Summary The design of tracking control problem and compensation of disturbance for switched neutral systems with multiple time‐delays and external disturbances are addressed in this paper. In this regard, a modified repetitive control technique based on the Matausek‐Micic modified Smith predictor approach is being implemented, which assures the exact tracking performance and disturbance attenuation with high precision in the considered system. To be specific, the integration of transfer function with modified Smith predictor block not only provides the accurate compensation of input time‐delays but also ensures the exact estimation and attenuation of external disturbances effectually. Furthermore, according to Lyapunov stability approach combined with average‐dwell‐time technique, a group of adequate conditions is derived in the form of matrix inequalities. Simultaneously, by solving the established matrix inequalities using available software the controller gain matrices are calculated. Ultimately, the simulation results of three numerical examples are presented to validate the efficiency and dominance of the suggested control procedure.
The demand for low-cost and low-power decoder chips has resulted in renewed interest in low-complexity decoding algorithms. In this paper a novel modification of the Max-Log-MAP algorithm is proposed for use in a turbo decoding process. This is achieved by scaling the a priori information by correction weights at each iteration, in order to maximize the exchange of mutual information between the component decoders. It is shown that the proposed technique results in a performance which approaches that of a turbo decoder using the optimum MAP algorithm, while maintaining the advantages of low complexity and insensitivity to input scaling inherent in the Max-Log-MAP algorithm. A second contribution of this paper is a method for off-line computation of the optimum weight values. The convergence behaviour of the proposed decoder is analysed via extrinsic information transfer (EXIT) charts.
The non-fragile fault-tolerant control for a class of nonlinear Markovian jump systems with intermittent multiple actuator faults is addressed in this study. The nonlinearity in the considered system is assumed to satisfy sector constraint. Multiple Markov chains are introduced to model the multiple intermittent actuator faults, which is in a multiplicative form. To ensure the fault tolerance of the closed-loop system in the presence of potential controller perturbation, a new non-fragile fault-tolerant controller is designed, which can stabilize the resulting closed-loop system and further satisfy a prescribed performance index. After appropriately synthesizing the fault model that dominated by multiple Markov chains and the underlying nonlinear Markovian jump system, a set of sufficient conditions for the considered problem focusing on the controller design is derived with both known and partially known transition probabilities, where the controller can be determined via a convex optimization procedure. An example is given to illustrate the effectiveness of the proposed controller.
This paper investigates the problem of exponential H <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">∞</sub> synchronization for a class of master-slave systems with both discrete and distributed time-delays, norm-bounded nonlinear uncertainties and Markovian switching parameters. Using an appropriate Lyapunov-Krasovskii functional, some delay-dependent sufficient conditions and a synchronization law which include the master-slave parameters are established for designing a delay-dependent mode-dependent sliding mode exponential H <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">∞</sub> synchronization control law in terms of linear matrix inequalities. The controller guarantees the H <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">∞</sub> synchronization of the two coupled master and slave systems regardless of their initial states. A numerical example is given to show the effectiveness of the method.
The 3rd International Conference on Innovations and Development of Information Technologies and Robotics (IDITR 2024). IDITR 2024 was successfully held at Hong Kong Polytechnic University, Hong Kong, China during May 23-25, 2024. The conference was jointly co-organized by Joint Chapter, Control Systems/Robotics and Automation Society (CS/RA), IEEE Hong Kong Section, Hong Kong Polytechnic University and Hong Kong Society of Mechanical Engineers(HKSME), supported by IEEE Chengdu Section and China University of Mining and Technology, media supported by Journal of Jiangsu University (Natural Science Edition).
No abstract is provided for this article.
In the car industry, the Finite Element Method (FEM) is being more and more used to analyze the crashworthiness performance of vehicles. In order to validate the results, these impact simulations are normally compared with real crash footage and acceleration data. This paper studies the deformation- and energy output of a simple dummy model during a non-linear dynamic impact. The dummy model is crashed into an obstacle at three different velocities to observe the energy dissipated through different damping mechanisms. Furthermore, in impact simulations, material damping plays an important role in energy dissipation. However, it can be difficult to determine realistic damping parameter values, and they almost certainly need to be verified through experiments. For further work, these results will be used to validate and calibrate an impact simulation of a dummy model attached to a notch impact equipment.
