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Xiaoli Li - IEEE Xplore Author Profile

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In this paper, a fault-tolerant-based online critic learning algorithm is developed to solve the optimal tracking control issue for nonaffine nonlinear systems with actuator faults. First, a novel augmented plant is constructed by fusing the system state and the reference trajectory, which aims to transform the optimal fault-tolerant tracking control design with actuator faults into the optimal re...Show More
In this article, a global output feedback control scheme is developed for a class of uncertain nonlinear systems subject to input quantization and unknown output function. By employing a time-varying gain and a time-invariant gain, we address the challenges posed by quantization errors and nonlinear functions with an unknown linear growth rate. Additionally, we determine an allowable measurement s...Show More
This article investigates the predefined-time tracking problem for high-order strict feedback system. Modified command filter can not only avoid the “computational complexity explosion” phenomenon in traditional backstepping methods, but also alleviate the chattering problem caused by signum in conventional filters. A novel predefined-time compensation system is proposed to compensate for the decr...Show More
This paper investigates the issue of adaptive finite-time tracking for nonlinear systems with both quantized input and states. More specially, a saturated quantized input is applied for the input quantization. By constructing a novel high-gain fuzzy state observer, the issues of unknown nonlinearities and discontinuous quantized signals are addressed. Then an adaptive backstepping controller invol...Show More
In the intricate process of steel manufacturing, the precise measurement of molten iron is a pivotal procedure, which directly impacts the quality of steel production. Rail weighbridges are commonly deployed in the steel industry for molten iron measurement. Therefore, the accuracy of rail weighbridges weighing data is extremely important. However, due to process intricacies and equipment nuances,...Show More
This paper introduces a novel state and input constrained optimal tracking control method to address limitations posed by only partially known robot system models and constrained physical variables, such as joint position, velocity, and torque during the control process. The method employs the slack function and nonquadratic function methods to effectively handle state error and input constraints,...Show More
In many basic oxygen furnace (BOF) steelmaking processes, if the furnace endpoint carbon can be monitored in real time, it is a breakthrough for BOF steelmaking intelligence. This paper presents a deep learning model used to predict the endpoint carbon content in BOF steelmaking process. A convolution long short-term memory network based on attention mechanism (CNN-LSTM-AM) model is proposed for t...Show More
Visual classification has attracted considerable research attention in the last few decades. This paper presents an approach to improve the hypergraph structure using a diffusion ranking method and employs hypergraph neural networks for such tasks. Hyperedges are formed by connecting a set of vertices, and the generation of the hypergraph structure is typically task-dependent, making hypergraph ge...Show More
Confronted with the limitations of conventional Planning Domain Definition Language (PDDL) in dynamic and unpredictable kitchen environments, this paper introduces a novel task planning methodology that leverages the synergy between advanced scene graphs. This interdisciplinary approach begins with the construction of a detailed task directive-target state dataset, which serves as the foundation f...Show More
As of 2018, China had more than 550,000 data centers, accounting for approximately 1.5% of the country’s total annual electricity consumption. Reducing energy consumption not only lowers costs but also aligns with environmental protection principles. Current research primarily focuses on IT equipment and air conditioning and refrigeration systems, as these components offer significant potential fo...Show More
Nowadays flue gas desulphurization (FGD) technologies have been extensively applied in the coal-fired electricity-generating plants. As emission standards for sulfur dioxide (SO2) have become more stringent in recent years, there is a real need to develop more advanced modeling techniques such that the FGD process can be identified accurately, which in turn provides a reliable foundation for FGD p...Show More
This paper develops a composite output consensus control protocol for a general linear multiagent system subject to mismatched disturbances, which incorporates active disturbance-rejection control and fully distributed adaptive consensus control. To estimate and then cancel out the effect of mismatched disturbances on the outputs of the agents, heterogeneous generalized equivalent-input-disturbanc...Show More
