Event-triggered stochastic consensus for networked Lagrangian systems with semi-Markov switching topologies and communication delays

In this paper, the event-triggered stochastic consensus for networked Lagrangian systems with semi-Markov switching topologies and communication delays is considered. An event-triggered sampling control strategy is used to design the distributed stochastic consensus scheme of networked Lagrangian systems for two cases with leader and leaderless. Two delay-dependent consensus criteria are derived in the sense of mean square by use of a suitable Lyapunov-Krasovskii functional and the stochastic delayed Halanay inequality, respectively. A key feature of the developed event-triggered consensus algorithm is to introduce a suitable adjustment parameter on consensus control gains characterizing the effect of both semi-Markov switching topology and communication delay. Finally, a numerical example of four manipulators with two links is presented to illustrate the effectiveness of the developed event-triggered methodology.

Research on the Dynamic Pricing and Service Decisions in the Reverse Supply Chain considering Consumers’ Service Sensitivity

In this work, considering consumers’ service sensitivity for the third-party collector in the reverse supply chain, a game model (including a manufacturer and a third-party collector) with dual-channel recycling structure was established. Based on the bounded rationality, we used dynamics theory to analyze the dynamic service and pricing decisions of the manufacturer and the third-party collector in the process of collecting waste products. The results showed that adjustment speeds of pricing and service decisions have great effect on the stability of recycling market, and the recycling market is most sensitive to the change of third-party collectors’ service decision. When the recycling market is in chaos, it has a strong initial value sensitivity. In addition, we found that increase of consumers’ service sensitivity and service cost parameter had negative effect on stability of the recycling market; there is a reverse relationship between price adjustment parameters and the service adjustment parameter. With the increase of service adjustment parameter, the bifurcation point of the system will appear more quickly. Finally, chaotic market can be controlled by the feedback control method.

Cournot Duopoly Games: Models and Investigations

This paper analyzes Cournot duopoly games that are constructed based on Cobb–Douglas preferences. We introduce here two models whose dynamic adjustments depend on bounded rationality, dynamic adjustment, and tit-for-tat mechanism. In the first model, we have two firms with limited information and due to that they adopt the bounded rationality mechanism. They update their productions based on the changing occurred in the marginal profit. For this model, its fixed point is obtained and its stability condition is calculated. In addition, we provide conditions by which this fixed point loses its stability due to flip and Neimark–Sacker bifurcations. Furthermore, numerical simulation shows that this model possesses some chaotic behaviors which are recovered due to corridor stability. In the second model, we handle two different mechanisms of cooperation. These mechanisms are dynamic adjustment process and tit-for-tat strategy. The players who use the dynamic adjustment increase their productions based on the cooperative output while, in tit-for-tat mechanism, they increase the productions based on the cooperative profit. The local stability analysis shows that adopting tit-for-tat makes the model unstable and then the system becomes chaotic for any values of the system’s parameters. The obtained results show that the dynamic adjustment makes the system’s fixed point stable for a certain interval of the adjustment parameter.

Fast Video Dehazing Using Per-Pixel Minimum Adjustment

To reduce the computational complexity and maintain the effect of video dehazing, a fast and accurate video dehazing method is presented. The preliminary transmission map is estimated by the minimum channel of each pixel. An adjustment parameter is designed to fix the transmission map to reduce color distortion in the sky area. We propose a new quad-tree method to estimate the atmospheric light. In video dehazing stage, we keep the atmospheric light unchanged in the same scene by a simple but efficient parameter, which describes the similarity of the interframe image content. By using this method, unexpected flickers are effectively eliminated. Experiments results show that the proposed algorithm greatly improved the efficiency of video dehazing and avoided halos and block effect.

Biarc Approximations Tool-Path Generation for Polyhedral Models

An effective biarc approximate tool path generation algorithm is presented for polyhedral models. A series of sections intersect the offset surface of polyhedral models to obtain the initial tool paths. The path interval is calculated by the curvature radiuses and scallop height for offset surface models. Within the range of fitting precision, based on the biarc fitting constraint condition and adjustment parameter of curvature, iteration method is used to determine adjustment parameter of curvature radius. So the last radius for biarc is obtained for fitting the initial tool paths. Example shows the method can keep G1 biarc approximations tool path and fewer biarc segments, so the machining efficiency is improved.

The Skewboid Method: A Simple and Effective Approach to Pareto Relaxation and Filtering

The concept of Pareto optimality is the default method for pruning a large set of candidate solutions in a multi-objective problem to a manageable, balanced, and rational set of solutions. While the Pareto optimality approach is simple and sound, it may select too many or too few solutions for the decision-maker’s needs or the needs of optimization process (e.g. the number of survivors selected in a population-based optimization). This inability to achieve a target number of solutions to keep has caused a number of researchers to devise methods to either remove some of the non-dominated solutions via Pareto filtering or to retain some dominated solutions via Pareto relaxation. Both filtering and relaxation methods tend to introduce many new adjustment parameters that a decision-maker (DM) must specify. In the presented Skewboid method, only a single parameter is defined for both relaxing the Pareto optimality condition (values between −1 and 0) and filtering more solutions from the Pareto optimal set (values between 0 and 1). This parameter can be correlated with a desired number of solutions so that this number of solutions is input instead of an unintuitive adjustment parameter. A mathematically sound derivation of the Skewboid method is presented followed by illustrative examples of its use. The paper concludes with a discussion of the method in comparison to similar methods in the literature.