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A robust self-organising fuzzy sliding mode control law steers autonomous underwater vehicles (AUVs) to track a predefined planar path at a constant speed without temporal specifications. An intelligent methodology has been adopted for path-following control to handle varying parametric uncertainties in vehicle dynamics and also conquers stringent preliminary condition constraints in several path-following control strategies illustrated in the literature. Robust controller design builds on a fusion of sliding mode control theory and fuzzy logic technique with an adaptation mechanism to tune boundary layer width and hitting gain. This novel strategy proposes two distinct tuning procedures: the first method commonly uses absolute error and their derivative as fuzzy input variables in a two-dimensional fuzzy logic rule structure. Herein, skew symmetry property is utilised in rule base structure to derive a single input fuzzy variable based on the signed distance technique, drastically reducing two-dimensional fuzzy logic rules. Since the second method provides substantial reductions in rule inferences through the use of the fuzzy rule's mirror image and the Lyapunov approach for tuning purposes, the resulting guidance control law yields fast convergence of the path-following error trajectory towards zero along with the elimination of chattering problem. Simulation results illustrate the effectiveness and robustness of the proposed control law to achieve favourable tracking performance with a high accuracy. [ABSTRACT FROM AUTHOR]

In this paper, a highly non-linear model with six degrees of freedom (DOF) is used for the manoeuvring and depth control of an autonomous underwater vehicle (AUV). A simplified scheme to design a conventional fuzzy logic controller known as robust Proportional Derivative (PD)-like Fuzzy Controller (PD-FZ) is designed separately for diving and steering subsystems of an AUV and then applied for combined steering, diving and speed control functions. Simulation results are shown by using the slender form of the Naval Post-Graduate School (NPS, Monterey, CA) AUV. Results of simulation studies using a nonlinearAUVdynamics are presented under the presence of any bounded ocean currents orwave disturbances and results show that proposed controller gives robust performance against these disturbances and modeling nonlinearity. Waypoint acquisition based on line of sight guidance is used to achieve path tracking. [ABSTRACT FROM AUTHOR]

Neurological disorders such as cerebral paralysis, spinal cord injuries, and strokes, result in the impairment of motor control and induce functional difficulties to human beings like walking, standing, etc. Physical injuries due to accidents and muscular weaknesses caused by aging affect people and can cause them to lose their ability to perform daily routine functions. In order to help people recover or improve their dysfunctional activities and quality of life after accidents or strokes, assistive devices like exoskeletons and orthoses are developed. Control strategies for control of exoskeletons are developed with the desired intention of improving the quality of treatment. Amongst recent control strategies used for rehabilitation robots, active disturbance rejection control (ADRC) strategy is a systematic way out from a robust control paradox with possibilities and promises. In this modern era, we always try to find the solution in order to have minimum resources and maximum output, and in robotics-control, to approach the same condition observer-based control strategies is an added advantage where it uses a state estimation method which reduces the requirement of sensors that is used for measuring every state. This paper introduces improved active disturbance rejection control (I-ADRC) controllers as a combination of linear extended state observer (LESO), tracking differentiator (TD), and nonlinear state error feedback (NLSEF). The proposed controllers were evaluated through simulation by investigating the sagittal plane gait trajectory tracking performance of two degrees of freedom, Lower Limb Robotic Rehabilitation Exoskeleton (LLRRE). This multiple input multiple output (MIMO) LLRRE has two joints, one at the hip and other at the knee. In the simulation study, the proposed controllers show reduced trajectory tracking error, elimination of random, constant, and harmonic disturbances, robustness against parameter variations, and under the influence of noise, with improvement in performance indices, indicates its enhanced tracking performance. These promising simulation results would be validated experimentally in the next phase of research.

Competing Interests: Conflicts of interest: There are no conflicts of interest for any of the authors.

In this paper, a robust nonlinear proportional-integral-derivative (PID)-like fuzzy control scheme is presented and applied to complex trajectory tracking control of a 2PRP-PPR (P-prismatic, R-revolute) planar parallel manipulator (motion platform) with three degrees-of-freedom (DOF) in the presence of parameter uncertainties and external disturbances. The proposed control law consists of mainly two parts: first part uses a feed forward term to enhance the control activity and estimated perturbed term to compensate for the unknown effects namely external disturbances and unmodeled dynamics, and the second part uses a PID-like fuzzy logic control as a feedback portion to enhance the overall closed-loop stability of the system. Experimental results are presented to show the effectiveness of the proposed control scheme., (Copyright © 2016 ISA. Published by Elsevier Ltd. All rights reserved.)