Search

This paper examines an observer-based backstepping terminal sliding mode controller (BTSMC) for 3 degrees of freedom overhead transmission line de-icing robot manipulator (OTDIRM). The control law for tracking of the OTDIRM is formulated by the combination of BTSMC and neural network (NN) based approximation. For the precise trajectory tracking performance and enhanced disturbance rejection, NN-based adaptive observer backstepping terminal sliding mode control (NNAOBTSMC) is developed. To obviate local minima problem, the weights of both NN observer and NN approximator are adjusted off-line using particle swarm optimization. The radial basis function neural network-based observer is used to estimate tracking position and velocity vectors of the OTDIRM. The stability of the proposed control methods is verified with the Lyapunov stability theorem. Finally, the robustness of the proposed NNAOBTSMC is checked against input disturbances and uncertainties. [ABSTRACT FROM AUTHOR]

Adaptive control methods are developed for stability and tracking control of flight systems in the presence of parametric uncertainties. This paper offers a design technique of adaptive sliding mode control (ASMC) for finite-time stabilization of unmanned aerial vehicle (UAV) systems with parametric uncertainties. Applying the Lyapunov stability concept and finite-time convergence idea, the recommended control method guarantees that the states of the quad-rotor UAV are converged to the origin with a finite-time convergence rate. Furthermore, an adaptive-tuning scheme is advised to guesstimate the unknown parameters of the quad-rotor UAV at any moment. Finally, simulation results are presented to exhibit the helpfulness of the offered technique compared to the previous methods. [ABSTRACT FROM AUTHOR]

We firstly investigate the fixed-time stability analysis of uncertain permanent magnet synchronous motors with novel control. Compared with finite-time stability where the convergence rate relies on the initial permanent magnet synchronous motors state, the settling time of fixed-time stability can be adjusted to desired values regardless of initial conditions. Novel adaptive stability control strategy for the permanent magnet synchronous motors is proposed, with which we can stabilize permanent magnet synchronous motors within fixed time based on the Lyapunov stability theory. Finally, some simulation and comparison results are given to illustrate the validity of the theoretical results. [ABSTRACT FROM AUTHOR]

Mobile wireless sensor networks (MWSNs) are wireless networks of small sensors moving around a certain coverage area relaying information among themselves and conveying their readings and data to base stations. Imposters are malicious nodes actively engaging other legitimate nodes in the network to read or inject wrong data. MWSN are susceptible to imposter attack and therefore, the protection of MWSN from imposter nodes placed by an adversary to contaminate the sensed data is essential for the reliability of its operation. Imposters detection algorithms need to be distributed in nature and therefore they are susceptible to variety of faults that can perturb the variables for algorithm and cause a major malfunction in the operation of the algorithm and subsequently the entire network if proper recovery mechanisms are not employed. The distributed nature of imposter detection schemes for WSN and the physical environment where the sensors are deployed require some approaches such as stabilization to deal with faults. A stabilizing distributed algorithm can withstand transient faults and start in an arbitrary initial configuration by eventually entering a legitimate system configuration regardless of the current system configuration. We view a fault as a transient fault if it affects the states of the system processes but not their program. In this paper, we propose an imposter detection scheme that can effectively deal with transient faults and arbitrary initialization. In addition, the proposed algorithm effectively adapts to the introduction and the removal of sensor nodes to/from the WSN which makes the proposed algorithm appropriate for practical sensor network applications. Other faults that can occur in the network and in the nodes are beyond the scope of this work. [ABSTRACT FROM AUTHOR]

A vehicle stability control approach for four-wheel independently actuated (FWIA) electric vehicles is presented. The proposed control method consists of a higher-level controller and a lower-level controller. An adaptive control-based higher-level controller is designed to yield the vehicle virtual control efforts to track the desired vehicle motions due to the possiblemodeling inaccuracies and parametric uncertainties. The lower-level controller considering tire force saturation is given to allocate the required control efforts to the four in-wheel motors for providing the desired tire forces. An analytic method is given to distribute the high-level control efforts, without using the numerical-optimization-based control allocation algorithms. Simulations based on a high-fidelity, CarSim, and full-vehicle model show the effectiveness of the control approach. [ABSTRACT FROM AUTHOR]

An incorrect inequality was applied in the proof of Theorem 2, in the above-mentioned paper. In this note, we correct the proof. The revised theorem requires bounded regressors. [ABSTRACT FROM AUTHOR]