Remaining driving range (RDR) research has continued to consistently evolve with the development of electric vehicles (EVs). Accurate RDR prediction is a promising approach to alleviate distance anxiety when power battery technology is not yet fully matured. This paper first introduces the research motivation of RDR prediction, summarizes the previous research progress, and classifies the influencing factors of RDR. Second, conduct research and analysis on the physical model of EVs, mainly including battery and vehicle models. Based on the physical model, the energy flow problem of EVs is analyzed and discussed. Third, four key challenges of RDR prediction are summarized: battery state estimation, driving behavior classification and recognition, driving condition prediction and speed prediction, and RDR calculation method. Finally, given the four challenges faced by RDR, a driving range prediction method based on vehicle‐cloud collaboration is proposed, which combines the advantages of cloud computing and machine learning to provide further research trends.
This chapter presented a robust data-driven fault detection scheme with the application to a wind turbine benchmark. The proposed scheme is based on robust residual generators constructed directly from available process measurements. For this purpose, a parity space is first identified from the measured data, and optimal parity vectors are selected from the parity space according to a given performance index and an optimization criterion to generate a robust residual vector. A proper evaluation approach as well as a suitable decision logic is further given to make a correct final decision. The effectiveness of the proposed scheme is finally demonstrated by the results obtained from the simulation of a wind turbine benchmark model.
In this paper, we extend the wavelet networks for identification and H ∞ control of a class of nonlinear dynamical systems. The technique of feedback linearization, supervisory control and H ∞ control are used to design an adaptive control law and also the parameter adaptation laws of the wavelet network are developed using a Lyapunov-based design. By some theorems, it will be proved that even in the presence of modeling errors, named network error, the stability of the overall closed-loop system and convergence of the network parameters and the boundedness of the state errors are guaranteed. The applicability of the proposed method is illustrated on a nonlinear plant by computer simulation.
Notice of Violation of IEEE Publication Principles<br><br>After careful consideration by a duly constituted committee, an author of this article, Hamid Reza Karimi, was found to have acted in violation of the IEEE Principles of Ethical Publishing by artificially inflating the number of citations to this article. <br/> This paper is concerned with dissipativity-based fuzzy integral sliding mode control (FISMC) of continuous-time Takagi-Sugeno (T-S) fuzzy systems with matched/unmatched uncertainties and external disturbance. To better accommodate the characteristics of T-S fuzzy models, an appropriate integral-type fuzzy switching surface is put forward by taking the state-dependent input matrix into account, which is the key contribution of the paper. Based on the utilization of Lyapunov function and property of the transition matrix for unmatched uncertainties, sufficient conditions are presented to guarantee the asymptotic stability of corresponding sliding mode dynamics with a strictly dissipative performance. A FISMC law is synthesized to drive system trajectories onto the fuzzy switching surface despite matched/unmatched uncertainties and external disturbance. A modified adaptive FISMC law is further designed for adapting the unknown upper bound of matched uncertainty. Two practical examples are provided to illustrate the effectiveness and advantages of developed FISMC scheme.
No abstract is provided for this article.
Simultaneous perturbation stochastic approximation (SPSA) has been widely investigated in active noise control (ANC) due to its model-free nature, which eliminates the need for system model estimation. Despite extensive efforts to enhance its performance, SPSA may suffer from instability and convergence issues, particularly in challenging environments. In this paper, we propose a stepwise SPSA algorithm that applies perturbations separately rather than simultaneously, significantly improving stability while maintaining comparable performance to standard SPSA. A Lyapunov-based theoretical analysis proves the algorithm's robust stability. A parameter optimization framework further enhances performance by guiding the selection of perturbation coefficients and step sizes. Numerical simulations and real-time DSP board implementation validate the improved stability and practical effectiveness for ANC applications.
The current paper describes an apparatus for full scale vehicle crash test experimentation. This apparatus is referred to as the Harp. In brief, the Harp may either accelerate a trolley which is impacted into a test vehicle or the test vehicle itself may be accelerated and impacted into an object such as a barrier, a pole or another vehicle. The trolley/vehicle is equipped with instruments which record the axial crushing force during the impact. At the impact site, high speed cameras and instrumentation record vital data during the crash.
