Disturbance Estimation Research Articles

Performance Optimization with LPV Synthesis for Disturbance Attenuation in Planar Motors

Optimizing the performance of motion control systems with variations in nonlinear parameters is not an easy task. To accomplish this task, it is important to design the controller using the linear system approach. In this study, a linear parameter varying (LPV) control method is proposed in which nonlinearities are treated as parameter variations for planar motors. The proposed control method consists of the force and torque modulation with the commutation scheme and the nonlinear current controller with H∞ state feedback control in the form of LPV synthesis to improve the position-tracking performance. An interpolated gain-scheduling controller based on LPV synthesis is determined by applying H∞ control to a linear matrix inequality technique. An interpolated gain-scheduling controller can attenuate disturbance without disturbance estimation. The effectiveness of the proposed control method is evaluated using simulation results and compared with the conventional proportional–integral–derivative control to verify both improved position-tracking performance and disturbance attenuation.

Real‐Time Implementation of Unknown Input Observer‐Based State and Unknown Disturbance Estimation for Series Active Filters

ABSTRACTSeries active filter (SAF) is generally utilized in compensating harmonic voltage source‐type loads. In this paper, a combined action of controller and observer is proposed for SAF. Full state feedback (SFB) and linear quadratic regulator (LQR) controllers are posited in order to estimate states, and fault. SFB utilizes the pole placement method, whereas LQR utilizes the tuning of matrices by Bryson's rule. Luenberger observer (LO), proportional–integral observer (PIO), and unknown input observer (UIO) were also designed. The efficacy of this scheme is illustrated through the simulations, in the presence of faults. The state dynamics of SFB‐ and LQR‐based control of SAF with LO, PIO, and UIO in different faulty cases are compared. It can be clearly seen through simulations that the state dynamic response of LQR‐based control of SAF is faster when compared to SFB‐based control of SAF in both cases. Further, LO and PIO established a steady‐state error between the actual state and its estimate, with reference to desired input, in the presence of a fault. UIO perfectly tracked the desired input, even in the presence of various unknown fault, when compared to LO and PIO. Furthermore, UIO also estimates the unknown faults better when compared to PIO. Finally, in a dynamic operating scenario, the effectiveness of the suggested control strategy has been assessed and verified using MATLAB/SIMULINK and the output of a real‐time simulator (OPAL‐RT OP4510).

Distributed Bipartite Consensus of Multi-Agent Systems via Disturbance Rejection Control Strategy

This work aims to focus on analyzing the consensus control problem in cooperative–competitive networks in the occurrence of external disturbances. The primary motive of this work is to employ the equivalent input-disturbance estimation technique to compensate for the impact of external disturbances in the considered multi-agent system. In particular, a suitable low-pass filter is implemented to enhance the accuracy of disturbance estimation performance. In addition, a specific signed, connected, and structurally balanced undirected communication graph with positive and negative edge weights is considered to express the cooperation–competition communication among neighboring agents. The cooperative–competitive multi-agent system reaches its final state with same magnitude and in opposite direction under the considered structurally balanced graph. By utilizing the properties of Lyapunov stability theory and graph theory, the adequate conditions assuring the bipartite consensus of the examined multi-agent system are established as linear matrix inequalities. An illustrative example is delivered at the end to check the efficacy of the designed control scheme.

Reliable Finite‐Time Control for Nonlinear Chaotic Semi‐Markov Jump Systems With Incomplete Transition Rates

ABSTRACTThis article studies the finite‐time control problem for a class of nonlinear chaotic semi‐Markov jump systems with incomplete transition rates described by the T‐S fuzzy model approach. As a means to depict the dynamical properties pertaining to the examined system, parametric uncertainties, faults, external disturbances and input saturation are taken into consideration. The foremost objective of this study is to come up with a composite control mechanism that effectively rejects and attenuates the repercussions of faults and disturbances. In particular, we primarily built a disturbance observer in order to obtain a precise estimation of the external disturbances. After which, the fault diagnosis observer is designated to effectively estimate the faults. Specifically, a composite reliable control mechanism is developed by fusing the output of the constructed observers with the mode‐dependent fuzzy‐rule based state feedback controller. By employing suitable Lyapunov functions in conjunction with the linear matrix inequality technique, a set of mode‐dependent conditions is derived to ensure the finite‐time stochastic boundedness of the underlying closed‐loop and estimation error systems. Following this, the anticipated controller and observer gain matrices are elicited by resolving the established linear matrix inequalities. Thereafter, intending to ascertain the efficacy and usefulness of accrued theoretical findings, simulation results performed on Chua's circuit system is endowed.

