The large-scale integration of renewable energy sources introduces significant uncertainty into modern power systems, posing new challenges for reliable and economical operation. Effective scheduling therefore requires accurate monitoring of uncertai...
This paper introduces a novel output constraint satisfaction mechanism that can be used to supplement controllers employing a control law. This mechanism is dedicated to control systems of nonlinear processes, with this additional feature. It utilize...
One of the fastest growing and efficient methods for solving the unconstrained minimization problem is the conjugate gradient method (CG). Recently, considerable efforts have been made to extend the CG method for solving monotone nonlinear equations....
This paper proposes a parametric hierarchical model for functional data with an elliptical shape, using a Gaussian process prior to capturing the data dependencies that reflect systematic errors while modeling the underlying curved shape through a vo...
With the development of spaceborne processing technologies, the demand for on-board processing has risen sharply. Against this background, spaceborne Interferometric Synthetic Aperture Radar (InSAR) processing has become an important research area. I...
This study establishes a vertical–horizontal coupling vibration model of hot rolling mill rolls under multi-piecewise nonlinear constraints considering the piecewise nonlinear spring force and piecewise nonlinear friction force constraints of t...
In this paper, we consider the parameter identification problem of partial differential equations with constraints. A nonlinear multigrid method is introduced to the process of parameter inversion. By keeping the objective functions on coarse grids c...
The particle filter method is a basic tool for inference on nonlinear partially observed Markov process models. Recently, it has been applied to solve constrained nonlinear filtering problems. Incorporating constraints could improve the state estimat...
This research paper proposes a derivative-free method for solving systems of nonlinear equations with closed and convex constraints, where the functions under consideration are continuous and monotone. Given an initial iterate, the process first gene...
This paper proposes a safety-constrained interaction control scheme for robotic manipulators by integrating model predictive control (MPC) and active disturbance rejection control (ADRC). The proposed method is specifically designed for manipulators...
This paper presents the optimisation of the segregation distance between two electric cable bundles installed in an aircraft structure under electromagnetic compatibility constraints. We first describe the problem formulation where a probabilistic co...
In this article, an event-triggered adaptive fuzzy finite-time dynamic surface control (DSC) is presented for a class of strict-feedback nonlinear fractional-order systems (FOSs) with full-state constraints. The fuzzy logic systems (FLSs) are employe...
This paper is concerned with the adaptive neural network (NN) partial tracking control problem for a class of completely unknown multi-input multi-output (MIMO) singularly perturbed nonlinear systems possessing time-varying asymmetric state constrain...
For the bearing-only target motion analysis (TMA), the pseudolinear Kalman filter (PLKF) solves the complex nonlinear estimation of the motion model parameters but suffers serious bias problems. The pseudolinear Kalman filter under the minimum mean s...
A simple yet effective optimization technique is developed to solve nonlinear conjugate heat transfer. The proposed Nonlinear Optimization with Replacement Strategy (NORS) is a mutation of several existing optimization processes. With the improvement...
Many practical applications in applied sciences such as imaging, signal processing, and motion control can be reformulated into a system of nonlinear equations with or without constraints. In this paper, a new descent projection iterative algorithm f...
This study addresses the problem of optimal resource allocation in nonlinear multi-module dynamic systems arising in complex computational and techno-economic processes, where numerical stability and strict enforcement of structural constraints are c...
To achieve the efficient and precise control of autonomous underwater vehicles (AUVs) in dynamic ocean environments, this paper proposes an innovative Gaussian-Process-based Model Predictive Control (GP-MPC) method. This method combines the advantage...
The problem of optimal synthesis of a nonlinear system’s control law parameters of satellite attitude control under constraints is considered. The maximum stability degree of a system is considered as an optimality criterion. The reaction wheel...
This paper presents a class of proximal alternating direction multiplier methods for solving nonconvex, nonsmooth optimization problems with nonlinear coupled constraints. The key feature of the proposed algorithm is that we use a linearized proximal...
This study investigates a green multimodal routing problem with soft time window. The objective of routing is to minimize the total costs of accomplishing the multimodal transportation of a batch of goods. To improve the feasibility of optimization,...
We present a sensitivity-based predictor-corrector path-following algorithm for fast nonlinear model predictive control (NMPC) and demonstrate it on a large case study with an economic cost function. The path-following method is applied within the ad...
In this study, the voltage stability margin for direct current (DC) networks in the presence of constant power loads is analyzed using a proposed convex mathematical reformulation. This convex model is developed by employing a second-order cone progr...
Work-flow scheduling is for finding the allocation method to achieve optimal resource utilization. In the scheduling process, constraints, such as time, cost and quality, need to be considered. How to balance these parameters is a NP-hard problem, an...
