Unknown Load Disturbances Research Articles

An Anti-Disturbance Extended State Observer-Based Control of a PMa-SynRM for Fast Dynamic Response

The control system of PMa-SynRMs (Permanent Magnet-assisted Synchronous Reluctance Machines) exhibit susceptibility to external disturbances, thereby emphasizing the utmost significance of employing an observer to effectively observe and suppress system disturbances. Meanwhile, disturbances in load are sensitive to control system noise, which may be introduced from current sensors, hardware circuit board systems, sensor-less control, and analog position sensors. To tackle these problems, this paper proposes an A-DESO (anti-disturbance extended state observer) to improve the dynamic performance, noise suppression, and robustness of PMa-SynRMs in both the constant torque and FW (flux weakening) regions. With the proposed A-DESO, lumped disturbance in torque could be detected, and speed could be extracted in position with unmeasurable noise. Thanks to the merits of the small observation error in the low-frequency region and the excellent anti-disturbance performance in the high-frequency region of the proposed A-DESO, the control of the PMa-SynRM features the advantages of a fast response and good noise immunity ability within the same observation error range. The proposed A-DESO presents a shorter convergence time and a better noise suppression ability, which leads to a better dynamic response of the PMa-SynRM when encountering an unknown load disturbance compared to the traditional ESO-based control, according to simulations and experiments.

Adaptive Position Control Strategy of SRM-Based EMA System for Precision Position Tracking

The electromechanical actuator (EMA) driven by switched reluctance motor (SRM) is promising to be used in the steering vane control system on the landing craft air cushion (LCAC) hovercraft due to its reduced maintenance costs and increased control flexibility. However, the system parameter uncertainty, the unknown load disturbance, and the large torque ripple of SRM make it challenging to achieve high position control precision. To improve the position control accuracy of the SRM-based EMA system, an adaptive position control strategy is proposed in this paper. Firstly, an adaptive fast terminal sliding mode controller (AFTSMC) is designed to address the issues of model parameter estimation and load disturbance rejection, which improves the dynamic response performance of the SRM-based EMA system. Secondly, a current-limited direct torque controller (CL-DTC) is proposed to track the reference torque calculated by AFTSMC with lower torque ripple and to limit the excessive currents of SRM at the same time, which helps further enhance the position control precision and prevent the SRM-based EMA from overheating. Finally, the proposed position control strategy is tested and compared with other three position controllers based on simulations and experiments. The results demonstrate the effectiveness and superiority of the proposed position control strategy.

Disturbance Observer based Backstepping Control for Electro-hydraulic Position Servo System of the Projectile Coordination Arm

Due to the existence of unmodeled friction and unknown load disturbance, the position tracking control of electro-hydraulic position servo system of projectile coordination arm becomes an important problem to be solved urgently. In this paper, a dynamic surface backstepping control strategy is proposed based on the disturbance observer(DOB). To be specific, the disturbance observer is applied to estimate the unknown disturbance force, and the backstepping controller realizes the position tracking control. In order to improve the position tracking performance, The estimated value of the observer output is brought into the backstepping controller to realize the model compensation of the disturbance. Meanwhile, the dynamic surface method is utilized to handle the differential explosion problem in the backstepping method. The global stability of the closed-loop system is verified by Lyapunov stability theory. The co-simulation results show that the proposed method can effectively compensate the unknown disturbance in the electro-hydraulic position servo system, and has better tracking performance and strong robustness.

