首页 | 本学科首页   官方微博 | 高级检索  
相似文献
 共查询到20条相似文献，搜索用时 31 毫秒
1.
Robust fault detection for a class of nonlinear time-delay systems   总被引：1，自引：0，他引：1  
In this paper, the robust fault detection filter (RFDF) design problems are studied for nonlinear time-delay systems with unknown inputs. Firstly, a reference residual model is introduced to formulate the robust fault detection filter design problem as an H∞ model-matching problem. Then appropriate input/output selection matrices are introduced to extend a performance index to the time-delay systems in time domain. The reference residual model designed according to the performance index is an optimal residual generator, which takes into account the robustness against disturbances and sensitivity to faults simultaneously. Applying robust H∞ optimization control technique, the existence conditions of the robust fault detection filter for nonlinear time-delay systems with unknown inputs are presented in terms of linear matrix inequality (LMI) formulation, independently of time delay. An illustrative design example is used to demonstrate the validity and applicability of the proposed approach.  相似文献   

2.
Unmanned surface vehicles (USVs) are a promising marine robotic platform for numerous potential applications in ocean space due to their small size, low cost, and high autonomy. Modelling and control of USVs is a challenging task due to their intrinsic nonlinearities, strong couplings, high uncertainty, under-actuation, and multiple constraints. Well designed motion controllers may not be effective when exposed in the complex and dynamic sea environment. The paper presents a fully data-driven learning-based motion control method for an USV based on model-based deep reinforcement learning. Specifically, we first train a data-driven prediction model based on a deep network for the USV by using recorded input and output data. Based on the learned prediction model, model predictive motion controllers are presented for achieving trajectory tracking and path following tasks. It is shown that after learning with random data collected from the USV, the proposed data-driven motion controller is able to follow trajectories or parameterized paths accurately with excellent sample efficiency. Simulation results are given to illustrate the proposed deep reinforcement learning scheme for fully data-driven motion control without any a priori model information of the USV.  相似文献   

3.
This paper presents an effective approach to stabilize nonlinear multiple time-delay (NMTD) interconnected systems via a composite of fuzzy controllers and dithers. First, a neural-network (NN) model is employed to approximate each subsystem. Then, the dynamics of the NN model is converted into a linear differential inclusion (LDI) state-space representation. Next, in terms of Lyapunov?s direct method, a delay-dependent stability criterion is derived to guarantee the exponential stability of the NMTD interconnected system. Subsequently, the stability conditions of this criterion are reformulated into a linear matrix inequality (LMI). Based on the LMI, a robustness design of fuzzy control is synthesized not only to stabilize the NMTD interconnected system but also to achieve the optimal H∞ performance by minimizing the disturbance attenuation level. A set of high-frequency signals (commonly referred to as dithers) is simultaneously injected to stabilize the NMTD interconnected system when the designed fuzzy controllers cannot stabilize it. If the dithers’ frequencies are high enough, the outputs of the dithered interconnected system and those of its corresponding mathematical model, the relaxed interconnected system, can be made as close as desired. This makes it possible to get a rigorous prediction of the stability of the dithered interconnected system by establishing the stability of the relaxed interconnected system. Finally, a numerical example with simulations is given to illustrate the feasibility of our approach.  相似文献   

4.
In precision motion systems, well-designed feedforward control can effectively compensate for the reference-induced error. This paper aims to develop a novel data-driven iterative feedforward control approach for precision motion systems that execute varying reference tasks. The feedforward controller is parameterized with the rational basis functions, and the optimal parameters are sought to be solved through minimizing the tracking error. The key difficulty associated with the rational parametrization lies in the non-convexity of the parameter optimization problem. Hence, a new iterative parameter optimization algorithm is proposed such that the controller parameters can be optimally solved based on measured data only in each task irrespective of reference variations. Two simulation cases are presented to illustrate the enhanced performance of the proposed approach for varying tasks compared to pre-existing results.  相似文献   

