This paper addresses the issue of polynomial iterative learning tracking control (Poly-ILC) for continuous-time linear systems (LTI) operating repetitively. It explores the design of an iterative learning control law by examining the stability along...
In this paper, we introduce Green Iterative Learning Control (Green ILC), an innovative hybrid control method that addresses the critical need for energy-efficient control in dynamic, repetitive-task environments. By integrating the iterative refinem...
Plastic injection molding is a widely used manufacturing process for producing plastic components. However, achieving optimal process stability and part quality remains a persistent challenge due to limited real-time feedback during production. The m...
Iterative learning control (ILC) requires that the operating conditions of the controlled system must remain unchanged in the repetitive learning process. If the parameters of system change, the former control experience of ILC would not be effective...
Wind disturbances and noise severely affect Unmanned Aerial Vehicles (UAV) when monitoring and finding faults in overhead power lines. Accordingly, we propose repetitive learning as a new solution for the problem. In particular, the performance of It...
This study aims to orchestrate a less restrictive learning controller by using the iteration-varying function, the so-called iterative learning controller (ILC), to synchronize two nonlinear systems with free time delay and couple free. The mathemati...
Pneumatic actuators demonstrate various nonlinear and uncertain behavior, and as a result, precise control of such actuators with model-based control schemes is challenging. The Iterative Learning Control (ILC) algorithm is a model-free control metho...
This paper presents a second order P-type iterative learning control (ILC) scheme with initial state learning for a class of fractional order linear distributed parameter systems. First, by analyzing the control and learning processes, a discrete sys...
In order to solve the problem that the parameters of traditional proportional–integral (PI) control are not easy to adjust, an iterative learning control (ILC) technique for a DC/DC power converter is proposed in this paper. Firstly, we have develope...
Aiming to reduce motor speed estimation and torque vibration present in the permanent magnet synchronous motors (PMSMs) of rim-driven thrusters (RDTs), a position-sensorless control algorithm using an adaptive second-order sliding mode observer (SMO)...
Iterative learning based digital peak current mode control (PCMC) is proposed in this paper. The proposed control method provides excellent current reference tracking against variations in input voltage, load, and circuit parameters. Compared to othe...
This paper develops an adaptive model predictive control (AMPC) scheme for uncertain nonaffine nonlinear systems by integrating deep Koopman operator theory into a fully data-driven modeling framework. Complex nonlinear systems typically feature prom...
Designing an optimal iterative learning control is a huge challenge for linear and nonlinear dynamic systems. For such complex systems, standard Norm optimal iterative learning control (NOILC) is an important consideration. This paper presents a nove...
This paper proposes a novel control approach for a robot gripper in which the impedance control, fuzzy logic control, and iterative learning control are combined in the same control schema. The impedance control is used to keep the gripping force at...
This paper proposes a simple tracking and synchronization control of a dual-drive system using inversion-based iterative learning control (IILC), which reformulates the model at each iteration based on input/output data. By the power of the IILC, thi...
Iterative learning contouring control (ILCC) improves contouring accuracy in multi-axis motion systems via the equivalent contour error formulation. However, its convergence strongly depends on the learning gain. Large gains may induce overly aggress...
This article addresses trajectory tracking between two non-identical systems with chaotic properties. To study trajectory tracking, we used the Rossler chaotic and resistive-capacitive-inductance shunted Josephson junction (RCLs-JJ) model in a simila...
This paper proposes Social-only Particle Swarm Optimization-based Iterative Learning Control (SO-PSO-ILC) to address the limitations of conventional Iterative Learning Control (ILC) in model dependency and manual parameter tuning. The proposed method...
Quantization errors and packet dropouts in noisy communication channels degrade the convergence performance of repetitive-motion plants under iterative learning control (ILC). Different from existing works focusing on the redesign of ILC schemes, thi...
The integration of renewable energy sources (RESs) into power systems, particularly in microgrids, is becoming a prominent trend aimed at reducing dependence on traditional energy sources. Replacing conventional synchronous generators with grid-conne...
This paper presents a vibration control method for the vibration suppression of a robotic arm. To understand the causes of the vibration in the six-axis manipulator and then eliminate the vibration through an effective control method, the vibration c...
In this paper, the formation tracking problem for heterogeneous multi-agent systems with loss of multiple communication packets is considered using the iterative learning control (ILC) method. A dropout compensation ILC method is presented to constru...
At present, the cogging torque of permanent magnet synchronous motors (PMSM) seriously limits the Los pointing accuracy of aviation photoelectric stabilization platforms based on PMSM, which also restricts the requirements of ultra-long-distance and...
Due to the under-actuated and strong coupling characteristics of quadrotor aircraft, traditional trajectory tracking methods have low control precision, and poor anti-interference ability. A novel fuzzy proportional-interactive-derivative (PID)-type...
The coordination of switched fractional-order nonlinear heterogeneous multi-agent systems (FONHMASs) with cooperative and antagonistic interactions presents significant challenges due to the complex coupling of switched fractional-order dynamics. Cru...