Predefined time attitude control of aircraft based on predefined time sliding mode control

This paper proposes a sliding mode control strategy with predefined time convergence for addressing the attitude control problem of aircraft. Firstly, a predefined time extended state observer is developed to realize the estimation of modelling error, uncertainty and external disturbance of aircraft within a predefined time. Secondly, a predefined time non-singular terminal sliding mode and a predefined time sliding mode reaching law are proposed for attitude control of aircraft. Especially, to address potential singularities arising from negative power terms, a switching strategy is employed. Finally, the numerical simulations and Monte Carlo test are used to validate the effectiveness of the proposed controller.

A semi-analytical transient undisturbed velocity correction scheme for wall-bounded two-way coupled Euler-Lagrange simulations

Force closure models employed in Euler-Lagrange (EL) point-particle simulations rely on the accurate estimation of the undisturbed fluid velocity at the particle center to evaluate the fluid forces on each particle. Due to the self-induced velocity disturbance of the particle in the fluid, two-way coupled EL simulations only have access to the disturbed velocity. The undisturbed velocity can be recovered if the particle-generated disturbance is estimated. In the present paper, we model the velocity disturbance generated by a regularized forcing near a planar wall, which, along with the temporal nature of the forcing, provides an estimate of the unsteady velocity disturbance of the particle near a planar wall. We use the analytical solution for a singular in-time transient Stokeslet near a planar wall (Felderhof [1]) and derive the corresponding time-persistent Stokeslets. The velocity disturbance due to a regularized forcing is then obtained numerically via a discrete convolution with the regularization kernel. The resulting Green's functions for parallel and perpendicular regularized forcing to the wall are stored as pre-computed temporal correction maps. By storing the time-dependent particle force on the fluid as fictitious particles, we estimate the unsteady velocity disturbance generated by the particle as a scalar product between the stored forces and the pre-computed Green's functions. Since the model depends on the analytical Green's function solution of the singular Stokeslet near a planar wall, the obtained velocity disturbance exactly satisfies the no-slip condition and does not require any fitted parameters to account for the rapid decay of the disturbance near the wall. The numerical evaluation of the convolution integral makes the present method suitable for arbitrary regularization kernels. Additionally, the generation of parallel and perpendicular correction maps enables to estimate the velocity disturbance due to particle motion in arbitrary directions relative to the local flow. The convergence of the method is studied on a fixed particle near a planar wall, and verification tests are performed in the Stokes regime on a settling particle parallel to a wall and a free-falling particle perpendicular to the wall.

Robust deadbeat predictive current control for unipolar sinusoidal excited SRM with multi-parameter mismatch compensation

In the control of unipolar sinusoidal excited switched reluctance motors (SRMs), deadbeat predictive current controllers (DPCCs) have gained attention for their enhanced dynamic performance. However, periodic disturbances caused by mismatches between the predictive model’s nominal and actual system parameters degrade the control performance of SRMs. To address this issue, a robust DPCC with multi-parameter compensation is proposed to improve dq0-axes current control performance. By analyzing the impact of parameter mismatches, a Kalman filter (KF) is developed to compensate for inductance coefficient mismatches, mitigating periodic disturbances. Additionally, a disturbance estimator with measurement noise suppression is integrated into the DPCC for both state and disturbance estimation to handle residual uncertainties, including winding resistance mismatches, magnetic saturation, and unmodeled dynamics. Compared simulation and experimental results validate the effectiveness of the proposed robust DPCC.