5.
This paper provides a systematic examination of the use of a Grand Innovation Prize (GIP) in action – the Progressive Automotive Insurance X PRIZE – a $10 million prize for a highly efficient vehicle. Following a mechanism design approach we define three key dimensions for GIP evaluation: objectives, design, and performance, where prize design includes ex ante specifications, ex ante incentives, qualification rules, and award governance. Within this framework we compare observations of GIPs from three domains – empirical reality, theory, and policy – to better understand their function as an incentive mechanism for encouraging new solutions to large-scale social challenges. Combining data from direct observation, personal interviews, and surveys, together with analysis of extant theory and policy documents on GIPs, our results highlight three points of divergence: first, over the complexity of defining prize specifications; secondly, over the nature and role of incentives, particularly patents; thirdly, the overlooked challenges associated with prize governance. Our approach identifies a clear roadmap for future theory and policy around GIPs.  相似文献   

6.
Data-driven innovation has received increasing attention, which explores big data technologies to gain more insights and advantages for product design. In user experience (UX) based design innovation, user-generated data and archived design documents are two valuable resources for various design activities such as identifying opportunities and generating design ideas. However, these two resources are usually isolated in different systems. Additionally, design information typically represented based on functional aspects is limited for UX-oriented design. To facilitate experience-oriented design activities, we propose a twin data-driven approach to integrate UX data and archived design documents. In particular, we aim to extract UX concepts from product reviews and design concepts from patents respectively and to discover associations between the extracted concepts. First, a UX-integrated design information representation model is proposed to associate capabilities with key elements of UX at the concept, category, and aspect levels of information. Based on this model, a twin data-driven approach is developed to bridge experience information and design information. It contains three steps: experience aspect identification using an attention-based LSTM (Long short-term memory) network, design information categorization based on topic clustering using BERT (Bidirectional Encoder Representations from Transformers) and LAD (Latent Dirichlet allocation) model, and experience needs and design information integration by leveraging word embedding techniques to measure concept similarity. A case study using healthcare-related experience and design information has demonstrated the feasibility and effectiveness of this approach.  相似文献   

7.
This paper investigates the consensus tracking problem of leader-follower multi-agent systems. Different from most existing works, dynamics of all the agents are assumed completely unknown, whereas some input-output data about the agents are available. It is well known from the Willems et al. Fundamental Lemma that when inputs of a linear time-invariant (LTI) system are persistently exciting, all possible trajectories of the system can be represented in terms of a finite set of measured input-output data. Building on this idea, the present paper proposes a purely data-driven distributed consensus control policy which allows all the follower agents to track the leader agent’s trajectory. It is shown that for a linear discrete-time multi-agent system, the corresponding controller can be designed to ensure the global synchronization with local data. Even if the data are corrupted by noises, the proposed approach is still applicable under certain conditions. Numerical examples corroborate the practical merits of the theoretical results.  相似文献   

8.
This paper presents a robust gain-scheduled output feedback yaw stability H∞ controller design to improve vehicle yaw stability and handling performance for in-wheel-motor-driven electric vehicles. The main control objective is to track the desired yaw references by managing the external yaw moment. Since vehicle lateral states are difficult to obtain, the state feedback controller normally requires vehicle full-state feedback is a critical challenge for vehicle lateral dynamics control. To deal with the challenge, the robust gain-scheduled output feedback controller design only uses measurements from standard sensors in modern cars as feedback signals. Meanwhile, parameter uncertainties in vehicle lateral dynamics such as tire cornering stiffness and vehicle inertial parameters are considered and handled via the norm-bounded uncertainty, and linear parameter-varying polytope vehicle model with finite vertices is established through reducing conservative. The resulting robust gain-scheduled output feedback yaw stability controller is finally designed, and solved in term of a set of linear matrix inequalities. Simulations for single lane and double lane change maneuvers are implemented to verify the effectiveness of developed approach with a high-fidelity, CarSim®, full-vehicle model. It is confirmed from the results that the proposed controller can effectively preserve vehicle yaw stability and lateral handling performance.  相似文献   

