Information that people rely on is often uncertain and partially reliable. Zadeh introduced the concept of Z-numbers as a more adequate formal construct for describing uncertain and partially reliable information. Most existing applications of Z-numbers involve discrete ones due to the high complexity of calculating continuous ones. However, the continuous form is the most common form of information in the real world. Simplifying continuous Z-number calculations is significant for practical applications. There are two reasons for the complexity of continuous Z-number calculations: the use of normal distributions and the inconsistency between the meaning and definition of Z-numbers. In this paper, we extend the triangular distribution as the hidden probability density function of triangular Z-numbers. We add a new parameter to the triangular distribution to influence its convexity and concavity, and then expand the value's domain of the probability measure. Finally, we implement the basic operations of triangular Z-numbers based on the extended triangular distribution. The suggested method is illustrated with numerical examples, and we compare its computational complexity and the entropy (uncertainty) of the resulting Z-number to the traditional method. The comparison shows that our method has lower computational complexity, higher precision and lower uncertainty in the results.

In this paper, the resilient controller design and synthesis issues of networked control systems under denial-of-service (DoS) attacks are investigated via an adaptive event-triggered strategy. In a networked control system, DoS attacks have serious impacts on the security of communication, possibly causing degraded stability performance of the system. To remove threats from DoS attacks, an adaptive event-triggered communication mechanism is proposed, which also provides benefits in reducing the consumption of communication resources and relieving the pressure on network bandwidth. Since the system state information is usually not fully known, an observer-based controller is developed to stabilize the system and maintain a desired performance index despite the occurrence of stochastic attacks. Furthermore, a joint design method is proposed to obtain the controller gain, observer gain and event-triggered weight matrix. Finally, practical examples based on a four-tank system, an Internet-based three-tank system and an Internet-based test rig system are presented to illustrate the effectiveness of the proposed techniques to respond and eliminate the impact of DoS attacks.

This article addresses the event-triggered tracking control and filtering problem for Takagi–Sugeno fuzzy-approximation-based discrete-time nonlinear networked systems subject to the effect of denial-of-service attacks. First, the unreliability of the communication channel between the sensor and the actuator/filter is considered, and the packet loss caused by denial-of-service attacks is characterized by the binary Markov chain. Second, two novel resilient adaptive event-triggered mechanisms are proposed to resist the impact of denial-of-service attacks and discard unnecessary data packets, in which the dynamic threshold variable is designed to adjust the event-triggered condition adaptively. A problem caused by the event-triggered mechanism is that the controller or filter cannot receive the system mode signal during the trigger interval. To surmount this problem, this article designs an estimator to compensate for the unavailable system mode. Then, an adaptive event-triggered controller or filter related to the estimated mode is designed to track the desired signal. Under this framework, by constructing a membership-function-dependent Lyapunov function, the conservativeness of the stability criterion is relaxed. Finally, two examples are used to validate the applicability of the proposed approaches.

This paper proposes a new path planning strategy - the Rapid Visible Tree (RVT) algorithm to guide a robot to its goal in a complex environment without dangerous collisions. By fusing the visibility information with the classic tree-based searching method, RVT only takes the noisy points locally acquired from the environment as input and computes the visible region at each location to decide the growing direction of the path tree. Compared with traditional methods, RVT is more efficient, lightweight, and robust. We demonstrate that the RVT algorithm can not only complete the path planning task in real-time but also explore the unknown environment in simulated or real scenes.

This article is concerned with the problem of distributed model predictive control (DMPC) for second-order multiagent systems under event-triggered technique and logarithm quantized communication for a directed topological graph. Considering the limitation of communication bandwidth, a new bounded logarithm quantized communication strategy is proposed to preprocess the information before its transmission, thus reducing the influence of quantization error on the final convergence state. In order to decrease the frequency of control law update and reduce the power consumption, a distributed event-triggered rule is designed to decide when to transmit the information and when to optimize the model predictive control, in which trigger function synthesizes three factors, namely, predictive step, saturation of quantizer, and event-triggered error related with quantized error. The optimal control sequence of DMPC guides the update of controller between two triggering instants. The relationship among the quantization level, event-triggered parameters, and Laplacian matrix is established. Conditions are presented to ensure that all leaders asymptotically converge to a designed formation configuration, while all followers reach to the convex hull of them. Finally, an example is given to illustrate the effectiveness of the proposed methods.