In this article, based on the concept of an equivalent-input-disturbance (EID), a tunable nonlinear-function-based estimator is developed for fast and efficient control of unknown and mismatched disturbances of a tracking control system, and the control performances are analyzed. A great superiority over the conventional EID estimators is that the gain is varying and tunable with respect to an int...Show More
This paper designs an observer-based output feedback controller for traffic flow with stop-and-go waves and disturbances in order to dissipate traffic congestion. The macroscopic traffic flow dynamics in the congestion regime is described by the linearized Aw-Rascle-Zhang (ARZ) traffic flow model over a time-varying moving spatial domain, and according to the Rankine-Hugoniot condition and the cha...Show More
This paper focuses on the adaptive output feedback tracking control of uncertain nonlinear systems with both quantized input and output. The only available signal is the non-differentiable quantized output, which makes the adaptive quantized controller hard to achieve via output feedback. Our research shows that this difficulty can be circumvented by utilizing the well known dynamic surface contro...Show More
In this paper, combining the advantages of regularized echo state network and improved sparrow search optimization, a novel prediction control method is proposed. Compared with the traditional recurrent neural network, the prediction model based the regularized echo state network has the advantages of simple training and less computational burden. Through using the reverse learning strategy and th...Show More
After training, the parameters and weights of the standard echo state network are fixed, which will result in poor prediction accuracy for different types of input data. Therefore, a weak-consciousness echo state network (W-ESN) for time series prediction is proposed in this article. By introducing the concept of “label” in the network, the network can select the optimal network weights and parame...Show More
This paper is concerned with providing a minimum dwell time switching method which guarantees the asymptotic stability under spatio-temporal constraints of switched nonlinear systems. Firstly, the spatio-temporal constraints considered here consist of two specifications: (1) the state trajectory is required to remain in a given region for each subsystem, and (2) the state trajectory is required to...Show More
The sulfur dioxide (SO2) concentration of flue gas in metal smelting industry is high and difficult to recycle. The commonly used SO2 desulfurization treatment is acid production from flue gas, however, it is difficult to directly measure the conversion rate of SO2. In this paper, we present a soft sensor method based on Long Short-Term Memory (LSTM) which integrates the attention mechanism for pr...Show More
The effective control of converter inlet temperature in the process of acid production with flue gas is an effective means to improve the conversion rate of sulfur dioxide and reduce environmental pollution. According to the characteristics of the process of acid production with flue gas, the control process of converter inlet temperature is studied in this paper. Firstly, the CARIMA (Controlled a...Show More
The quality of flotation conditions directly affects the flotation efficiency. Aiming at the problems of difficult online detection, strong subjective arbitrariness, and low recognition efficiency of various flotation conditions in actual flotation work, a flotation condition recognition method based on hypergraph neural network (HGNN) and dynamic feature of forth images is proposed in this paper....Show More
The heating, ventilation, and air conditioning(HVAC) system consumes a large amount of energy in buildings. Accurate modeling of the HVAC refrigeration room system is crucial for building temperature control and optimization of energy consumption. In this paper, Levenberg Marquardt (LM) algorithm and particle swarm optimization (PSO) algorithm are used to establish a nonlinear autoregressive neura...Show More
Heating, Ventilation and Air Conditioning (HVAC) system is a highly nonlinear system with a large amount of complex, coupled inputs. This paper presents a novel prediction method for HVAC energy consumption based on deep neural network (DNN). In order to solve the problem that traditional neural networks tend to fall into local optima, batch normalization and Adam optimization algorithm are signif...Show More
This paper proposes a data-driven, multi-objective optimization control method based on policy iteration for flotation process, addressing the limitations of existing control methods that rely on the system model and cannot satisfy multiple performance indices simultaneously. Firstly, The ordinary linear quadratic regulator algorithm is improved with process data, enabling the algorithm to obtain ...Show More
Due to the complex process of flue gas acid production and numerous processes, the controlled objects in the whole process have the characteristics of time-variation, randomness, nonlinearity and large lag. For SO2 fan, because the traditional PID control adopts the parameters set in advance, it is difficult to play an effective role in the complex flue gas acid production system, therefore, a fuz...Show More