Disturbance Compensation Control Research Articles

A Disturbance Compensation Control Strategy for Rotational Speed Standard Device Based on AMB System

The rotational speed standard device that can carry loads is the key device for calibrating passive rotational speed sensors. The rotor of the passive rotational speed sensor is connected to the rotor of the standard speed device through a coupling, and the standard reference speed is provided by the standard device. Due to the rotor eccentricity, the unbalanced force of the rotor occurs, and it can not only affect the rotational speed accuracy but can also damage the mechanical bearings of the standard speed device. To solve this issue, a method for suppressing the unbalanced force of the speed standard device based on an active magnetic bearing (AMB) force compensation system is proposed. First, the overall structure of the system is briefly introduced. Then, the force feedback control system model with the AMB as the force actuator is established, and a PI controller is designed to achieve the disturbed force control. Finally, a semi-physical simulation experimental platform is built to verify the effectiveness of the proposed method. The experimental results show that the AMB force compensation system can reduce 84.4%, 81.6%, and 79.8% of the unbalanced vibration force at the frequency of 30 Hz, 90 Hz, and 150 Hz, respectively.

Data‐driven disturbance compensation control for discrete‐time systems based on reinforcement learning

SummaryIn this article, a self‐learning disturbance compensation control method is developed, which enables the unknown discrete‐time (DT) systems to achieve performance optimization in the presence of disturbances. Different from traditional model‐based and data‐driven state feedback control methods, the developed off‐policy Q‐learning algorithm updates the state feedback controller parameters and the compensator parameters by actively interacting with the unknown environment, thus the approximately optimal tracking can be realized using only data. First, an optimal tracking problem for a linear DT system with disturbance is formulated. Then, the design for controller is achieved by solving a zero‐sum game problem, leading to an off‐policy disturbance compensation Q‐learning algorithm with only a critic structure, which uses data to update disturbance compensation controller gains, without the knowledge of system dynamics. Finally, the effectiveness of the proposed method is verified by simulations.

Finite-time disturbance observer-based levitation control for vehicle-guideway coupling systems

In this study, a novel composite control scheme for the vehicle-guideway coupling systems is proposed, consisting of FTDOs and a FTC, aiming to address the challenges of unknown disturbances and vibration suppression. Specifically, this method adopts a single magnet-track coupling model and introduces a finite-time disturbance observer (FTDO) that utilizes only measured electromagnet-side signals to estimate unmeasurable states and unknown disturbances. Based on the estimated information provided by the FTDO, a finite-time control (FTC) scheme is developed, which simultaneously handles the problems of disturbance compensation and finite-time tracking control. Additionally, the finite-time stability of the levitation system is analyzed and proven. Finally, simulation and experimental results are given to demonstrate the feasibility and superiority of the proposed control approach.

Compensation control strategy for photoelectric stabilized platform based on disturbance observation

The accuracy and stability of the photoelectric stabilized platform will be inevitably affected by the friction disturbance and the base platform disturbance in the actual operation. To improve the disturbance rejection performance, two kinds of the disturbance observers are employed and compared in this paper, including the adaptive proportion-integrator observer and the robust sliding mode observer. The disturbances of the friction torque and the moving base are observed, then these observed values are compensated to the voltage loop by the feedback and feedforward, respectively. While the disturbances of the friction torque and the shaking base are compensated, the parameters of the speed stability loop are also tuned to improve the performance of this photoelectric stabilized platform. Finally, the effectiveness of the proposed method is verified by both simulations and experiments. The results show that the proposed disturbance compensation control method based on the sliding mode observer has strong robustness and can effectively reduce the impact of system disturbances.

Robust trajectory tracking of quadrotors using adaptive radial basis function network compensation control

Radial Basis Function Neural Networks (RBFNN) methods have gained incredible efficiency and applicability in control. This paper presents a nested control strategy for robust trajectory tracking of a quadrotor using adaptive RBF compensation and NN-supervised control embedded with Integrator BackStepping (IBS). The approach addresses the robustness in the presence of modeling uncertainties, sensing noise, and bounded disturbances. The control design is derived from the decentralized inverse dynamics, using adaptive RBFNN for outer-loop disturbance approximation and compensation. In conjunction with an Inner-loop supervised control that stabilizes the quadrotor attitude, preventing initial instability during NN convergence. In addition, an adaptive Extended Kalman Filter (EKF) attenuates noisy signals. Simulation results demonstrate strong adaptability to changes in model parameters, and superior performance when compared to Proportional Integral Derivative (PID), Integrator BackStepping (IBS), and offline decentralized Multi-Layer Perceptron (MLP) algorithms, in terms of parameter convergence, disturbance compensation control, and noise attenuation.