Saturated adaptive feedback control of electrical‐optical gyro‐stabilized platform based on cascaded adaptive extended state observer with complex disturbances

AbstractIt is still an open and challenging issue to the typical position control problems of the three‐axis electrical‐optical gyro‐stabilized platform systems (TEOGSP), due to inherent characteristics, for example, measurement noise, input saturation, parametric uncertainties, largely unknown load disturbance. To solve this problem, a saturated adaptive robust feedback controller using an adaptive cascaded extended state observer (SAFCESO) is proposed for compromising between the measurement noise effect and the sensitivity to disturbances. Firstly, the matched and mismatched disturbances existing in the TEOGSP system are estimated and rejected by the cascaded adaptive extended state observers (CESO). Secondly, the parametric uncertainties are evaluated by the adaptive control, and the match disturbances are attenuated by the robust control. Moreover, the adaptive robust control law does not require the velocity measurement signal and internal dynamics information of the system, which is practical to implement. Hence, all various uncertainties could be mainly compensated. Then, the improved auxiliary systems governed by smooth switching functions are developed and incorporated into the control design to compensate for the effect of the input saturation. Finally, the command filters are introduced to limit the magnitude of the virtual control and to calculate the derivative of the virtual control, respectively. The extensive comparative experimental results in the TEOGSP systems showed that the proposed SAFCESO method had superiorities in terms of high‐precision tracking accuracy, robustness, and noise reduction.

Modeling and Position Control of the HASEL Actuator via Port-Hamiltonian Approach

This paper deals with the modeling and control problem of a Hydraulically Amplified Self-healing Electrostatic (HASEL) actuator based on the port-Hamiltonian framework. A nonlinear spring-damper system is used to approximate the mechanical deformation of the actuator due to the motion of the fluid while a nonlinear capacitance is used to approximate the electric behavior of the system. The actuator position control strategy is investigated based on the Interconnection Damping Assignment-Passivity Based Control (IDA-PBC) method, with further Integral Actions (IA) added to cope with load uncertainties. The proposed model and control laws are validated on an experimental benchmark. The experimental tests demonstrate that the proposed model is accurate up to 94% of fitness. The controllers allow assigning the actuator position with ramp and sinusoidal references with the relative error less than 5%. At last, the robustness of the proposed IDA-PBC controller with IA has been shown with the experimental result for the unknown load disturbance rejection.

Speed sensorless nonlinear adaptive control of induction motor using combined speed and perturbation observer

High performance induction motors (IM) require a robust and reliable speed controller to maintain the speed tracking performance under various uncertainties and disturbances. This paper presents a sensorless speed controller for IM based on speed and perturbation estimation and compensation. By defining a lumped perturbation term to include all unmodeled nonlinear dynamics and external disturbances, two state and perturbation observers are designed with combining the model reference adaptive system (MRAS) based speed observer to estimate the flux and speed states and the flux- and speed-loop related lumped perturbation terms. The estimated flux, speed and perturbation terms are used to design an output feedback, speed sensorless nonlinear adaptive controller (SSNAC) for IM. The stability of the closed-loop system is addressed in Lyapunov theory. Effectiveness of the SSNAC is verified via simulation and experiment tests. Comparing with the standard vector control plus MRAS speed observer (VC-MRAS), the proposed SSNAC reduces the speed tracking error by 20% to 30% on average under model uncertainties and unknown load disturbance due to the estimation and compensation of perturbation terms. The combined observer can estimate the real rotor speed under speed varying and load changes and thus makes SSNAC achieve high performance robust speed drive without using speed sensors.

Optimization and H∞ Performance Analysis for Load Frequency Control of Power Systems With Time-Varying Delays

With the development and expansion of the power grid, the load frequency control (LFC) scheme receives sensor signals and outputs control signals through an open communication network with a mass of data and extensive information exchange, which may introduce constant, and time-varying delays. This paper considers the optimization andH∞performance problem for LFC of power systems with time-varying delays. Some improved criteria for guaranteeing the stability andH∞performance of the closed-loop system with unknown external load disturbances via the Lyapunov stability theory application. An unique delay-dependent proportional-integral (PI) controller and an optimized PI controller are designed for a specifiedH∞performance index and set, respectively. The criteria proposed in this paper are based on linear matrix inequalities (LMIs), which can be easily solved by the MATLAB LMI-Toolbox. Finally, in case studies, the effectiveness of our method is demonstrated.

