Practical time-varying formation tracking problems for second-order nonlinear multiagent systems with multiple leaders are investigated using adaptive neural networks (NNs), where the time-varying formation tracking error caused by time-varying external disturbances can be arbitrarily small. Different from the previous work, there exists a predefined time-varying formation formed by the states of the followers and the formation tracks the convex combination of the states of the leaders with unknown control inputs. Besides, the dynamics of each agent has both matched/mismatched heterogeneous nonlinearities and disturbances simultaneously. First, a practical time-varying formation tracking protocol using adaptive NNs is proposed, which is constructed using only local neighboring information. The proposed control protocol can process not only the matched/mismatched heterogeneous nonlinearities and disturbances, but also the unknown control inputs of the leaders. Second, an algorithm with three steps is introduced to design the practical formation tracking protocol, where the parameters of the protocol are determined, and the practical time-varying formation tracking feasibility condition is given. Third, the stability of the closed-loop multiagent system is proven by using the Lyapunov theory. Finally, a simulation example is showed to illustrate the effectiveness of the obtained theoretical results.

Practical Time-Varying Formation Tracking for Second-Order Nonlinear Multiagent Systems With Multiple Leaders Using Adaptive Neural Networks

This paper proposes a voltage control strategy for islanded operation of dispatchable electronically coupled distributed energy resource (DER) systems, for remote (off grid) electrification systems. The proposed control strategy is based on fractional-order sliding-mode control, offers black-start functionality, maintains the quality of the output voltage of the host DER system in spite of unbalanced and/or distorted load currents, and ensures protection of the power-electronic interface to external faults. Moreover, the fractional derivative order of the controller can be used as an additional tuning parameter. Performance of the proposed control strategy is demonstrated through time-domain simulation of single- and multi-DER islanded networks, starting from black-start and subjected to various operating scenario, and it is also compared to the performance of a proportional-integral (PI)-based control strategy.

Fractional-Order Sliding-Mode Control of Islanded Distributed Energy Resource Systems

Application of wave-variable control to bilateral teleoperation systems: A survey

Development and validation of a surgical training simulator with haptic feedback for learning bone-sawing skill

Formation control and coordination of multiple unmanned ground vehicles in normal and faulty situations: A review

The control performance of sensorless vector-controlled induction motors mainly relies on the accurate flux estimation. However, due to the variations of electrical parameters, the inaccuracy of estimated fluxes will cause the performance degradation of speed control. In this paper, a fractional-order integral sliding-mode flux observer is provided to estimate the d- and q-axis fluxes in the stationary reference frame. In addition to simulations, a DSP/FPGA based experimental platform is setup to evaluate the feasibility of the proposed scheme. Simulations and experimental results illustrate that the performance of flux and speed tracking can be performed as desire by utilizing the fractional-order integral sliding-mode flux observer in a wide speed range.

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Fractional-order integral sliding-mode flux observer for sensorless vector-controlled induction motors

This paper presents a new robust adaptive control method for multi-robot systems, where the kinematic model of a differentially driven wheeled mobile robot is considered. Particularly, the situations involving partial loss of actuator effectiveness are addressed. Distributed controllers are derived based on dynamic surface control techniques over networked multiple robots. In addition, adaptive mechanisms are applied to estimate the bounds of effectiveness factor and uncertainty bounds. The robust stability of the multi-robot systems are preserved by using the Lyapunov theorem. The proposed controller can make the robots reach a desired formation following a designate trajectory. Simulation results indicate that the proposed control scheme has superior responses compared to conventional dynamic surface control.

Adaptive dynamic surface control for fault-tolerant multi-robot systems

This paper presents an adaptive distributed fault-tolerant formation control for multi-robot systems. Both the kinematics and dynamics of differential wheeled mobile robots are considered. In particular, the problem caused by actuator faults is investigated. Based on dynamic surface control techniques, adaptive formation controllers can be obtained under a directed communication network. The closed-loop stability is guaranteed by using Lyapunov stability analysis such that all followers can exponentially converge to a leader-follower formation pattern. Simulation and experimental results illustrate that the desired formation pattern can be preserved for a group of wheeled robots subject to unknown uncertainties and actuator faults.

Adaptive Distributed Fault-tolerant Formation Control for Multi-robot Systems under Partial Loss of Actuator Effectiveness

In order to develop a virtual surgery training platform with a force feedback function so as to facilitate the training of new medical personnel, this study first had to establish a virtual environment, and then implement interactions involving vision and tactile sensations. The system's augmented reality function modules include the establishment of an augmented reality environmental space, image loading and model establishment, and force feedback modules, as well as the required design for collision detection, object parameter settings, and controller functions. Apart from combining a virtual environment with force feedback and establishing diverse force feedback modules, this project also overcomes the single-point sensor restriction of most force feedback hardware, and establishes a tactile cutting function. In addition to the establishment of force feedback modules, the project further employs the conservation of energy principle in the design of the energy estimator and controller, and completes the design of a stable virtual surgery training platform.

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Development of an Augmented Reality Force Feedback Virtual Surgery Training Platform

A fuzzy sliding-mode consensus control is investigated for multi-agent systems in this paper. The consensus problem is discussed for networks of dynamic agents with external disturbances and model uncertainty. To deal with the consensus problems of the multi-agent system, a novel consensus algorithm combining the concepts of graph theory and fuzzy sliding-model control is proposed. According to the communication topology, the consensus stability conditions can be determined so that the fuzzy sliding-mode consensus controller (FSMCC) can be derived. Simulation results are provided to illustrate the effectiveness of the provided control scheme. Compared to the conventional consensus algorithms, the simulation results empirically support the promising performance of desire.

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Yeong-Hwa Chang

Papers

Fractional-order integral sliding-mode flux observer for sensorless vector-controlled induction motors

Adaptive dynamic surface control for fault-tolerant multi-robot systems

Adaptive Distributed Fault-tolerant Formation Control for Multi-robot Systems under Partial Loss of Actuator Effectiveness

Development of an Augmented Reality Force Feedback Virtual Surgery Training Platform

Fuzzy sliding-mode consensus control for multi-agent systems