Direct Tilt Controller Design with Disturbance Compensation and Implementation for a Narrow Tilting Electric Vehicle

Three-wheeled electric city vehicles are becoming popular because they have lower cost and enable motorcycle driving feeling with electric powertrain performance. These vehicles need a driver assistant system, also known as an active tilting stability controller, to provide a safe cornering manoeuvre. Active tilt control methods are direct tilt control (DTC), steering tilt control (STC) and a combination of these methods. In this study, DTC system design with a servo motor actuator with simulation and experimental results are presented. State feedback control with pole placement design has been improved with disturbance compensation control. This novel controller structure enhances the response of DTC and enables a faster-tilting response. Simulation results are given up to 10 m/s speed. Experimental results of the developed method are given up to 3.05 m/s (11 km/h) speed on a three-wheeled electric vehicle. The speed control loop of the servo motor drive unit (SMDU) stabilizes the DTC system. In the state of the art, a proportional derivative controller is commonly used as a tilt controller. By including the speed control loop of SMDU in the tilt control system, the use of the derivative term can be eliminated. The stability effect of the speed control loop is shown by MATLAB analysis, simulations in Simulink and experimental step response test as well.

Transmission characteristics analysis and disturbance compensation control strategy for two-inertia system with a flexible link

Transmission characteristics analysis and disturbance compensation control strategy for two-inertia system with a flexible link

Variable-horizon predictive tracking control for air-breathing hypersonic vehicle based on composite disturbance observer

In this paper, a variable-horizon predictive tracking control (VHPTC) scheme based on composite disturbance observer (CDO) is proposed to investigate the attitude tracking problem for an air-breathing hypersonic vehicle (AHV) subject to external matched and mismatched disturbances. An explicit predictive tracking control term with the variable horizon is employed to reduce the online computation and improve the control performance of the AHV system. To comprehensively suppress the negative influences caused by the matched and mismatched disturbances, a CDO is constructed to estimate the unknown disturbances. Moreover, to further guarantee the stability of the closed-loop system affected by the resulting disturbance estimation error, the auxiliary control term is presented. Combining the predictive tracking control term with the variable horizon, the auxiliary control term, and the disturbance compensation control term obtained by CDO, the entire VHPTC law for the AHV system is obtained. Through the Lyapunov analysis, the rigorously exponential stability of the closed-loop system is ensured by the proposed CDO-based VHPTC scheme. The simulation results demonstrate the effectiveness of the presented strategy for the AHV attitude system.

Iterative Learning Control for Tricalcium Neutralization Process with Initial Disturbance

AbstractThe tricalcium neutralization process (TNP) is a key recovery process in the citric acid production process. The amount of calcium carbonate added needs to be controlled to ensure the pH of the reactants within the target range at the terminal of every batch. But the random initial pH has a great influence on the stability of the terminal pH. In this work, an iterative learning control (ILC)‐based control strategy is proposed to optimize the addition of calcium carbonate. First, the terminal iterative learning control (TILC) is performed and the optimal input of the process can be obtained. Then, an initial disturbance compensation controller optimized by ILC is proposed. The results of the TNP control experiments demonstrate that the suggested control strategy can suppress the disturbances and achieve terminal pH control.

A Disturbance Force Compensation Framework for a Magnetic Suspension Balance System

The research on the dynamic characteristics of vehicles requires wind tunnel tests. The natural mass frequency of the support mechanism and the interference of the support mechanism on the flow field will greatly reduce the repeatability and accuracy of the experimental results. The magnetic suspension and balance system (MSBS) uses non-contact electromagnetic force instead of mechanical support to eliminate the support mechanism’s interference with the test results. The MSBS needs to actively adjust the electromagnetic force to control the position of the tested model. At present, its control strategy is PID control. However, when the wind tunnel is opened, there will be large aerodynamic loads, leading to large changes in displacement. We propose a disturbance compensation control algorithm framework that can quickly estimate the external force disturbance and quickly compensate it to the control loop, reduce the influence of the disturbance on the control system, and provide stability and accuracy of displacement control.

Strict Sliding Mode Control with Power Reaching Law and Disturbance Bounds in Synchronous Servo Tracking Drive System

This paper presents the analysis and synthesis results of a sliding mode controller for tracking drive systems using a synchronous servo motor and its accompanying power amplifier. Considering a Permanent Magnet Synchronous Motor (PMSM) and its accompanying Power Amplifier (PA) as one object, the strict control law using traditional sliding-surface reaching speed and additional exponential components has created the anti-disturbance torque control signal for the system. Synthesis of the sliding mode controller is guaranteed mathematically based on Lyapunov stability. The disturbance compensation control component is quantified based on the upper and lower bounds of disturbance. Simulation in Matlab shows visual research findings.

