This paper proposes a dual-loop discrete-time adaptive control (DDAC) method for three-phase PWM rectifiers, which considers inductance-parameter-mismatched and DC load disturbances. A discrete-time model of the three-phase PWM rectifier is establish...
Discrete-time architectures offer a distinct advantage over their continuous counterparts, as they can be seamlessly implemented on embedded hardware without the necessity for discretization processes. Yet, because of the difficulty of ensuring Lyapu...
In this paper, a practical discrete-time control method with adaptive image feature prediction for the image-based visual servoing (IBVS) scheme is presented. In the discrete-time IBVS inner-loop/outer-loop control architecture, the time delay caused...
This paper addresses the challenges of achieving robust coordination in discrete-time multi-robot systems subject to uncertainties and Byzantine attacks affecting both actuator and sensor channels. Such adversarial disruptions degrade system performa...
This study contrives a discrete-time adaptive decentralized control algorithm with input quantization for interconnected multi-machine power systems with SVC. First, a dynamic surface scheme is applied to the excitation controller design, in which fi...
This paper introduces an innovative adaptive control approach utilizing a nonlinear filter for a specific subset of nonlinear discrete-time systems, considering the presence of both input and output noise. The system can be transformed into a nonline...
This study focuses on the full-form model-free adaptive controller (FFMFAC) for SISO discrete-time nonlinear systems, and proposes enhanced FFMFAC. The proposed technique design incorporates long short-term memory neural networks (LSTMs) and fuzzy ne...
This paper presents the design and industrial implementation of an adaptive discrete control system for a rotary dryer operating in potash fertilizer production. The drying process is characterized by high inertia, multivariable interactions, transpo...
Robotic systems equipped with a task-multiplexer unit are considered as a class of unknown non-linear discrete-time systems, where the input is a command voltage of the driver unit and the output is the feedback signal obtained by the multiplexer uni...
As technology evolves, more complex non-affine systems are created. These complex systems are hard to model, whereas most controllers require information on systems to be designed. This information is hard to obtain for systems with varying control d...
This paper is concerned with the adaptive event-triggered finite-time pinning synchronization control problem for T-S fuzzy discrete complex networks (TSFDCNs) with time-varying delays. In order to accurately describe discrete dynamical behaviors, we...
Adaptive mixing control (AMC) is a recently developed control scheme for uncertain plants, where the control action coming from a bank of precomputed controller is mixed based on the parameter estimates generated by an on-line parameter estimator. Ev...
This study proposes a Disturbance-improved Model-free Adaptive Prediction Control (DMFAPC) algorithm for a discrete-time nonlinear system with time delay and disturbance. The algorithm is shown to have good robustness. On the one hand, the Smith pred...
This paper concerns an improved model-free adaptive fractional-order control with a high-order pseudo-partial derivative for uncertain discrete-time nonlinear systems. Firstly, a new equivalent model is obtained by employing the Grünwald–L...
This paper addresses a class of uncertain nonlinear systems with disturbances that are challenging to model by proposing a novel model-free adaptive sliding mode control (MFASMC) scheme based on a discrete-time extended state observer (DESO). Initial...
The control of nonlinear, open-loop unstable dynamics is a prevalent engineering challenge, often benchmarked through magnetic levitation (Maglev) systems. While continuous-time adaptive neural networks are commonly used to reject disturbances, their...
The distributed leader-follower control of multi-agent systems is discussed. Each agent is expressed in a discrete-time and non-linear dynamic model with an unknown parameter and can be affected by its neighbors’ history information. For each a...
This paper extends one of the nonswitching-type reaching laws for discrete-time sliding mode control. The control task under consideration is the regulation of the grid current of the grid-following power inverter. A mathematical model of a plant is...
This paper presents a self-tuning minimal-rule fuzzy logic controller for high-performance induction motor drives operating under field-oriented control. Unlike conventional full-rule fuzzy controllers and reduced-rule designs with fixed post-design...
Model-free adaptive control (MFAC) can carry out various tasks using only I/O data, providing advantages such as lower operational costs, higher scalability and easier implementation. However, the robustness of MFAC remains an open problem. In this p...
This paper is concerned with the problem of a full formal dynamic linearized model-free adaptive control scheme based on pattern class variable (P-FFDL-MFAC) for a class of unknown non-affine nonlinear discrete-time systems. The concept of pattern cl...
Sliding mode control (SMC) is widely recognized for its robustness against modeling uncertainties and external disturbances. However, asymmetric actuator dynamics, excessive switching activity, and the absence of active cooling challenge its applicat...
This paper presents a fuzzy-based adaptive admittance control (FAAC) framework for position-controlled robots in uncertain contact environments. The proposed FAAC regulates admittance parameters using three fuzzy adaptation maps rather than directly...
Data technology advances have increased in recent years, especially for robotic systems, in order to apply data-driven modelling and control computations by only considering the input and output signals’ relationship. For a data-driven modellin...
