Predictive control offers many advantages such as simple design and a systematic way to handle constraints. Model predictive control (MPC) belongs to predictive control, which uses a model of the system for predictions used in predictive control. A m...
An accurate definition of a system model significantly affects the performance of model-based control strategies, for example, model predictive control (MPC). In this paper, a model-free predictive control strategy is presented to mitigate all ramifi...
In this paper, an improved model-free adaptive predictive control method is presented for unknown nonlinear systems with quantization to handle the limited network transmission capacity and denial of service (DoS) attacks. Firstly, to reduce the impa...
Classical model-free predictive current control (MFPCC) is a robust control technique for a two-level inverter-fed induction-motor drive, with advantages that consist of a simple concept, rapid response, simple implementation, and excellent performan...
pH neutralization reaction process plays a crucial role in Waste Water Treatment Process (WWTP). Traditional PID Proportion Integral Differential, (or even advanced PID control) algorithms have poor performance on WWTP due to the strong non-linearity...
Model predictive control is highly dependent on accurate models and the parameters of electric motor drives. Multiphase permanent magnet synchronous motors (PMSMs) contain nonlinear parameters and mutual cross-coupling dynamics, resulting in challeng...
Currently, a two-level voltage source inverter (2L-VSI) is regarded as the cornerstone of modern industrial applications. However, the control of VSIs is a challenging task due to their nonlinear and time-varying nature. This paper proposes employing...
A model-free adaptive predictive control algorithm based on an improved extended state observer (IESO) is proposed to solve the problem that the primary permanent magnet linear motor is susceptible to time-varying parameters and unknown disturbances....
Model predictive control (MPC) is significantly affected by parameter mismatch in inverter applications, whereas model-free predictive control (MFPC) avoids parameter dependence through the ultra-local model (ULM). However, the traditional MFPC based...
The trajectory-tracking capability of autonomous mining trucks is critical for accomplishing transportation tasks efficiently. However, due to the diverse road surfaces and rugged terrains in open-pit mines, the existing vehicle dynamics models strug...
To address the issues of excessive current ripple and poor dynamic response in conventional angle position control (APC) for high-speed switched reluctance generator (SRG), this paper proposes an online parameter identification-based model-free predi...
In this paper, the problem of model-free adaptive predictive control (MFAPC) under denial-of-service attacks and quantization effects for high-speed trains with unknown models is investigated. Since the system model of the high-speed train is unknown...
Vector control of an induction machine (IM) is typically performed by using cascade control structures with conventional linear proportional–integral (PI) controllers, the inner loop being designed for current control and the outer loop for rot...
The model-free predictive control (MFPC) scheme is an effective scheme to enhance the parameter robustness of model predictive control. However, the MFPC scheme can be affected by the current gradient updating frequency. This paper proposes an improv...
One of the significant features of the transverse flux linear motors (TFLMs) is the relatively higher thrust density, since the main flux loop of TFLM is located on a perpendicular plane to the motion direction. As one type of reluctance TFLM, the tr...
This paper proposes a data-driven model-free robust predictive control strategy for parallel three-level NPC inverters based on finite control set model predictive control (FCS-MPC), focusing on the zero-sequence circulating current (ZSCC) problem un...
Traditional model predictive current control (MPCC) is heavily dependent on the accuracy of motor parameters and incurs high computational costs. To address these challenges, this paper proposes an enhanced model-free predictive current control (MFPC...
Utility grid-tied photovoltaic (PV) installations are becoming a typical component of the current electrical energy grid. The adoption of transformerless inverters has recently changed the topology of these systems. Despite being small, inexpensive,...
This paper investigates the problem of ensuring the stable operation of multiple high-speed train systems under the threat of False Data Injection (FDI) attacks. Due to the wireless communication characteristics of railway networks, high-speed train...
A Model-based predictive current control (MBPCC) has recently become a powerful advanced control technology in industrial drives. However, MBPCC relies on the knowledge of the system model and parameters, being, therefore, very sensitive to parameter...
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 study presents a general framework for the control of unknown dynamic systems with unknown input delay. A concise output feedback control system is structured with tuning stabilization/dynamic response by an output feedback low gain, removing st...
Climate changes and the lack of running water across vast territories require the massive use of pumping systems, often powered by solar energy sources. In this context, simple drives with high-efficiency motors can be expected to take hold. It is im...
This work addresses the model predictive control (MPC) of the offset-free tracking problem in the dynamic partial least square (DyPLS) framework. Firstly, state space MPC based on the DyPLS is proposed. Then, two methods are proposed to solve the off...
A nonlinear offset-free model predictive control based on a dynamic partial least square (PLS) framework is proposed in this paper. A multi-output multi-input system is projected into latent variable space by a PLS outer model. For each latent variab...
