observer (DOB). We investigated a mixture basic function (MBF) to approximate the unknown nonlinear dynamics of the system, which allows an approximation in a global scope, replacing the traditional radial basis function (RBF) neural networks technique that only works locally and could be invalid beyond some scope. The classical disturbance observer is improved, and some constraint conditions thus are no longer needed. A neural network embedding learning control scheme is exploited. An arbitrary type of neural network can be embedded into a base controller, and the new controller is capable of optimizing the control performance by tuning the parameters of neural network and satisfying the Lyapunov stability simultaneously. Simulation results verify the effectiveness and advantage of our proposed methods.

Research on Tracking Control of Urban Rail Trains Based on Improved Disturbance Observer

Urban rail transit trains operate in a complex and changing environment susceptible to uncertainties such as unknown disturbances or actuator faults. In order to ensure that the automatic train control (ATC) system can operate safely and control accurately even when the train is affected by uncertainties, the train is first subjected to force analysis, and a multiple point-mass model for the urban rail trains (URTs) is established. Secondly, an improved disturbance observer is proposed to estimate and attenuate the unknown disturbance online. The stability of the URTs system under the improved disturbance observer-based control (IDOBC) is demonstrated based on the linear matrix inequality and Lyapunov theorem. Finally, the Simulink platform is used to verify the target curves obtained after data optimization of the certain Nanchang Metro line for case verification. Compared to the traditional disturbance observer-based control (TDOBC) method, the train tracking error converges to near the zero region faster after being subjected to an external disturbance, and the mean absolute error (MAE) metric is smaller throughout the whole operation. The control strategy proposed in this paper has a more desirable control effect and can ensure the safer and more stable operation of the URTs.

Decoupling design and control of a spaceborne ultra–stable platform for vibration isolation and precise steering

This study concerns the problems of system coupling and large payload mass ratio and designs a spaceborne ultra–stable platform (SUSP) to isolate the payload from the satellite vibration and accomplish high–precision payload steering. First, the dynamic equilibrium of the SUSP and vibration transfer functions are determined. The decoupling condition is then derived to make the coupled vibration transfer functions equal to zero, and the SUSP multi–input multi–output (MIMO) system is decoupled into six single–input single–output (SISO) subsystems. Consequently, the natural frequency matrix can be easily designed to guarantee the vibration isolation performance and obtain identical feedback gain values. Subsequently, a steering controller based on a nominal system simplified by decoupled dynamic equilibrium was designed. The impact of a large payload mass ratio was estimated and eliminated by the improved disturbance observer (IDO) in the steering controller. After rigid–flexible coupling dynamic modeling and analysis, two simulation stages were implemented. The results of the isolation stage exhibit a –40 dB/dec roll–off of the vibration disturbance and a coupled response reduction of approximately –20 dB. The payload tracking error of the isolation–steering integrated stage is reduced to 0.13″ (0.1° circular trace), and the isolation performance is further improved.

A Rate-Difference Disturbance Observer Control for a Timing-Belt Servo System

The belt-drive control enables the mechanical system to gain the advantages of lightweight, vibration absorption, and high torque, while it brings strong nonlinear disturbances due to friction, backlash, and flexibility. Therefore an improved disturbance observer (DOB) control method based on the dual-rate loop structure is proposed in this article to suppress these disturbances. Only a linear low-frequency device model is required, which indicates that this method avoids the dependence on accurate identification of the nonlinear uncertain systems. The rate information on the motor-side is replaced with the input signal of inner loop due to the high bandwidth of inner motor loop, which greatly simplifies the design of the control system. In the case of insufficient system bandwidth, the proposed method integrates the favorable information of the load-side and the motor-side under the DOB framework. And the speed-commutation spikes and chatters resulting from disturbances on the flexible transmission chain can be more effectively suppressed by the proposed control structure compared with the conventional methods.

Robust Suppression Strategy for Photovoltaic Grid-Connected Inverter Cluster Resonance Based on Kalman Filter Improved Disturbance Observer

In response to the key engineering problems of photovoltaic grid-connected inverter cluster resonance suppression affected by grid-connected inverter impedance, in this paper, a control strategy based on a disturbance observer is proposed to dynamically compensate for the damping coefficient of the controlled system and improve the robustness of the system. First, an engineering mathematical model of a 200 MW photovoltaic inverter cluster is established, and the mechanism of the active damping of the cluster inverter influenced by the disturbance is analyzed. Secondly, the capacitor current feedback is utilized to constitute the virtual damping, and the inverter output impedance is reshaped to suppress the resonance peak. Then, a Kalman filter is used to improve the traditional disturbance observer to accurately detect disturbance of the system during the dynamic process of the cluster inverter so as to better adapt to changes in grid impedance and dynamically compensate for the virtual damping of the cluster resonant system. Finally, the proposed control strategy is verified with respect to a practical PV power station. The experimental results demonstrate the feasibility of the proposed control method.