Discrete-time command filtered adaptive fuzzy fault-tolerant control for induction motors with unknown load disturbances

In this paper, a command filtered fault-tolerant control (CFFTC) approach is investigated for induction motors (IMs) discrete-time system in the presence of actuator faults and unknown load disturbances. Firstly, the IMs system discrete-time model is obtained by Euler method. Then, the fuzzy logic systems (FLSs) is utilized to compensate for unknown actuator faults. Besides, introducing the error compensation mechanism into discrete-time systems via command filters, “complexity of computation” and noncausal problem can be conquered, and the filtering error is avoided concurrently. Finally, simulation results demonstrate the validity of the presented fault-tolerant method for IMs system.

Neuroadaptive observer-based discrete-time command filtered fault-tolerant control for induction motors with load disturbances

In this paper, a neuroadaptive observer-based discrete-time command filtered fault-tolerant control method is proposed for induction motors (IMs) with possible actuator faults and load disturbances. Firstly, the problem of “complexity of computation” and noncausal problem result from the traditional backstepping method are solved using the command filtered technique. Secondly, fault-tolerant control considering possible actuator faults is realized by adaptive neural control. In addition, a neuroadaptive observer is utilized to estimate the rotor position, angular velocity, and settle unknown load disturbances of IMs. The results of simulation demonstrate that the new design scheme can get rid of the effect of actuator faults and guarantee satisfactory position tracking performance.

Finite Time Fractional-order Adaptive Backstepping Fault Tolerant Control of Robotic Manipulator

In this paper, fractional calculus theory is employed to inspect a finite time fault tolerant controller for robotic manipulators in the presence of uncertainties, unknown external load disturbances, and actuator faults, using fractional-order adaptive backstepping approach in order to achieve, fast response and high-precision tracking performance. Knowing the advantages of adaptive controllers an adaptive form of the above controller is then established to deal with the overall uncertainties in the system. The most important property of the proposed controller is that we do not need to have knowledge about the actuator fault, external disturbances and system uncertainties exist in system. In this study two important achievements are made. The first one is that the finite time convergence of closed-loop system is ensured irrespective of initial states values. The second one is that the effects of the actuator faults and other uncertainties are attenuated by the suggested controller. The performance of the suggested controller is then tested for a PUMA560 robot in which the first three joints are used. The simulation results validate the usefulness of the suggested finite-time fractional-order adaptive backstepping fault-tolerant (FOAB-FTC) controller in terms of accuracy of tracking, and convergent speed.

Prescribed Performance Adaptive Backstepping Control for Winding Segmented Permanent Magnet Linear Synchronous Motor

In this paper, a prescribed performance adaptive backstepping control (PPABC) strategy is proposed to control the speed of a winding segmented permanent magnet linear synchronous motor (WS-PMLSM) with variable parameters and an unknown load disturbance. Firstly, a mathematical model of WS-PMLSM is provided. Then, the prescribed performance technique is introduced in the adaptive backstepping control to improve the transient performance and ensures the tracking error converges within a predetermined range. In addition, a constrained command filter is introduced to address the problem of differential expansion which exists in the traditional backstepping method, and a filter compensation signal is designed against the filter error. Moreover, the adaptive law is designed based on Lyapunov stability theory to estimate the uncertainties caused by parameter changes and load disturbances. The stability of the proposed control strategy is given and the simulation of the control system is carried out under the proposed PPABC in contrast with another backstepping control and traditional PI control. Finally, the experiment is conducted to further show the effectiveness of the proposed controller.

Runge-Kutta Model Predictive Speed Control for Permanent Magnet Synchronous Motors

Permanent magnet synchronous motors (PMSMs) have commonly been used in a wide spectrum ranging from industry to home appliances because of their advantages over their conventional counterparts. However, PMSMs are multiple-input multiple-output (MIMO) systems with nonlinear dynamics, which makes their control relatively difficult. In this study, a novel model predictive control mechanism, which is referred to as the Runge-Kutta model predictive control (RKMPC), has been applied for speed control of a commercial permanent magnet synchronous motor. Furthermore, the RKMPC method has been utilized for the adaptation of the speed of the motor under load variations via RKMPC-based online parameter estimation. The superiority of RKMPC is that it can take the constraints on the inputs and outputs of the system into consideration, thereby handling the speed and current control in a single loop. It has been shown in the study that the RKMPC mechanism can also estimate the load changes and unknown load disturbances to eliminate their undesired effects for a desirable control accuracy. The performance of the employed mechanism has been tested on a 0.4 kW PMSM motor experimentally for different conditions and compared to the conventional Proportional Integral (PI) method. The tests have shown the efficiency of RKMPC for PMSMs.