With the increasing demand for space missions, space robots have become the focus of research and attention. As a typical representative, the free-floating dual-arm space robot has the characteristics of multiple degrees of freedom, a floating base,...
This article proposes an improved model-free deadbeat predictive current control (MFCC) method for permanent magnet synchronous motors (PMSMs) based on the ultralocal model and H∞ norm. Firstly, the traditional deadbeat predictive current contr...
In this paper, a finite control set model-free predictive current control (FCS-MFPCC) of a permanent magnet synchronous motor is presented. The control scheme addresses the problems of large current fluctuation and decline of the motor system perform...
Conventional model predictive power control (MPPC) features a simple concept and quick dynamic response. However, it relies heavily on the system model and its parameter accuracy. Furthermore, the steady ripples are still high due to the use of one v...
The development of intelligent transportation technology has provided a significant impetus for autonomous driving technology. Currently, autonomous vehicles based on Model Predictive Control (MPC) employ motion control strategies based on sampling t...
Model predictive control (MPC) performance depends on the accuracy of the system model. Moreover, the optimization algorithm of MPC requires numerous online computations. These inherent limitations of MPC hinder its application in power electronics s...
To remove parameter dependence in existing sensorless control strategies, a parameter-free model predictive current control is proposed for permanent magnet synchronous motor without any position sensor. First, the current variation during one sampli...
The distributed model predictive control (DMPC) strategy with particle swarm optimization (PSO) is applied to solve the collision-free trajectory tracking problem for the mecanum-wheeled mobile robot (MWMR) formation. Under the leader–follower...
Predictive current control (PCC) is an advanced control strategy for permanent magnet synchronous motors (PMSM). When the motor drive system is undisturbed, predictive current control exhibits a good dynamic response speed and steady−state perf...
The finite control set model predictive torque control (FCS-MPTC) selects the optimal voltage vector (VV) by the composite cost function composed of torque and flux error, which makes it have a faster dynamic response than conventional control method...
Voltage source converter-based–high voltage direct current (VSC-HVDC) systems exhibit strong nonlinear characteristics that dominate their dynamic behavior under large disturbances, making large-signal stability assessment essential for secure...
Grid-forming (GFM) converters play a vital role in future power systems due to their ability to independently establish voltage and frequency. However, their interaction with AC circuits may give rise to synchronous oscillations, which pose a threat...
This paper focuses on developing a data-driven trajectory tracking control approach for autonomous underwater vehicles (AUV) under uncertain external disturbance and time-delay. A novel model-free adaptive predictive control (MFAPC) approach based on...
This paper presents a non-linear model predictive control approach for offset-free tracking and the rejection of piece-wise constant disturbances. The approach involves augmenting the system’s state vector with the integral of the tracking erro...
In this paper, the performance of three model-free control approaches on a multi-input, multi-output (MIMO) nonlinear system with constant and time-varying references is compared. The first control algorithm is model-free adaptive control (MFAC). The...
This paper presents the study of linear Offset-Free Model Predictive Control (OF-MPC) for an Active Magnetic Bearing (AMB) application. The method exploits the advantages of classical MPC in terms of stability and control performance and, at the same...
For current control in power conversion and motor drive systems, there exist three classic methods in the literature and they are the hysteresis current control (HCC), the sine pulse-width modulation (SPWM), and the space vector pulse width modulatio...
The current paper presents a comprehensive review analysis of Multi-agent control methodologies for Integrated Building Energy Management Systems (IBEMSs), considering combinations of multi-diverse equipment such as Heating, Ventilation, and Air cond...
Model Predictive Control constitutes an important element of any modern control system. There is growing interest in this technology. More and more advanced predictive structures have been implemented. The first applications were in chemical engineer...
This paper proposes a double-layer model predictive control (MPC) algorithm for the integrated path planning and trajectory tracking of autonomous vehicles on roads. The upper module is responsible for generating collision-free lane trajectories, whi...
This paper develops an offset free tracking model predictive control based on a dynamic partial least square (PLS) framework. First, state space model is used as the inner model of PLS to describe the dynamic system, where subspace identification met...
This paper focuses on the collision-free formation tracking of autonomous underwater vehicles (AUVs) with compound disturbances in complex ocean environments. We propose a novel finite-time extended state observer (FTESO)-based distributed dual close...
In the conventional dual-loop vector control strategy of Voltage Source Converter-based High Voltage Direct Current (VSC-HVDC) systems employed in offshore wind farms, challenges such as complex PI parameter-tuning and slow response speed exist. Furt...
ANNs have become a cornerstone in efficiently managing building energy management systems (BEMSs) as they offer advanced capabilities for prediction, control, and optimization. This paper offers a detailed review of recent, significant research in th...
With the continuous expansion of data center scales worldwide, the problem of energy consumption has become increasingly prominent. To address the multi-parameter control challenge in environmental temperature regulation for large data center compute...
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