This paper investigates the output feedback (OPFB) tracking control problem for discrete-time linear (DTL) systems with unknown dynamics. To solve this problem, we use an augmented system approach, which first transforms the tracking control problem...
Real-time hybrid simulation (RTHS) evaluates the dynamic performance of a structure by physically testing the selected components while modeling the remaining structure numerically, making it efficient in both cost and testing space requirements. In...
In feedback control of mechatronic systems, sensor signals are usually noisy and uncertain because of measurement errors and environmental disturbances. Such uncertainty and noise of feedback signals may cause instability of the controlled systems. T...
As operational scenarios become more complex and task demands intensify, the requirements for the intelligence and automation of manipulators in industry are increasing. This work investigates the challenge of posture tracking control for hydraulic f...
Model-free adaptive control (MFAC) builds a virtual equivalent dynamic linearized model by using a dynamic linearization technique. The virtual equivalent dynamic linearized model contains some time-varying parameters, time-varying parameters usually...
Discrete-time chaotic systems exhibit nonlinear and unpredictable dynamic behavior, making them very difficult to classify. They have dynamic properties such as the stability of equilibrium points, symmetric behaviors, and a transition to chaos. This...
This paper proposes a frequency-adaptive current control design for a grid-connected inverter with an inductive–capacitive–inductive (LCL) filter to overcome the issues relating to both the harmonic distortion and frequency variation in t...
This article proposes an adaptive flight framework that integrates a discrete-time incremental nonlinear dynamic inversion controller and a neural network (NN)-based observer for maneuvering flight. The framework is built on the feedback-inversion sc...
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...
Controllers designed on the basis of an approximate discrete time model can fail when they are applied to the real processes. This is a problem of interest in adaptive symmetry control system theory. In this paper, we introduce the certain polynomial...
The integration of communication channels with the feedback loop in a networked control system (NCS) is attractive for many applications. A major challenge in the NCS is to reduce transmissions over the network between the sensors, the controller, an...
With the increasing integration of renewable energy sources (RESs) into power systems, batteries are playing a critical role in ensuring grid reliability and flexibility. Among them, vanadium redox flow batteries (VRFBs) have emerged as a promising s...
This paper presents a novel optimal control-based beamforming framework for phased antenna arrays, targeting advanced wireless communication and radar applications, including 5G systems. Unlike conventional beamforming techniques, such as Fourier-bas...
This work introduces a unified Artificial Intelligence-based framework for the optimal tuning of gains in a neural discrete-time sliding mode controller (SMC) applied to a two-degree-of-freedom robotic manipulator. The novelty lies in combining surro...
The idea of active noise control is an attenuation of unwanted noise with an additionally generated acoustic wave using the phenomenon of interference. Its technical realization employs advanced control algorithms. Active noise control is an area of...
High-performance operation of permanent magnet synchronous motors (PMSMs) strongly depends on the reliable availability of rotor position and speed information. Although this information is commonly obtained using physical position sensors, such sens...
In this paper, we consider an iterative learning control problem for a class of unknown discrete-time nonlinear systems with iteration-varying initial error, iteration-varying system parameters, iteration-varying external disturbance, iteration-varyi...
The optimal tracking problem is addressed in the robotics literature by using a variety of robust and adaptive control approaches. However, these schemes are associated with implementation limitations such as applicability in uncertain dynamical envi...
This paper proposes an optimal tracking control scheme through adaptive dynamic programming (ADP) for a class of partially unknown discrete-time (DT) nonlinear systems based on a radial basis function neural network (RBF-NN). In order to acquire the...
This article proposes a new fractional-order discrete-time chaotic system, without equilibria, included two quadratic nonlinearities terms. The dynamics of this system were experimentally investigated via bifurcation diagrams and largest Lyapunov exp...
Electric heating furnaces are widely used in industrial production and scientific research, where the quality of temperature control directly affects product performance and operational safety. However, precise control remains challenging due to the...
In the literature on sensorless control of induction motors, many algorithms have been presented for rotor flux and speed estimation. However, all these algorithms have been developed in the continuous–time domain. The digital realization of th...
The dynamics of power converters are highly influenced by uncertainties, nonlinearities, and external disturbances. Thus, high-performance, extremely resilient, and robust control strategies are necessary for their control. For the robust operation o...
This study proposes a microservices-based software architecture for implementing digital twins (DT) in real-time industrial process control. Unlike monolithic approaches, the proposed architecture decouples acquisition, modeling, prediction, and actu...
Flexible-joint robots (FJRs) offer safety and energy efficiency in collaborative tasks, yet achieving high-precision tracking remains challenging under strict state and safety constraints due to elastic coupling, model mismatch, and external disturba...
The problem of controlling a spreading process in a two-layer multiplex networks in such a way that the extinction state becomes a global attractor is addressed. The problem is formulated in terms of a Markov-chain based susceptible-infected-suscepti...
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