9.
This paper proposes an adaptive data-driven fault-tolerant control scheme using the Koopman operator for unknown dynamics subjected to nonlinearities, time-varying loss of effectiveness, and additive actuator faults. The main objective of this method is to design a virtual actuator to hide actuator faults from the view of the system’s nominal controller without having any prior knowledge about the system’s underlying dynamics. The designed virtual actuator is placed between the faulty plant and the nominal controller of the system to keep the dynamical system’s performance consistent before and after the occurrence of actuator faults. Based on the Koopman operator theory, an equivalent Koopman predictor is first obtained using the process data only, without knowing the governing equations of the underlying dynamics. Koopman operator is an infinite-dimensional, linear operator which takes the nonlinear process data into an infinite-dimensional feature space where the dynamic data correlations have linear behavior. Next, based on the approximated system’s Koopman operator, a virtual actuator is designed and implemented without knowing the system’s nominal controller. Needless to use a separate fault detection, isolation, and identification module to perform fault-tolerant control, the current method leverages the adaptive framework to keep the system’s desired performance in facing time-varying additive and loss of effectiveness actuator faults. Finally, the approach’s efficacy is demonstrated using simulation on a two-link manipulator benchmark, and a comparison study is presented.  相似文献   

10.
This paper investigates the mixed H∞ and passive control problem for a class of nonlinear switched systems based on a hybrid control strategy. To solve this problem, firstly, using the Takagi–Sugeno (T–S) fuzzy model to approximate every nonlinear subsystem, the nonlinear switched systems are modeled as the switched T–S fuzzy systems. Secondly, the hybrid controllers are used to stabilize the switched T–S fuzzy systems. The hybrid controllers consist of dynamic output-feedback controllers for every subsystem and state updating controllers at the switching instant. Thirdly, a new performance index is proposed for switched systems. This new performance index can be viewed as the mixed weighted H∞ and passivity performance. Based on this new performance index, the weighted H∞ control problem and the passive control problem for switched T–S fuzzy systems via the hybrid control strategy are solved in a unified framework. Together the multiple Lyapunov functions (MLFs) approach with the average dwell time (ADT) technique, new design conditions for the hybrid controllers are obtained. Under these conditions, the closed-loop switched T–S fuzzy systems are globally uniformly asymptotically stable with a prescribed mixed H∞ and passivity performance index. Moreover, the desired hybrid controllers can be constructed by solving a set of linear matrix inequalities (LMIs). Finally, the effectiveness of the obtained results is illustrated by a numerical example.  相似文献   

11.
In this paper, a novel decentralized adaptive neural control approach based on the backstepping technique is proposed to design a decentralized H∞ adaptive neural controller for a class of stochastic large-scale nonlinear systems with external disturbances and unknown nonlinear functions. RBF neural networks are utilized to approximate the packaged unknown nonlinearities. A novel concept with regard to bounded-H∞ performance is proposed. It can be applied to solve an H∞ control problem for a class of stochastic nonlinear systems. The constant terms appeared in stability analysis are dealt with by using Gronwall inequality, so that H∞ performance criterion is satisfied. The assumption that the approximation errors of neural networks must be square-integrable in some literature can be eliminated. The design process for decentralized bounded-H∞ controllers is given. The proposed control scheme guarantees that all the signals in the resulting closed-loop large-scale system are uniformly ultimately bounded in probability, and each subsystem possesses disturbance attenuation performance for external disturbances. Finally, the simulation results are provided to illustrate the effectiveness and feasibility of the proposed approach.  相似文献   

