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This paper presents an adaptive nonsingular terminal sliding mode formation control by means of output recurrent fuzzy wavelet neural networks for a group of networked heterogeneous Mecanum-wheeled omnidirectional robots with uncertainties. The dynamic behavior of each uncertain heterogeneous omnidirectional robot is modelled by a reduced three-input-three-output second-order state equation with uncertainties...
The paper is concerned with the robust finite-time stabilization problem of quadrotors subject to inertia uncertainty and disturbances. The underlying stabilization problem consists of controller designs for position loop and attitude loop, both of which are carried out based on the terminal sliding mode control approach. First, a robust finite-time position controller is designed by considering the...
Brain-state drifts could significantly impact on the performance of machine-learning algorithms in brain computer interface (BCI). However, less is understood with regard to how brain transition states influence a model and how it can be represented for a system. Herein we are interested in the hidden information of brain state-drift occurring in both simulated and real-world human-system interaction...
Bayesian Optimization or Efficient Global Optimization (EGO) is a global search strategy that is designed for expensive black-box functions. In this algorithm, a statistical model (usually the Gaussian process model) is constructed on some initial data samples. The global optimum is approached by iteratively maximizing a so-called acquisition function, that balances the exploration and exploitation...
This paper, considering the complexity of university internal governance effect and particularity of the university itself, aims to build a indicator system to evaluate university internal governance effect, using the Grey Multilayer Comprehensive Assessment Method to evaluate this indicator system, whilst applying the Analytical Hierarchical Process (AHP) and Entropy Evaluation Method to define the...
We explore the use of adaptive control for a hydraulic actuator model in an engine with variable cam timing (VCT) system. The hydraulic actuator is modeled as a Hammer-stein system with an asymmetric, uncertain input nonlinearity followed by known time delay and linear dynamics. We begin the presentation by designing a fixed-gain baseline controller, which consists of a PI controller with high robustness...
The intuitionistic fuzzy set which is characterized by a membership degree and a non-membership degree, is a very powerful and useful tool to cope with fuzziness and uncertainty. Recently, the Pythagorean fuzzy set which is an extension of the intuitionistic fuzzy set has been introduced. In this paper, we focus on multi-attribute decision making with Pythagorean fuzzy information. First of all, considering...
In this paper, we propose a mechanism for cancer cell differentiation therapy based on a game-theoretic rough set model with intuitionistic fuzzy set. We introduce an intuitionistic fuzzy relation with the help of fuzzy compatibility relation. The approximation space classification is controlled with a pair of intuitionistic fuzzy thresholds. It provides a flexibility to set up tolerance level depending...
In multiple attribute decision analysis (MADA) problems, one often needs to deal with assessment information with uncertainty. The evidential reasoning approach is one of the most effective methods to deal with such MADA problems. As a kernel of the evidential reasoning approach, an original evidential reasoning (ER) algorithm was firstly proposed by Yang et al, and later they modified the ER algorithm...
Supply chain risk management is one of significant issues in the design and operations of supply chains. It is well-known that leader-follower relationship influences the decision making of decentralized supply chains. In this paper, we address a game theoretical analysis of the leadership structure in the decentralized supply chain with risky supplier under demand uncertainty. The risky supplier...
In this paper, an interal observer for both state and unknown input estimation is proposed for a Linear Time Invariant (LTI) system. It generalizes previous work done on the subject. Such an observer is constructed under some specific conditions. Among those conditions, a rank condition is needed to ensure the independence between the state estimation and the unknown input. In this paper, former proposed...
In this paper, a power system model is proposed to achieve a decentralized voltage control scheme. A stabilizing controller design is presented to solve the voltage regulation problem with output feedback. The model is intended to be an exact representation of frequency and terminal voltage, which will allow us to cope with time-varying parameter uncertainties, and also unknown design parameters of...
In this paper, we investigate distributed consensus problems for multiple miniature aerial vehicles (MAVs) with nonlinear dynamics and uncertainty. We develop distributed consensus protocol to solve regulation synchronization problem for leaderless MAVs with directed interaction topology. Adaptive control algorithms are used locally for each vehicle to deal with nonlinear dynamics and uncertainty...
In many real-life situations, we know the upper bound of the measurement errors, and we also know that the measurement error is the joint result of several independent small effects. In such cases, due to the Central Limit Theorem, the corresponding probability distribution is close to Gaussian, so it seems reasonable to apply the standard Gaussian-based statistical techniques to process this data...
The ability to conduct fast and reliable simulations of dynamic systems is of special interest to many fields of operations. Such simulations can be very complex and, to be thorough, involve millions of variables, making it prohibitive in CPU time to run repeatedly for many different configurations. Reduced-Order Modeling (ROM) provides a concrete way to handle such complex simulations using a realistic...
The expert selection is an important decision problem in the research and development process of complex product systems (CoPS) projects and suitable experts will facilitate the successful task achievement. Existing methods for the expert selection are mostly based on the individual performance, whereas the task characteristics of CoPS projects and the knowledge correlationship between candidates...
The interaction between a human driver and an automated driving system may improve when the automation is designed in such a way that it behaves in a human-like manner. This paper introduces a human-like steering model, in which the driver adapts to the risk due to uncertainty in the environment. Current steering models take a risk-neutral approach, while the fields of economics and sensorimotor control...
This paper investigates the uncertainty of the day-ahead distribution system scheduling considering the random variations of both Photovoltaic-based distributed generator (PV-DG) output power and load. Instead of Monte-Carlo simulation (MCS), a two-point estimation method (2PEM) is applied to obtain accurate and computation-efficient analysis results. Based on the two-year real-world hourly weather...
Proactive cognitive agents need to be capable of both generating their own goals and enacting them. In this paper, we cast this problem as that of maintaining equilibrium, that is, seeking opportunities to act that keep the system in desirable states while avoiding undesirable ones. We characterize desirability of states as graded preferences, using mechanisms from the field of fuzzy logic. As a result,...
This paper highlights the necessity of the rider weight consideration during observer's design for motorcycle dynamics estimation or control. It presents a novel approach using a linear parameter varying (LPV) model associated with the well-know Takagi-Sugeno (TS) methods to derive a robust observer regarding the rider weight uncertainty. Then the proposed solution is illustrated with an application...
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