Boundary control of multiple-sectioned flexible marine riser with time-varying output constraint

This article addresses the problem for vibration suppression of a multiple-sectioned marine riser system subject to time-varying external disturbances and asymmetric output constraint. Under the assumption that continuity constraint, multiple-sectioned marine riser’s dynamics are described by some continuously connected partial differential equations (PDEs) coupled with an ordinary differential equation (ODE). We only employ boundary control mechanism that suppresses system’s vibration displacements and compensate the influence of external disturbances. A novel and improved disturbance observer is proposed to estimate unknown boundary disturbance and two different barrier Lyapunov functions are constructed to prevent the time-varying constraint violation. Based on the backstepping technology and Lyapunov-based control, a boundary controller is presented to accomplish the control objectives. Moreover, the uniform boundedness and stability of the closed-loop system are rigorously guaranteed. Finally, simulation results are provided to illustrate the effectiveness of the designed control scheme.

Adaptive Non-Singular Terminal Sliding Mode Control Method for Electromagnetic Linear Actuator.

In this study, to further improve the dynamic performance and steady-state accuracy of the electromagnetic linear actuator (EMLA) for the direct-drive system, the adaptive non-singular terminal sliding mode controller (ANTSMC) based on an improved disturbance observer (IDOB) is proposed. Accurate modeling of the EMLA based on the LuGre friction model was obtained by identification. Aiming at the continuous disturbance of the system, a non-singular terminal sliding mode control based on improved exponential reaching law (IERL) is designed, which is combined with the advantages of fuzzy control. Adaptive adjustment of the IERL gain is achieved to ensure finite time convergence of the tracking error while suppressing system jitter. Based on the IDOB to achieve effective observation compensation under noise disturbance and further improve the system robustness. The stability of the control is analyzed based on the Lyapunov function. The results show that the proposed method suppresses the jitter and improves the tracking performance and robustness of the servo system for different desired trajectories effectively.

Neural-embedded learning control for fully-actuated flying platform of aerial manipulation system

To address the problem of efficient task for the fully-actuated aerial manipulation system, the flight platform control scheme based on neural networks embedding is proposed. We embed the neural networks controllers (NNC) into some base controllers, which are Lyapunov stable for their system. Due to the learning and optimizing capability of NNC, the derivative controllers allow to improve control performance by updating the parameters of NNC under Lyapunov stability condition. The backstepping technology based on the mixture basis functions that approximates unknown system dynamics and the improved disturbance observer is designed for the base controller of platform attitude. And the linear active disturbance rejection controller (LADRC) is utilized as the base controller of platform position. Considering safety and cost, we made some virtual experiments in CoppeliaSim a software which offers high accuracy physical engine. The results of virtual experiments prove that compared with some state-of-the-art technologies the methods proposed are advanced in tracking errors performance due to NNC.

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.

Improved disturbance-observer-based fault-tolerant control for the linear system subject to unknown actuator faults and multiple disturbances

The problem of fault-tolerant control for the time-invariant system subject to actuator faults and multiple disturbances is focused. The multiple disturbances are composed of two kinds: one is a norm-bounded vector; the other described by an exogenous system is viewed as a harmonic signal with known amplitude and unknown frequency and phase. An improved disturbance observer is designed to obtain the modelled disturbance with partially known information. Based on this, two novel fault-tolerant control algorithms are put forward to the analysis and compensate two different types of actuator faults (one is norm-bounded, and the other is with an unknown boundary). The effectiveness and robustness of control schemes can be exhibited through some numerical simulations with different cases.

Disturbance Observer-Based Control of Tip-Tilt Mirror for Mitigating Telescope Vibrations

In the ground-based astronomical telescope, the imaging quality is usually affected by tip-tilt vibrations induced by the telescope structure. Long exposure time of the image sensor is usually required for a good signal-to-noise ratio, which brings the amount of time delays into the control loop of the tip-tilt mirror. Thus, a low control bandwidth is insufficient to compensate telescope vibrations. In this paper, an improved disturbance observer (DOB) control based on only the image sensor is proposed to reject structural vibrations. This new DOB controller is added into the original loop in the tip-tilt mirror control system, so the closed-loop performance can be optimized by designing an appropriate Q-filter. An improved Q-filter is presented to reject large-magnitude vibrations and also to reduce amplifications induced by this controller at nondisturbance frequencies. This proposed controller can achieve a satisfying result in vibration mitigations when vibration frequencies are provided to design the Q-filter. Furthermore, in the tilt-tilt mirror control system, this improved DOB is not restricted by an accurate model such that noise in the loop cannot provide serious influence on vibration mitigation. Both simulations and extensive experiments are carried out to demonstrate that the DOB can earn an extra improvement on the control performance in comparisons with the conventional feedback controller.