Predictive controllers have been extensively studied and applied to electrical drives, mainly because they provide fast dynamic responses and are suitable for multi-variable control and non-linear systems. Many approaches perform the prediction and o...
The nonlinear optical response of common materials is limited by bandwidth and energy consumption, which impedes practical application in all-optical signal processing, light detection, harmonic generation, etc. Additionally, the nonlinear performanc...
Amidst growing uncertainty regarding global sustainable development goals and the increasing complexity of social systems, accurately characterizing long-term transition processes driven by the interactions of multiple agents and factors remains a cr...
Process operational safety plays an important role in designing control systems for chemical processes. Motivated by this, in this work, we develop a process Safeness Index-based economic model predictive control system for a broad class of stochasti...
In the transmission expansion planning (TEP) problem, it is challenging to consider a fault current level constraint due to the time-consuming update process of the bus impedance matrix, which is required to calculate the fault currents during the se...
In modern power-system load frequency control (LFC), proportional–integral–derivative (PID) controllers are widely used because of their simple structure and ease of implementation. However, the combined effects of communication delay and...
The quick growth of energy consumption in urban rail transit has drawn much attention due to the pressure of both operational cost and environmental responsibilities. In this paper, the timetable is optimized with respect to the system cost of urban...
Soft growing robots, which mimic the biological growth of plants, have demonstrated excellent performance in navigating tight and distant environments due to their flexibility and extendable lengths of several tens of meters. However, controlling the...
Nonlinear model predictive control (NMPC) delivers high tracking accuracy for industrial processes but requires solving a nonlinear program at each sampling instant, limiting its applicability under tight real-time constraints. The Koopman operator p...
Aiming to address the chicken-and-egg problem in star identification and the intrinsic parameter determination processes of on-orbit star sensors, this study proposes an on-orbit self-calibration method for star sensors that does not depend on star i...
Time, cost, and quality are critical factors that impact the production of intelligent manufacturing enterprises. Achieving optimal values of production parameters is a complex problem known as an NP-hard problem, involving balancing various constrai...
In the article, we propose a combination method based on the multigrid method and constraint data to solve the inverse problem in the context of the nonlinear convection–diffusion equation in the multiphase porous media flow. The inverse proble...
In this article, we introduce a novel framework for the design of multi set-point nonlinear explicit controllers for process systems engineering problems where the set-points are treated as uncertain parameters simultaneously with the initial state o...
This paper investigates the design and MATLAB/Simulink implementation of two intelligent neural reinforcement learning control algorithms based on deep learning neural network structures (RL DLNNs), for a complex Heating Ventilation Air Conditioning...
Path tracking control is a key technology in the research of intelligent vehicles. In the path tracking process of intelligent vehicles, there are multiple constraints and time-varying nonlinear system states. To address the problems of low tracking...
Inverse fuzzy model control (IFMC) is an attractive strategy for regulating nonlinear thermal processes, where complex heat-transfer dynamics, disturbances, and actuator constraints challenge conventional control approaches. However, traditional dire...
Nonlinear optimization with equation constraints has wide applications in intelligent control systems, acoustic signal processing, etc. Thus, effectively tackling the nonlinear optimization problems with equation constraints is of great significance...
For some highly nonlinear problems, the general second-order response surface method (RSM) cannot satisfy the accuracy requirement. To improve accuracy, the highest order number has to be determined in advance. Thus, a progressive trigonometric mixed...
Impulsive control is an effective approach for coordinating multi-agent systems in practical environments due to its high robustness and low cost. However, impulsive control exhibits characteristics such as high amplitude and rapid variation, potenti...
Smart grid private communication networks need to support heterogeneous services with varying requirements for reliability, security, bandwidth, and controllability. In such networks, service function chains (SFCs) can provide customized network serv...
Symmetries are crucial to the investigation of nonlinear physical processes, particularly the evaluation of a differential problem in the real world. This study focuses on the investigation of the Kadomtsev–Petviashvili
Steam conditioning is a key hydrothermal process for ensuring the quality of pelleted commercial swine compound feed. However, the molecular evolution of starch during processing remains poorly understood, particularly under the industrial constraint...
A method for the advanced construction of the dynamic matrix for Model Predictive Control (MPC) algorithms with linearization is proposed in the paper. It extends numerically efficient fuzzy algorithms utilizing skillful linearization. The algorithms...
Machine learning (ML) methods present a valuable opportunity for modeling the non-linear behavior of the injection molding process. They have the potential to predict how various process and material parameters affect the quality of the resulting par...
This work explores neural approximation for nonlinear dimensionality reduction mapping based on internal representations of graph-organized regular data supports. Given training observations are assumed as a sample from a high-dimensional space with...
This paper presents a more active and efficient recycling investment strategy that considers the balances among the current production constraints, manufacturing profits, and recycling investments for a sustainable circular economy as compared to the...
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