12.
To alleviate the restriction of system model on control design, data-driven model-free adaptive control (MFAC) is an excellent alternative to model-based control methods. This paper studies event-triggered data-driven control for switched systems over a vulnerable and resource-constrained network. The system is transformed into an equivalent switched data model through dynamic linearization. Resource constraints and denial of service (DoS) attacks in the network are concerned, and a novel joint anti-attack method including resilient event-triggering mechanism and prediction scheme is presented. Furthermore, new event-triggered MFAC algorithms are proposed. In this scenario, by constructing a Lyapunov functional on tracking error, sufficient conditions to ensure its boundedness are derived. This is the first time in the literature to give a complete solution to data-driven control of switched systems. At last, the validity of new algorithms and theoretical results is confirmed by simulations.  相似文献   

13.
We present a 3-staged method for automated learning of the spatial density function of the mass of all gravitating matter in a real galaxy, for which, data exist on the observable phase space coordinates of a sample of resident galactic particles that trace the galactic gravitational potential. We learn this gravitational mass density function, by embedding it in the domain of the probability density function (pdf) of the phase space vector variable, where we learn this pdfas well, given the data. We generate values of each sought function, at a design value of its input, to learn vectorised versions of each function; this creates the training data, using which we undertake supervised learning of each function, to thereafter undertake predictions and forecasting of the functional value, at test inputs. We assume that the phase space that a kinematic data set is sampled from, is isotropic, and we quantify the relative violation of this assumption, in a given data set. Illustration of the method is made to the real elliptical galaxy NGC4649. The purpose of this learning is to produce a data-driven protocol that allows for computation of dark matter content in any example real galaxy, without relying on system- specific astronomical details, while undertaking objective quantification of support in the data for undertaken model assumptions.  相似文献   

14.
This paper addresses the positive filter design problem for a class of continuous-discrete Roesser model in Takagi-Sugeno fuzzy form. Both the observer-based and the general form of filters are designed with l1 performance constraint. By utilizing the co-positive Lyapunov function approach, sufficient criteria are derived in the form of linear programming, which not only guarantee the existence of the positive lower-bounding/upper-bounding filters but also assure the resulting filtering error system to be asymptotically stable and having a prescribed l1-gain performance index. In addition, the explicit design schemes for the corresponding filter parameters are also presented. Finally, two numerical examples are provided to illustrate effectiveness of the proposed results.  相似文献   

15.
In this paper two robust controllers for a multivariable vertical short take-off and landing (VSTOL) aircraft system are designed and compared. The aim of these controllers is to achieve robust stability margins and good performance in step response of the system. LQG/LTR method is a systematic design approach based on shaping and recovering open-loop singular values while mixed-sensitivity H∞ method is established by defining appropriate weighting functions to achieve good performance and robustness. Comparison of the two controllers show that LQG method requires rate feedback to increase damping of closed-loop system, while H∞ controller by only proper choose the weighting functions, meets the same performance for step response. Output robustness of both controllers is good but H∞ controller has poor input stability margin. The net controller order of H∞ is higher than the LQG/LTR method and the control effort of them is in the acceptable range.  相似文献   

16.
This paper proposes a scheme to achieve real-time stability performance monitoring (SPM) and designs performance recovery controllers (PRCs) for feedback control systems with multiplicative faults. To be specific, a stability performance indicator is presented with the aid of stable image representation (SIR) for multiplicative faults through coprime factorization techniques. On this basis, a systematically hierarchical SPM and PRC scheme is proposed with three thresholds derived to evaluate the performance degradation degree. Subsequently, an integrated model-based and data-driven SIR-based PRC is presented to recover system stability performance. The embedded PRC parameters are adaptive to system variations by means of identifying the SIR of the faulty plant through a dual parity vector. Besides, some QR-decomposition based data-driven techniques are provided for the implementation of PRC to improve computation efficiency. Finally, the effectiveness of the proposed approach is demonstrated on a boost circuit model.  相似文献   

