2,674 research outputs found
Variance-constrained multiobjective control and filtering for nonlinear stochastic systems: A survey
The multiobjective control and filtering problems for nonlinear stochastic systems with variance constraints are surveyed. First, the concepts of nonlinear stochastic systems are recalled along with the introduction of some recent advances. Then, the covariance control theory, which serves as a practical method for multi-objective control design as well as a foundation for linear system theory, is reviewed comprehensively. The multiple design requirements frequently applied in engineering practice for the use of evaluating system performances are introduced, including robustness, reliability, and dissipativity. Several design techniques suitable for the multi-objective variance-constrained control and filtering problems for nonlinear stochastic systems are discussed. In particular, as a special case for the multi-objective design problems, the mixed H 2 / H ∞ control and filtering problems are reviewed in great detail. Subsequently, some latest results on the variance-constrained multi-objective control and filtering problems for the nonlinear stochastic systems are summarized. Finally, conclusions are drawn, and several possible future research directions are pointed out
Distributed filtering of networked dynamic systems with non-gaussian noises over sensor networks: A survey
summary:Sensor networks are regarded as a promising technology in the field of information perception and processing owing to the ease of deployment, cost-effectiveness, flexibility, as well as reliability. The information exchange among sensors inevitably suffers from various network-induced phenomena caused by the limited resource utilization and complex application scenarios, and thus is required to be governed by suitable resource-saving communication mechanisms. It is also noteworthy that noises in system dynamics and sensor measurements are ubiquitous and in general unknown but can be bounded, rather than follow specific Gaussian distributions as assumed in Kalman-type filtering. Particular attention of this paper is paid to a survey of recent advances in distributed filtering of networked dynamic systems with non-Gaussian noises over sensor networks. First, two types of widely employed structures of distributed filters are reviewed, the corresponding analysis is systematically addressed, and some interesting results are provided. The inherent purpose of adding consensus terms into the distributed filters is profoundly disclosed. Then, some representative models characterizing various network-induced phenomena are reviewed and their corresponding analytical strategies are exhibited in detail. Furthermore, recent results on distributed filtering with non-Gaussian noises are sorted out in accordance with different network-induced phenomena and system models. Another emphasis is laid on recent developments of distributed filtering with various communication scheduling, which are summarized based on the inherent characteristics of their dynamic behavior associated with mathematical models. Finally, the state-of-the-art of distributed filtering and challenging issues, ranging from scalability, security to applications, are raised to guide possible future research
Optimal control of nonlinear partially-unknown systems with unsymmetrical input constraints and its applications to the optimal UAV circumnavigation problem
Aimed at solving the optimal control problem for nonlinear systems with
unsymmetrical input constraints, we present an online adaptive approach for
partially unknown control systems/dynamics. The designed algorithm converges
online to the optimal control solution without the knowledge of the internal
system dynamics. The optimality of the obtained control policy and the
stability for the closed-loop dynamic optimality are proved theoretically. The
proposed method greatly relaxes the assumption on the form of the internal
dynamics and input constraints in previous works. Besides, the control design
framework proposed in this paper offers a new approach to solve the optimal
circumnavigation problem involving a moving target for a fixed-wing unmanned
aerial vehicle (UAV). The control performance of our method is compared with
that of the existing circumnavigation control law in a numerical simulation and
the simulation results validate the effectiveness of our algorithm
Non-fragile estimation for discrete-time T-S fuzzy systems with event-triggered protocol
summary:This paper investigates the non-fragile state estimation problem for a class of discrete-time T-S fuzzy systems with time-delays and multiple missing measurements under event-triggered mechanism. First of all, the plant is subject to the time-varying delays and the stochastic disturbances. Next, a random white sequence, the element of which obeys a general probabilistic distribution defined on , is utilized to formulate the occurrence of the missing measurements. Also, an event generator function is employed to regulate the transmission of data to save the precious energy. Then, a non-fragile state estimator is constructed to reflect the randomly occurring gain variations in the implementing process. By means of the Lyapunov-Krasovskii functional, the desired sufficient conditions are obtained such that the Takagi-Sugeno (T-S) fuzzy estimation error system is exponentially ultimately bounded in the mean square. And then the upper bound is minimized via the robust optimization technique and the estimator gain matrices can be calculated. Finally, a simulation example is utilized to demonstrate the effectiveness of the state estimation scheme proposed in this paper
Rauch-Tung-Striebel Smoother for Position Estimation of Short-Stroke Reluctance Actuators
This article presents a novel state estimator for short-stroke reluctance actuators, intended for soft-landing control applications in which the position cannot be measured in real time. One of the most important contributions regards the system modeling for the estimator. The discrete state of the hybrid system is treated as an input. Moreover, the model is simplified to facilitate the identification of parameters and the implementation of the estimator. Thus, auxiliary variables are added to the state vector in order to indirectly account for modeling errors. Another important contribution is the state estimation approach. It is based on the Rauch–Tung–Striebel fixed-interval smoother, which allows refining past data from later observations. Numerous simulations are performed to analyze and compare the proposal and several alternatives. In addition, experimental testing is presented to evaluate and validate the estimator. As the simulated and experimental analyses demonstrate, the combined effect of the novel additions results in significantly smaller estimation errors of position and velocity
Active Disturbance Rejection Control (ADRC) Toolbox for MATLAB/Simulink
In this study, an active disturbance rejection control (ADRC) toolbox for
MATLAB/Simulink is introduced. Although ADRC has already been established as a
powerful robust control framework with successful industrial implementations
and strong theoretical foundations, a comprehensive tool for computer-aided
design of ADRC has not been developed until now. The proposed open-source ADRC
Toolbox is a response to the growing need in the scientific community and the
control industry for a straightforward software application of the ADRC
methodology. Its main purpose is to fill the gap between the current theories
and applications of ADRC and to provide an easy-to-use solution for users in
various control fields who want to employ the ADRC scheme in their
applications. The ADRC Toolbox contains a single, general-purpose,
drag-and-drop function block that allows the synthesis of a predefined
ADRC-based strategy with minimal design effort. Additionally, its open
structure allows creation of custom control solutions. The efficacy of the ADRC
Toolbox is validated through both simulations and hardware experiments, which
were conducted using a variety of problems known in the motion, process, and
power control areas.Comment: 43 pages, 16 figures, 3 table
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Multi-sensor multi-rate fusion estimation for networked systems: Advances and perspectives
National Natural Science Foundation of China under Grants 62103095, 61873058, 61873148 and 61933007; AHPU Youth Top-notch Talent Support Program of China under Grant 2018BJRC009; Natural Science Foundation of Anhui Province of China under Grant 2108085MA07; Royal Society of the UK; Alexander von Humboldt Foundation of Germany
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