The Precision Improvement of Robot Integrated Joint Module Based on a New ADRC Algorithm

This article analyzes the factors causing the precision error of the robot joint module, such as gear meshing disturbance, output elastic deformation, and load mutation. An improved active disturbance rejection control (ADRC) algorithm is proposed to overcome the uncertainty of nonlinear factors and variables of this research topic. The output precision loss of the joint module is introduced as a new input variable of ADRC, combined with the input variable of torque current of the joint module. The extended state observer is redesigned, and the online estimation of disturbance is realized. According to the disturbance estimation results, the current loop algorithm of permanent magnet synchronous motors is improved to compensate the torque disturbance of the robot joint module. The experimental results show that the improved ADRC algorithm can obviously suppress the disturbance of the joint module, weaken the meshing error and torque output deformation of the harmonic reducer gear, and improve the control accuracy of the joint module.

Disturbance observer based adaptive predefined‐time sliding mode control for robot manipulators with uncertainties and disturbances

AbstractThis article develops a predefined‐time sliding mode control approach for systems with external disturbances and uncertainties through a nonlinear disturbance observer (DO). For addressing predefined‐time stabilization problem of robotic manipulator system, a predefined‐time sliding mode surface is proposed, ensuring system states converge to origin within a predefined‐time once sliding mode surface is attained. Compared to conventional fixed‐time and finite‐time control strategies, a distinctive advantage of this scheme is that system settling time can be explicitly chosen in advance and independent of system states. To achieve predefined‐time performance, a disturbance observer is introduced to generate the disturbance estimate, which can be incorporated into controller to counteract disturbance. To address the systems uncertainty, an adaptive law is employed to estimate the unknown upper boundary of system uncertainties. Finally, the effectiveness and performance of the proposed scheme are illustrated by simulation and experiment.

Stabilization of LTI systems with both uncertainties and external disturbances via DE-based control method

This paper is concerned with the stabilization of linear time-invariant (LTI) systems with unknown parameters and external disturbances. Firstly, four types of suitable filters are presented and applied to achieve the accuracy estimate of the disturbances. Based on these filters, four types of disturbance estimators are designed and used to asymptotically cancel the corresponding disturbances. Secondly, an adaptive disturbance estimator (DE)-based control method is obtained by combining the adaptive control method with the DE-based control method. It is noted that the algebraic representation of the adaptive feedback control law is given in a more concise form by the tool of the semi-tensor product of matrix. Further, the stabilization of LTI systems is achieved by the obtained adaptive DE-based control method. Finally, three numerical examples with computer simulation are provided to verify the correctness and validity of the obtained theoretical methods.

Low-Complexity Tracking Control of Unknown Strict-Feedback Systems With Quantitative Performance Guarantees.

This article is concerned with the prescribed performance tracking control problem for the strict-feedback systems with unknown nonlinearities and unmatched disturbances. The challenge lies in the realization of a complete performance specification for trajectory tracking in the sense of quantitatively regulating the peak value, overshoot, settling time, and accuracy while ensuring that the initial condition holds naturally. To this end, an error transformation, equipped with a shifting function, is introduced and incorporated with a new-type barrier function. Then, a class of performance functions is exploited to quantify the settling times and steady-state bounds of the intermediate errors. Moreover, to improve the flexibility of formulating performance specifications for the tracking error, a pair of asymmetric performance boundaries are further designed. With their combination, a novel robust prescribed performance control (PPC) approach is proposed in this article. It not only achieves the quantitative performance guarantees but also preserves the unique simplicity of PPC, evading the needs for function approximation, parameter identification, disturbance estimation, derivative calculation, or command filtering. The above theoretical findings are confirmed via three simulation studies.