Effective Position Control for a Three-Phase Motor

This document presents an efficient proportional derivative (PD) position controller for three-phase motor drives. The regulator has been designed in frequency domain, employing the direct–quadrature (d–q) synchronous rotating reference frame and the indirect vector control. The presented position regulator is easy to tune and incorporates a feed forward (FF) term to compensate effectively the effect of the load disturbance. This position controller has been validated experimentally by using two industrial three-phase motors: an induction motor (IM) of 7.5 kW and a permanent magnet synchronous motor (PMSM) of 3.83 kW. The inner proportional integral (PI) current loops of both machines have also been designed in the frequency domain. Each machine has connected in its shaft an incremental encoder of 4096 pulses per revolution, to measure the position. Several simulations and experimental tests have been carried out with both motors, in favorable conditions and also with various types of adversities (parametric uncertainties, unknown load disturbance and measurement noise in the position and current loops), getting very good results and suggesting that this controller could be used in the research area and also in the industry.

Distributed Frequency Control With Operational Constraints, Part I: Per-Node Power Balance

This paper addresses the distributed optimal frequency control of multi-area power system with operational constraints, including the regulation capacity of individual control area and the power limits on tie-lines. Both generators and controllable loads are utilized to recover nominal frequencies while minimizing regulation cost. We study two control modes:the per-node balance mode and the network balance mode. In Part I of the paper, we only consider the per-node balance case, where we derive a completely decentralized strategy without the need for communication between control areas. It can adapt to unknown load disturbance. The tie-line powers are restored after load disturbance, while the regulation capacity constraints are satisfied both at equilibrium and during transient. We show that the closed-loop systems with the proposed control strategies carry out primal-dual updates for solving the associated centralized frequency optimization problems. We further prove the closed-loop systems are asymptotically stable and converge to the unique optimal solution of the centralized frequency optimization problems and their duals. Finally, we present simulation results to demonstrate the effectiveness of our design. In Part II of the paper, we address the network power balance case, where transmission congestions are managed continuously.

Survey on Passivity Based Control of Induction Machine

AbstractInduction machines (IM) constitute a theoretically interesting and practically important class of nonlinear systems. They are frequently used as wind generators for their power/cost ratio. They are described by a fifth‐order nonlinear differential equation with two inputs and only three state variables available for measurement. The control task is further complicated by the fact that IM are subject to unknown (load) disturbances and the parameters can be of great uncertainty. One is then faced with the challenging problem of controlling a highly nonlinear system, with unknown time‐varying parameters, where the regulated output, besides being unmeasurable, is perturbed by an unknown additive signal. Passivity‐based control (PBC) is a well‐established structure‐preserving design methodology which has shown to be very powerful to design robust controllers for physical systems described by Euler‐Lagrange equations of motion. PBCs provide a natural procedure to "shape" the potential energy yielding controllers with a clear physical interpretation in terms of interconnection of the system with its environment and are robust vis á vis to unmodeled dissipative effects. One recent approach of PBC is the Interconnection and Damping Assignment Passivity‐Based Control (IDA‐PBC) which is a very useful technique to control nonlinear systems assigning a desired (Port‐Controlled Hamiltonian) structure to the closed‐loop. The aim of this paper is to give a survey on different PBC of IM. The originality of this work is that the author proves that the well known field oriented control of IM is a particular case of the IDA‐PBC with disturbance.