Q-learning–based practical disturbance compensation control for hypersonic flight vehicle

Aiming at the attitude control problem of hypersonic flight vehicle, a compound control strategy based on the disturbance compensation technique and Q-learning optimization is proposed. Firstly, a three-channel independent control scheme based on the super-twisting extended state observer (STESO) is proposed such that coupling among channels, uncertainties, and external disturbances can be estimated and compensated in real time. Secondly, the Q-learning mechanism is introduced to optimize the control parameters while keeping the control structure unchanged. Lastly, the convergence of the STESO is analyzed by the Lyapunov theory, and some numerical simulation results are carried out to verify the effectiveness of the proposed strategy. Compared with the traditional linear active disturbance rejection control, the proposed method can avoid a lot of manual parameter tuning process and also has better performance.

Conditional Disturbance Negation Based Control for an Omnidirectional Mobile Robot: An Energy Perspective

Disturbances widely exist in all control systems. Disturbance observers are commonly employed to estimate the disturbances which are often fully compensated in the control signal. However, one rarely recognized fact is that disturbances may be beneficial to the control performances and thus can be effectively exploited. In this letter, from an energy balance point, a conditional disturbance negation (CDN) control scheme is designed for an omnidirectional mobile robot, yielding a physically interpretable design. By energy analysis, the forces imposed on the robot are classified into workless force, internal damping force, and lumped disturbance force, wherein the later two are effectively exploited. A judgment function is designed to determine whether the disturbance is beneficial to the control performance, allowing the controller to selectively compensate the estimated disturbances. Convergence of the proposed control system is analyzed. Finally, both simulations and experimental results show that the proposed control scheme can achieve better performance against conventional full disturbance compensation control scheme, if the disturbances contain beneficial parts.

Fuzzy Compensation and Load Disturbance Adaptive Control Strategy for Electro-Hydraulic Servo Pump Control System

Aiming at the high-precision position control of electro-hydraulic servo pump control system, a compensation control algorithm based on fuzzy control theory is proposed based on the classical PID control algorithm for the control of factors such as oil compression and system leakage. Firstly, a mathematical model of the system was established, and online identification of load disturbance was carried out. Then, oil compression and system leakage compensation controllers were established, and the position error caused by the load disturbance was compensated based on fuzzy control rules. Finally, the position control effect was verified using an experimental platform. The results show that the load disturbance compensation control strategy can significantly reduce the influence of load disturbance of the system. The steady-state accuracy of the system reached ±0.01 mm, which significantly enhanced the anti-disturbance ability of the system.

Optimized control strategy based on EPCH and DBMP algorithms for quadruple-tank liquid level system

According to the actual production requirements in process control, this paper proposes an optimized control strategy for the quadruple-tank liquid level system (QTLLS). Firstly, using the Bernoulli’s law and mass conservation principle, the dynamic mathematical model of QTLLS is established and linearized. Secondly, the state error port controlled Hamiltonian (EPCH) controller is designed by Hamiltonian system model construction which utilize the Hamiltonian principle, and a disturbance observer(DOB) is chosen to compensate disturbances impact. Thirdly, a deadbeat model predictive (DBMP) control algorithm with discrete-time disturbance observer (DTDOB) is proposed. Finally, in order to establish an optimized control strategy, an optimized function is proposed, which can give full play to the advantages of DBMP-OB algorithm with fast dynamic response and EPCH-OB algorithm with good steady-state performance. A wealth of results from simulation and experimental fully confirm the superiority of the proposed control strategies compare with proportional–integral–derivative (PID) control and sliding mode control (SMC). Moreover, the proposed optimized control strategy has been realized position control, tracking control and disturbance compensation control in this paper. It meets the needs of production and has great industrial application prospects.

A Novel Control Strategy of Crosswind Disturbance Compensation for Rack-Type Motor Driven Power Steering (R-MDPS) System