Fuzzy Logic Self-Tuning PID Controller Design for Ball Mill Grinding Circuits Using an Improved Disturbance Observer

In this study, a fuzzy logic self-tuning PID controller based on an improved disturbance observer is designed for control of the ball mill grinding circuit. The ball mill grinding circuit has vast applications in the mining, metallurgy, chemistry, pharmacy, and research laboratories; however, this system has some challenges. The grinding circuit is a multivariable system in which the high interaction between loops, the variation of the system parameters with time, and time delay are some of the problems that pose a challenge. Since the controller parameters are determined offline in classic PID control, these gains are unchangeable and cannot overcome the mentioned challenges in this system. Hence, a fuzzy logic self-tuning PID controller, which is a combination of fuzzy logic and a conventional PID controller, is proposed to control the grinding system, especially in the presence of model mismatch and disturbances. In addition, in order to solve the system challenges, a multivariable control approach based on an improved disturbance observer is proposed to suppress the effects of the disturbances. The most important feature of the algorithm proposed in this paper as the combination of fuzzy logic self-tuning PID and improved disturbance observer is its ability to eliminate system interaction, attenuate internal and external disturbances, and compensate the effect of system uncertainty on the performance of the ball mill grinding circuit. Simulation results in the cases of the set-point change in particle size and circulating load in the presence of model mismatch and external disturbances confirmed the controller performance compared to other controllers.

Improved disturbance observer based control for airborne photoelectric stabilized platform

The aim of this work was to solve the problem that the stabilization accuracy of photoelectric stabilized platforms is affected by disturbance. An improved disturbance observer was established to observe the disturbance. By using the ultra-high control bandwidth of the current loop, the observer was used as the input of the current loop. The design of the improved disturbance observer consists of an inverse model of the control object and an improved filter. The high-order disturbance observer not only has good suppression ability compared to the high order disturbance model, but also has good robustness, meeting the application requirements of photoelectric stabilized platforms.

End-Effector Force Estimation for Flexible-Joint Robots With Global Friction Approximation Using Neural Networks

This paper proposes an improved disturbance observer to realize accurate contact force estimation using the joint torque sensor. The joint torque sensor separates the dynamics of the link side from the motor side of the robot manipulator. Therefore, only computing the partial dynamics on the link side can realize external force estimation. This can considerably reduce the modeling workload and error terms that may affect the estimation results. Furthermore, this paper presents that the observed residual value during free motion can be considered as the friction dynamics, which is approximated by the neural network (NN) due to its inherent capacity in approximating nonlinear functions. After that, the estimation accuracy of the observer is considerably improved. Compared to other local NN approximation method, we analyzes the properties of the friction force in detail to select appropriate excitation trajectory for accurate global approximation results using only limited training data. We have presented that the suitable excitation trajectory and the use of global basis function are the sufficient conditions for global friction approximation. The proof of this theorem is also given. The Kalman filter is also utilized to reduce the noise of the estimation results in real time. The experimental results also demonstrate the efficacy of the proposed method, which accurately estimates the contact force for flexible joint robots.

Robust Current Controller for IPMSM Drives Based on Explicit Model Predictive Control With Online Disturbance Observer

To improve the performance of a current loop, this paper presents a novel current control scheme for an interior permanent magnet synchronous motor (IPMSM) based on the model predictive control (MPC) algorithm in a synchronous rotating frame (dq-frame). The recently developed explicit MPC (EMPC) is introduced to ensure the feasibility of real-time implementation in the control hardware. To achieve feasible reformulation of the current control problem using EMPC, a coupled nonlinear IPMSM mathematical model is linearized using an augmented model with disturbance. Furthermore, to approximate the related quadratic stator current and voltage constraints in the dq-frame, they are also transformed into a series of linear inequalities. We propose an improved disturbance observer based on the augmented model, in conjunction with the concept of offset-free MPC, to estimate both the disturbance terms and the state variables from the predicted and measured outputs. All the influences of plant/model mismatches and un-modeled nonlinear terms are removed by the estimated total disturbance within the closed-loop framework of EMPC. The proposed EMPC scheme not only improves both the dynamic performance and the steady-state precision of the current loop, but it also exhibits robustness against parameter uncertainties. The proposed method has been proven and verified successfully in both simulation and experiment.

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.

Differential Steering Based Yaw Stabilization Using ISMC for Independently Actuated Electric Vehicles

Differential drive assistance steering (DDAS) is an emerging assisted steering mechanism in in-wheel-motor driven (IWMD) electric vehicles, yielded by the differential moment of the front tires in the steering system. DDAS can steer the front wheels when there is no steering power from the steering motor, and thus can be used as a redundant steering mechanism. To realize the yaw control when the active front steering entirely breaks down and guarantee the transient control performance therein, this paper proposes an integral sliding mode control (ISMC) approach for IWMD electric vehicles steered by DDAS. Two contributions are made in this paper: 1) An improved disturbance observer based ISMC strategy is designed to cope with the unknown mismatched disturbances, and the composite nonlinear feedback technique is employed to design the nominal part of the controller to restrain overshoots and remove steady-state errors considering the tire force saturations; 2) An adaptive super-twisting control approach is proposed to deal with the disturbances with unknown boundaries using a continuous controller while eliminating the chattering effect. The system stability and robustness are proved via Lyapunov approach. CarSim-Simulink simulation has verified the effectiveness of the proposed control approach in the case of the steering fault.