Antiwindup Control of an Electrohydraulic System With Load Disturbance and Modeling Uncertainty

In this study, a linear antiwindup controller of an electrohydraulic system (EHS) is proposed to drive the joint motion of a two-degree-of-freedom robotic arm. Since the unknown external load disturbance is caused by the driven force/torque of the robotic arm and some hydraulic parametric uncertainties existing in an EHS model, perhaps the control saturation emerges in the controller, which will degrade the dynamic performance and the stable margin of the EHS. Thus, a model recovery antiwindup compensator embedded in an unconstrained controller is designed to suppress the control saturation of a servo valve. The antiwindup effectiveness of the proposed controller has been demonstrated by a comparative experiment study with both linear and nonlinear controllers, which indicates the proposed controller can achieve better dynamic performance under largely unknown load disturbance and model uncertainty.

Sliding Mode Observer-Based Current Sensor Fault Reconstruction and Unknown Load Disturbance Estimation for PMSM Driven System

This paper proposes a new scheme of reconstructing current sensor faults and estimating unknown load disturbance for a permanent magnet synchronous motor (PMSM)-driven system. First, the original PMSM system is transformed into two subsystems; the first subsystem has unknown system load disturbances, which are unrelated to sensor faults, and the second subsystem has sensor faults, but is free from unknown load disturbances. Introducing a new state variable, the augmented subsystem that has sensor faults can be transformed into having actuator faults. Second, two sliding mode observers (SMOs) are designed: the unknown load disturbance is estimated by the first SMO in the subsystem, which has unknown load disturbance, and the sensor faults can be reconstructed using the second SMO in the augmented subsystem, which has sensor faults. The gains of the proposed SMOs and their stability analysis are developed via the solution of linear matrix inequality (LMI). Finally, the effectiveness of the proposed scheme was verified by simulations and experiments. The results demonstrate that the proposed scheme can reconstruct current sensor faults and estimate unknown load disturbance for the PMSM-driven system.

Saturated Adaptive Control of an Electrohydraulic Actuator with Parametric Uncertainty and Load Disturbance

In this paper, a saturated adaptive control of an electrohydraulic actuator is proposed to drive the joint motion of a two-degree-of-freedom robotic arm. Due to the largely unknown load disturbance from the driven force/torque of the robotic arm and the existing control saturation of a servo valve, a Nussbaum function is designed to compromise between the antiwindup control effect and the dynamic response performance of an electrohydraulic system. Then, an adaptive parametric estimation law is designed to estimate the hydraulic parametric uncertainties. The effectiveness of the proposed controller has been demonstrated by comparative experimental study, which indicates that this controller can quickly recover the unsaturated dynamics with satisfactory tracking accuracy under largely unknown load disturbance and parametric uncertainty.

Online Algebraic Identification Approach of Continuous Linear Time Delay Systems

AbstractIn this paper, we propose an online algebraic method to identify linear continuous time delay process from step response, in presence of unknown initial state and constant load disturbance. The identification mechanism is split into two sequential steps. The time delay and dynamic of the plant is estimated firstly through a spectral formulation. In the next stage, the transient regime is deduced from a linear regression. To improve the robustness of the proposed method, a local convolution by sigmoid function is proposed. Simulation results are provided, at last, to show the effectiveness of our conceived approach.

Optimal Shape Control of Piezoelectric Intelligent Structure Based on Genetic Algorithm

Shape variation induced by mismachining tolerance, humidity and temperature of the working environment, material wear and aging, and unknown external load disturbances have a relatively large influence on the dynamic shape of a mechanical structure. When integrating piezoelectric elements into the main mechanical structure, active control of the structural shape is realized by utilizing the inverse piezoelectric effect. This paper presents a mathematical model regarding piezoelectric intelligent structure shape control. We also applied a genetic algorithm, and given a piezoelectric intelligent cantilever plate with both ends affected by a certain load, optimal shape control results of piezoelectric materials were analyzed from different perspectives (precision reference or cost reference). The mathematical model and results indicate that, by optimizing a certain number of piezoelectric actuators, high-precision active shape control can be realized.