The wind suddenly blown to the side of the car (i.e, cross-wind effect) is considered as one of the major lateral disturbances, which causes the unstable motion of the vehicle and the persistent driving fatigue for the driver who tracks the desired travel path. In particular, a commercial vehicle having a large side area is greatly affected by this effect. Therefore, many related automotive/car manufacturers still wish to equip their Advanced Driving Assistant System (ADAS) with the crosswind disturbance compensation control system. Meanwhile, in recent advanced vehicle systems, a rack-type motor-driven power steering (R-MDPS) system is more widely used than a column-type MDPS (C-MDPS) due to the structure advantage and the effective steering assistance. Recognizing those two issues, this paper investigates a novel anti-control and estimation strategy of crosswind disturbance for the R-MDPS system of vehicles with non-negligible side surfaces. Specifically, an adaptive disturbance observer (D.O.B) has been proposed to estimate the crosswind effect. Furthermore, using optimal control theory, the compensation control system is designed to assist the driver in two possible situations. One is for when the driver continues to steer the vehicle under the effect of the crosswind, and the other is for when the driver temporarily loses steering control due to the effect. In addition, the control mode selection conditions between two controls are clearly presented to maximize the efficiency and performance of the proposed control system. Finally, the effectiveness of the proposed control system has been evaluated based on the Simulink/Carsim Co-simulation and HILS environments.

Composite control with observers for a class of stochastic systems with multiple disturbances

<p style='text-indent:20px;'>In this paper, the composite anti-disturbances control problem is considered for a class of stochastic systems with multiple disturbances. The states of the system are assumed to be unavailable. A state observer and a disturbance observer are constructed to estimate the states and the matched disturbance respectively. Based on the estimated values of state observer and disturbance observer, a non-fragile composite controller is designed to achieve disturbance attenuation and rejection. By means of the technique of the disturbance compensation control and stochastic control theory, some sufficient conditions are obtained to guarantee that the closed-loop system is asymptotically bounded in mean square or asymptotically stable in probability. Finally, a numerical example is given to verify the validity of the obtained results.</p>

Voltage disturbance compensation based on impedance modeling of DFIG under weak grid

This paper proposes a grid voltage disturbance compensation control for the stability of the DFIG system under weak grid conditions. A detailed impedance model of the DFIG system, including the generator, the inner and outer control loops of the rotor side converter (RSC) and grid side converter (GSC), the DC-link and phase locked loop (PLL) dynamic, is developed in the d-q synchronous reference frame. Based on the proposed model, the relationship between the outputs of the controllers and the grid voltage disturbance at the point of common coupling (PCC) can be obtained. Then, the compensation control of the grid voltage disturbance is integrated to the current controllers of RSC and GSC to improve the stability of the DFIG system connected to the weak grid. In this paper, the effectiveness of the proposed compensation control strategy is proved using the generalized Nyquist criterion (GNC), which illustrates that the compensation control strategy implemented in RSC and GSC simultaneously has a better ability to maintain the stability of the DFIG system under weak grid conditions than only one side applied. The simulation results verify the analysis.

Three controllers via 2nd-order sliding mode for leader-following formation control of multi-robot systems

The multi-robot formation has always been an attractive field for cooperative control of robots. This paper uses the improved second-order sliding mode method to control the leader-following formation system. The traditional second-order sliding mode control is not perfect because the disturbances and uncertainties of the system may cause the compensation control to overestimate. The adaptive gain super-twisting sliding mode control suppresses the output oscillation and speeds up the system response by improving the gain function and adding a differential link. However, this method is generally applied to single-input single-output systems. This paper attempts to apply this method to a multi-input-multi-output leader-following formation system and improve its switching function and compensation control part. We use the estimators, i.e., the extreme learning machine and the nonlinear disturbance observer. These estimators can observe disturbance changes to replace the adaptive gain function to realise disturbance estimation and compensation control. Then combine the extreme learning machine and the nonlinear disturbance observer with the super-twisting sliding mode control to produce two new sliding mode methods. We use the Lyapunov method to prove the system stability as well. Finally, we illustrate the feasibility of the three control methods.

Event-based disturbance compensation control for discrete-time SPMSM with mismatched disturbances

This paper investigates the problem of event-based disturbance compensation control for discrete-time surface-mounted permanent magnet synchronous motor (SPMSM) subject to both mismatched external disturbances and the limited communication bandwidth. The mismatched external disturbances make it impossible to transform the original model into the multiple-step-ahead predictor model by using the existing predictor technology. To tackle such a challenge, a novel backstepping-based disturbance compensation control framework is firstly proposed for the discrete-time SPMSM with known system dynamics. In the proposed framework, the disturbance observer is designed to compensate for the external disturbances, and the novel variable substitution/decoupling technology is proposed to design the event-based controller for the original controlled system. The proposed controller is composed of the event-based feedback control signal and the feedforward disturbance compensation signal, thereby improving the system disturbance rejection ability and mitigating the communication resource. Subsequently, an event-based adaptive neural control scheme is proposed by combining a modified neural disturbance observer. The proposed scheme ensures that the tracking error converges to a small neighbourhood of the origin, all the signals in the closed-loop system are bounded and meanwhile the communication resources are greatly reduced. The effectiveness of the proposed controller is illustrated through the simulation results.