Force-Coordination Control for Aerial Collaborative Transportation Based on Lumped Disturbance Separation and Estimation

Force-Coordination Control for Aerial Collaborative Transportation Based on Lumped Disturbance Separation and Estimation

Control Based on Nonlinear Estimators of Parametric Uncertainties Applied to an Agricultural Tractor Equipped with a Towed Implement System

This article presents a nonlinear control strategy designed to address parametric uncertainties in an agricultural tractor system coupled to a towed implement. The controller ensures accurate tracking of lateral and yaw velocities relative to desired reference trajectories, even under the presence of parametric variations and external disturbances. The reference trajectories are derived from an “ideal” tractor model, excluding the effects of the towed implement. A High-Order Sliding Mode (HOSM) estimator is employed to provide an estimation of disturbances, which are subsequently mitigated by the controller to maintain system stability and precision. The effectiveness of the proposed control strategy is validated through Matlab-Simulink simulations, which include a double-step steer maneuver. This maneuver tests the system’s ability to handle abrupt steering changes, providing insight into the controller’s robustness and its capacity to ensure accurate trajectory tracking in demanding conditions.

Dynamic Double Event-Triggered Anti-Disturbance Tracking Control for a 2-DOF Small Unmanned Helicopter.

This article devises a new dynamic double event-triggered anti-disturbance tracking control scheme for a 2-degree of freedom (DOF) laboratory helicopter subject to external time-varying disturbances and load fluctuation by using the generalized proportional-integral observer technique. The helicopter system is separated into two subsystems in the proposed control method, i.e., the pitch subsystem and the yaw subsystem. Each subsystem includes a discrete-time dynamic double event-triggering mechanism (DDETM), and the control laws of the two subsystems are independent of each other. There are two triggering conditions in the designed double triggering mechanism: one is designed based on the system states and the other is based on the lumped disturbance estimation. These two triggering conditions form a competitive relationship such that the controller updates the control signal as long as one of the triggering conditions is satisfied. Theoretical analysis is provided for achieving the better communication and control performance of the proposed DDETM-based robust control method. Through rigorous stability analysis, it is proved that the closed-loop hybrid system is globally ultimately bounded. At last, numerical simulations show that the suggested control strategy not only reduces the event-triggering number, but also improves the initial dynamic performance of the system.

Enhanced Impedance Control of Cable-Driven Unmanned Aerial Manipulators Using Fractional-Order Nonsingular Terminal Sliding Mode Control with Disturbance Observer Integration

The article presents a novel control strategy for cable-driven aerial manipulators (UAMs) aimed at enhancing impedance control during contact operations in complex environments. A fractional-order nonsingular terminal sliding mode control (FONTSMC) integrated with a disturbance observer (DOB) is proposed to improve the robustness and precision of the UAM under lumped disturbances. This developed approach utilizes the flexibility of fractional calculus, the finite-time stability of nonsingular terminal sliding mode, and the real-time disturbance estimation capabilities of the DOB to ensure smooth and compliant contact interactions. The effectiveness of the proposed control strategy is validated through comprehensive simulation studies, which demonstrate significant improvements in control performance, stability, and disturbance rejection when compared to traditional methods. The results indicate that the FONTSMC-DOB framework is highly suitable for complex aerial manipulation tasks, offering both theoretical and practical insights into the design of advanced control systems for UAMs.

Complementary extended state observer‐based model‐free sliding mode control for a PMSM in cathode copper production

AbstractThis study introduces a model‐free sliding mode control scheme based on a complementary extended state observer (CESO) for a permanent magnet synchronous motor (PMSM) in cathode copper production. First, an ultra‐local model of the PMSM is proposed. Compared with the existing ultra‐local model, the ultra‐local model proposed in this study divides the disturbances into periodic and aperiodic perturbations. Furthermore, based on the proposed ultra‐local model, a CESO is proposed. Compared to the linear extended state observer (LESO) and the non‐linear extended state observer (NLESO), the proposed CESO combines the advantages of the LESO and the NLESO. The proposed CESO exhibits reduced disturbance estimation errors and greater resilience to significant periodic and minor aperiodic disturbances. By leveraging the ultra‐local model, a novel combined control strategy is devised, utilizing the CESO and a model‐free sliding mode control. The stability of the proposed control scheme has been verified through the Lyapunov stability theorem and the Hurwitz stability criterion. Subsequently, comparative simulations on disturbance rejection are conducted under periodic and aperiodic disturbances, illustrating the efficacy of the proposed control approach.