Iterative learning control (ILC) typically requires strict repeatability in initial states, trajectory length, external disturbances, and system dynamics. However, these assumptions are often difficult to fully satisfy in practical applications. Whil...
During periodic scanning, friction-dominated disturbances near motion reversals cause velocity fluctuations in an inertially stabilized platform (ISP). This paper proposes a disturbance rejection control method based on an iterative-learning-embedded...
To realize the high-performance load torque tracking of an electric dynamic load simulator system with random measurement noises and strong position disturbances, a PD-type iterative learning control (ILC) algorithm with adaptive learning gains is pr...
An adaptive fuzzy iterative learning control (ILC) algorithm is designed for the iterative variable reference trajectory problem of nonlinear discrete-time systems with input saturations and unknown control directions. Firstly, an adaptive fuzzy iter...
In this study, vibration control, a behavior which subordinates to stall-induced nonlinear vibration and amplitude control of a wind turbine’s blade section, based on unified pitch motion driven by slider-linkage mechanism, is investigated by u...
This paper presents an application of Iterative Learning Control (ILC) theory to secure communication system design by using chaotic signals, where the logistic-map is employed as a source of chaos. Meanwhile, the ILC scheme is employed as a tool to...
Renewable energy generation is increasingly important due to serious energy issues. A Doubly Salient Permanent Magnet Generator (DSPMG) can be an interesting candidate for tidal stream renewable energy systems. However, the special structure makes th...
Bowden-cable-actuated soft exoskeleton robots are known for their light weight and flexibility of power transmission during rehabilitation training or movement assistance for humans. However, friction-induced nonlinearity of the Bowden transmission c...
Intelligent robotics has drawn a great deal of attention due to its high precision, stability, and reliability, which are the basic key factors for industrial automation. This paper proposes an iterative learning control (ILC) technique with predefin...
This study deals with P-type iterative learning control (ILC) techniques for switched impulsive systems governed by composite fractional derivatives. The systems considered incorporate non-instantaneous impulses and an initial state offset, with the...
Background: Pneumatic muscle actuator (PMA) actuated multisection continuum arms are widely applied in various fields with high flexibility and bionic properties. Nonetheless, their kinematic modeling and control strategy proves to be extremely chall...
Random delays in the communication links affect the precise tracking of the expected trajectory by a plant controlled by the iterative learning control (ILC) strategy. To tackle the link impact, this paper proposes a state estimator to derive accurat...
In order to solve the problems of repetitive and non-repetitive interference in the workflow of Automated Guided Vehicle (AGV), Iterative Learning Control (ILC) combined with linear extended state observer (LESO) is utilized to improve the control ac...
(1) Background: An iterative learning control (ILC) strategy was developed for a “Muscle First” Motor-Assisted Hybrid Neuroprosthesis (MAHNP). The MAHNP combines a backdrivable exoskeletal brace with neural stimulation technology to enabl...
An iterative learning fault-tolerant control method is designed for an actuator fault intermittent process with simultaneous uncertainties for the system parameters. First, an intermittent fault tolerance controller is designed using 2D system theory...
Electrical machines generate unwanted flux and current harmonics. Harmonics can be suppressed using various methods. In this paper, the harmonics are significantly reduced using Iterative Learning Control (ILC) and Neural Networks (NNs). The ILC can...
This paper presents an adaptive Kalman filter (AKF)-enhanced iterative learning control (ILC) scheme to improve trajectory tracking in non-repetitive time-varying systems (NTVSs), particularly in industrial applications. Unlike traditional ILC method...
In this paper, a current-error-based iterative learning controller (ILC) with a nonlinear controller is proposed to improve the position-tracking performance in permanent-magnet (PM) stepper motors. Our proposed method comprises a current-error-based...
Periodic torque ripple often occurs in permanent magnet synchronous motors due to cogging torque and flux harmonic distortion, leading to motor speed fluctuations and further causing mechanical vibration and noise, which seriously affects the perform...
This study developed a frequency-domain fault-tolerant iterative learning control (ILC) strategy for spatially interconnected systems subject to external disturbances and actuator faults. An equivalent one-dimensional system model was established by...
This paper deals with the consensus tracking problem of heterogeneous linear multiagent systems under the repeatable operation environment, and adopts a proportional differential (PD)-type iterative learning control (ILC) algorithm based on the fract...
To mitigate low-speed speed oscillations in permanent magnet synchronous motors (PMSMs) arising from the combined effects of rotor-position-related periodic disturbances and external perturbations, this paper develops a composite robust speed regulat...
A novel Set Point Weighting Iterative Learning Controller (SPW-ILC) has been proposed for voltage stabilization at AC/DC bus, coordinated control among the distributed sources in the modeled hybrid microgrid (HMG) and synchronization of HMG with util...
As the demand for high-speed elevators grows, the requirements of elevator performance have also developed. The high speed will produce strong airflow disturbances and drastic pressure changes, which is prone to cause passenger discomfort. In this pa...
In this paper, we develop a hybrid iterative learning controller (HILC) for a non-holonomic wheeled mobile platform to achieve trajectory tracking with actual complex constraints, such as physical constraints, uncertain parameters, and initial errors...
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