This paper proposes a robust model predictive control (MPC) scheme to asymptotically stabilize an uncertain linear plant with polytopic model uncertainty description. Quadratic robust stability constraints are explicitly imposed as contractive constraints on the predicted state at each sampling time. The feasibility of these constraints can be detected either off-line or at the first step of on-line optimization. The feasibility is independent of the selection of the optimization objective function and its parameters. Therefore, the objective function can be formulated to satisfy other criterion such as the performance requirements. The simulation study shows the effectiveness and features of the proposed method.
TEB (Timed Elastic Band) can efficiently generates optimal trajectories that match the motion characteristics of car-like robots. However, the quality of the generated trajectories is often unstable, and they sometimes violate boundary conditions. Therefore, this paper proposes a fuzzy logic control-TEB algorithm (FLC-TEB). This method adds smoothness and jerk objectives to make the trajectory generated by TEB smoother and the control more stable. Building on this, a fuzzy controller is proposed based on the kinematic constraints of car-like robots. It uses the narrowness and complexity of trajectory turns as inputs to dynamically adjust the weights of TEB's internal objectives. The results of real car-like robot tests show that compared to the classical TEB, FLC-TEB increased trajectory time by 16% but reduced trajectory length by 16%; The trajectory smoothness was significantly improved, the change in the turning angle on the trajectory was reduced by 39%, the smoothness of the linear velocity increased by 71%, and the smoothness of the angular velocity increased by 38%, with no reverse movement occurring. This indicates that when planning trajectories for car-like mobile robots, FLC-TEB provides more stable and smoother trajectories compared to the classical TEB.
A robust model predictive control (MPC) scheme based on output feedback is presented in this paper. A state estimator is incorporated in the MPC formulation to reflect the fact that the process output instead of state information is available. This approach is shown to asymptotically stabilize an uncertain linear plant with polytopic model uncertainty description. Linear matrix inequality (LMI) robust stability criteria are explicitly imposed in on-line computation as contractive constraints on the estimated state variables. The feasibility of these constraints can be detected either off-line or at the first step of on-line optimization. Comparing to other existing robust MPC formulations, the feasibility is independent of the selection of the optimization objective function and its parameters. Therefore, the objective function can be formulated based on other criteria such as performance requirements. The simulation study shows the effectiveness of this proposed method
The difficulty of tracing the process of planting, processing, quality inspection, storage, transportation and sales of precious Chinese herbal medicines can be well solved by using the blockchain that is characterized by decentralization, tamper resistance and distributed storage. In this paper, we discuss how to design a traceability system for rare Chinese herbal medicine with double-chain structure by using the high efficiency of private blockchain and the extensibility of consortium blockchain to store the detailed information of each process in the interplanetary file system (IPFS), store the Hash value of each production process traceability information in the private blockchain, and record the transaction identification ID in the private blockchain in the previous stage in the traceability information in the next stage, so that consumers can get the complete traceability information of rare Chinese herbal medicines by combining the traceability information of the sales stage with the IPFS. By linking the Hash value of the traceability information of the final sales stage to the consortium blockchain as a transaction, the safety and reliability of the scheme are enhanced. The private blockchain is used to collect and track the traceability information, while the consortium blockchain is to tamper with and verify the traceability information.
Maintaining global dynamic routing in large-scale wireless network requires lots of overhead due to the mobility of nodes, thus the hierarchical network structure is widely used in reality.Therefore, this paper proposes a modified local community detection algorithm in large scale wireless network scenario to enhance the network self-organization.In this paper, we first describe the scenario of large-scale wireless network communication.Then the algorithm of local community detection is adopted to cluster the nodes that communicate with others more frequently into a community.Finally the local community detection algorithm is modified with a selection factor.The simulation results show that the new algorithm has higher detection accuracy than classic local community detection algorithms.
Consensus of fractional-order singular multiagent systems is considered in this article. The model of uncertain systems with actuator fault is established, and its admissible consensus in the field of fractional-order systems is studied. First, the uncertain singular multiagent systems with actuator fault are proposed. Then, a state feedback controller and a state consensus protocol with an observer based on output information are designed. Then, new consensus criteria of uncertain fractional-order singular multiagent systems are proposed. Finally, for the sake of demonstrating the validity of proposed results, some relevant numerical examples are provided.
TEB (timed elastic band) can efficiently generate optimal trajectories that match the motion characteristics of car-like robots. However, the quality of the generated trajectories is often unstable, and they sometimes violate boundary conditions. Therefore, this paper proposes a fuzzy logic control–TEB algorithm (FLC-TEB). This method adds smoothness and jerk objectives to make the trajectory generated by TEB smoother and the control more stable. Building on this, a fuzzy controller is proposed based on the kinematic constraints of car-like robots. It uses the narrowness and turning complexity of the trajectory as inputs to dynamically adjust the weights of TEB’s internal objectives to obtain stable and high-quality trajectories in different environments. The results of real car-like robot tests show that compared to the classical TEB, FLC-TEB increased the trajectory time by 16% but reduced the trajectory length by 16%. The trajectory smoothness was significantly improved, the change in the turning angle on the trajectory was reduced by 39%, the smoothness of the linear velocity increased by 71%, and the smoothness of the angular velocity increased by 38%, with no reverse movement occurring. This indicates that when planning trajectories for car-like mobile robots, while FLC-TEB slightly increases the total trajectory time, it provides more stable, smoother, and shorter trajectories compared to the classical TEB.
In this paper, a simple and effective stabilization method for a class of systems with time delay controlled by PD μ controllers is presented. Based on D-decomposition method, the explicit formulae corresponding to Real Root Boundary(RRB) and Complex Root Boundary(CRB) are derived in terms of the PD μ controller parameters. The stability region of the control system is determined by the implicit function theorem. The set of stability regions in (kd, kp)-plane when 11 equals to different values in (0, 2) can be obtained. To verify the accuracy of the proposed method, two examples are given. The simulations verify that the fractional order PD μ controllers can provide larger stability regions, which is beneficial for designing the controller.
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