Reinforcement learning-based robust formation control for Multi-UAV systems with switching communication topologies

This paper introduces a novel optimal robust formation method for quadcopter multiple unmanned aerial vehicle (multi-UAV) systems. Firstly, a reinforcement learning (RL) algorithm based on a unique gradient descent training approach is proposed to solve the Hamilton–Jacobi–Bellman (HJB) equation, which can effectively eliminate the requirement of the Persistent Excitation (PE) condition. Secondly, the robustness of the controlled system is emphasized, and an Uncertainty and Disturbance Estimator (UDE) observer is developed to suppress model uncertainty and external disturbances through filtering techniques. Furthermore, a switched sliding mode control technique according to the average dwell time (ADT) is employed to convert switching communication topology between UAVs dynamically, and the stability analysis of the corresponding closed-loop control systems is then performed by the use of Lyapunov analysis. Finally, the simulation examples are provided to verify the effectiveness of the designed control strategy.

Reinforcement learning intermittent optimal formation control for multi-agent systems with disturbances

Abstract This paper investigates disturbance-resistant intermittent event-triggered optimal formation control problems of second-order multi-agent systems by using the reinforcement learning method, which takes into account the influence of network damage including denial-of-service (DoS) and deception attacks, stochastic noises, and unknown external disturbances. Firstly, we propose a novel disturbance observer based on adaptive control to estimate unknown external disturbances under an event-triggered mechanism. Secondly, by use of estimation of disturbances, an innovative intermittent event-triggered optimal formation algorithm is given. By applying theories such as Lyapunov stability and stochastic stability, sufficient conditions are derived to guarantee that all agents achieve the desired formation in mean square sense. Additionally, in the model-free case, the optimal controller is solved using the least squares method, which is computationally less complex than some existing approaches. Finally, the theoretical results are effectively validated through simulation examples.

Stability analysis of flying wing layout aircraft based on radial basis function neural network model

PurposeTo ensure the stability of the flying wing layout unmanned aerial vehicle (UAV) during flight, this paper uses the radial basis function neural network model to analyse the stability of the aforementioned aircraft.Design/methodology/approachThis paper uses a linear sliding mode control algorithm to analyse the stability of the UAV's attitude in a level flight state. In addition, a wind-resistant control algorithm based on the estimation of wind disturbance with a radial basis function neural network is proposed. Through the modelling of the flying wing layout UAV, the stability characteristics of a sample UAV are analysed based on the simulation data. The stability characteristics of the sample UAV are analysed based on the simulation data.FindingsThe simulation results indicate that the UAV with a flying wing layout has a short fuselage, no tail with a horizontal stabilising surface and the aerodynamic focus of the fuselage and the centre of gravity is nearby, which is indicative of longitudinal static instability. In addition, the absence of a drogue tail and the reliance on ailerons and a swept-back angle for stability result in a lack of stability in the transverse direction, whereas the presence of stability in the transverse direction is observed.Originality/valueThe analysis of the stability characteristics of the sample aircraft provides the foundation for the subsequent establishment of the control model for the flying wing layout UAV.

Polynomial filter-based adaptive fault-tolerant control for a class of nonlinear systems with multiplicative faults

In this article, the problem of fault-tolerant control is investigated for polynomial nonlinear systems (PNSs) subject to multiplicative faults and measurement noise. Firstly, a matrix Taylor expansion technique is applied to transform the PNS into a linear parameter varying system. Then the polynomial filter is constructed to get estimations of states and unmatched disturbances, which reduces the effect of measurement noise. A novel adaptive fault-tolerant controller is proposed to compensate for multiplicative faults and unmatched disturbances. Furthermore, the condition of the parameter-dependent linear matrix inequality (PDLMI) is deduced, which guarantees the boundedness of tracking errors and estimation errors, and the sum of squares (SOS) decomposition technique is utilized to solve PDLMI. Finally, the simulation of a rotary steerable drilling tool system confirms the feasibility of the proposed adaptive fault-tolerant control framework.