17.
Distributed multi-actuator systems can provide effective solutions for mitigating the vibrational response of large structures. In this paper, we present a computational strategy to design inerter-based multi-actuation systems for the seismic protection of adjacent structures. The proposed approach allows considering both interstory and interbuilding Tuned Mass-Inerter Damper (TMID) actuators, and aims at simultaneously reducing the vibrational response of the individual buildings and avoiding the interbuilding impacts. The tuning procedure is based on an H∞ cost-function and uses a constrained global-optimization solver to compute parameter configurations with high-performance characteristics. To illustrate the main features of this work, two different Tuned Inerter Damper (TID) multi-actuator schemes are considered for the seismic protection of a particular multi-story two-building system. A multi-actuator Tuned Mass Damper (TMD) system is also designed and is taken as a reference in the performance assessment. The obtained results demonstrate the flexibility and effectiveness of the proposed design methodology, and clearly show the superior performance and robustness of the TID actuation systems.  相似文献   

18.
Many existing systems for analyzing and summarizing customer reviews about products or service are based on a number of prominent review aspects. Conventionally, the prominent review aspects of a product type are determined manually. This costly approach cannot scale to large and cross-domain services such as Amazon.com, Taobao.com or Yelp.com where there are a large number of product types and new products emerge almost everyday. In this paper, we propose a novel method empowered by knowledge sources such as Probase and WordNet, for extracting the most prominent aspects of a given product type from textual reviews. The proposed method, ExtRA (Extraction of Prominent Review Aspects), (i) extracts the aspect candidates from text reviews based on a data-driven approach, (ii) builds an aspect graph utilizing the Probase to narrow the aspect space, (iii) separates the space into reasonable aspect clusters by employing a set ofproposed algorithms and finally (iv) generates K most prominent aspect terms or phrases which do not overlap semantically automatically without supervision from those aspect clusters. ExtRA extracts high-quality prominent aspects as well as aspect clusters with little semantic overlap by exploring knowledge sources. ExtRA can extract not only words but also phrases as prominent aspects. Furthermore, it is general-purpose and can be applied to almost any type of product and service. Extensive experiments show that ExtRA is effective and achieves the state-of-the-art performance on a dataset consisting of different product types.  相似文献   

19.
Privacy has raised considerable concerns recently, especially with the advent of information explosion and numerous data mining techniques to explore the information inside large volumes of data. These data are often collected and stored across different institutions (banks, hospitals, etc.), or termed cross-silo. In this context, cross-silo federated learning has become prominent to tackle the privacy issues, where only model updates will be transmitted from institutions to servers without revealing institutions’ private information. In this paper, we propose a cross-silo federated XGBoost approach to solve the federated anomaly detection problem, which aims to identify abnormalities from extremely unbalanced datasets (e.g., credit card fraud detection) and can be considered a special classification problem. We design two privacy-preserving mechanisms that are tailored to the federated XGBoost: anonymity based data aggregation and local differential privacy. In the anonymity based data aggregation scenario, we cluster data into different groups and using a cluster-level data feature to train the model. In the local differential privacy scenario, we design a federated XGBoost framework by incorporate differential privacy in parameter transmission. Our experimental results over two datasets show the effectiveness of our proposed schemes compared with existing methods.  相似文献   

20.
The estimation of query model is an important task in language modeling (LM) approaches to information retrieval (IR). The ideal estimation is expected to be not only effective in terms of high mean retrieval performance over all queries, but also stable in terms of low variance of retrieval performance across different queries. In practice, however, improving effectiveness can sacrifice stability, and vice versa. In this paper, we propose to study this tradeoff from a new perspective, i.e., the bias–variance tradeoff, which is a fundamental theory in statistics. We formulate the notion of bias–variance regarding retrieval performance and estimation quality of query models. We then investigate several estimated query models, by analyzing when and why the bias–variance tradeoff will occur, and how the bias and variance can be reduced simultaneously. A series of experiments on four TREC collections have been conducted to systematically evaluate our bias–variance analysis. Our approach and results will potentially form an analysis framework and a novel evaluation strategy for query language modeling.  相似文献   

设为首页 | 免责声明 | 关于勤云 | 加入收藏

Copyright©北京勤云科技发展有限公司  京ICP备09084417号