115 research outputs found

    Active noise and vibration controlโ€“Part I

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    Real-time embedded system of super twisting-based integral sliding mode control for quadcopter UAV

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    This paper presents the development of set-point weighting-based integral super-twisting sliding mode control (SISTASMC) with full-order state observers to overcome the control challenges encountered with nonlinear and underactuated systems. Quadcopter UAV form is a good example of underactuated systems, and this is selected in this research for validating the developed control. A comparative assessment through experimental validation is conducted between SISTASMC and Set-point weighting-based Integral Sliding Mode Control to demonstrate the performance of both controllers. Based on predetermined performance criteria, the results obtained demonstrate good performance of SISTASMC in dealing with uncertainty

    A modified bats echolocation-based algorithm for solving constrained optimisation problems

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    A modified adaptive bats sonar algorithm (MABSA) is presented that utilises the concept of echolocation of a colony of bats to find prey. The proposed algorithm is applied to solve the constrained optimisation problems coupled with penalty function method as constraint handling technique. The performance of the algorithm is verified through rigorous tests with four constrained optimisation benchmark test functions. The acquired results show that the proposed algorithm performs better to find optimum solution in terms of accuracy and convergence speed. The statistical results of MABSA to solve all the test functions also has been compared with the results from several existing algorithms taken from literature on similar test functions. The comparative study has shown that MABSA outperforms other establish algorithms, and thus, it can be an efficient alternative method in the solving constrained optimisation problems

    Protective effects of vitamins/antioxidants on occupational noise induced hearing loss: A systematic review

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    Objectives: Occupational noise-induced hearing loss (NIHL) due to industrial, military, and other job related noise exposure can cause harmful health issues to occupied workers, but may also be potentially preventable. Vitamins/antioxidant have been studied as therapeutic strategies to prevent and/or delay the risks of human diseases as well as NIHL. So, this study was conducted to systematically review the protective effects of vitamins/ antioxidants on occupational noise induced hearing loss. Methods: Online databases including PubMed/Medline, Scopus, Web of Science, EMBASE, Science Direct, and Google Scholar were systematically searched up to 12.January 2021. Based on 6336 potentially relevant records identified through the initial search in the databases, twelve full-text publications were retrieved, one of which can be viewed as two separate trials, because it has studied the effects of two different antioxidants (Ginseng and NAC) on NIHL, separately. Results: A review of the studies show that vitamin B12, folic acid, and N-acetylcysteine (NAC) have a considerable protective effect on NIHL. However, these protective effects are not yet specified in different frequencies. The findings regarding the protective effects of other antioxidants are inconsistent in this field. Conclusion: Vitamin B12, folic acid, and NAC may have a protective effect as an antioxidant on reducing occupational hearing loss. For a conclusive evidence of vitamins/antioxidants protective therapies, future studies with precise criteria for noise exposure and similar outcome parameters are required

    Hybrid iterative learning control of a flexible manipulator

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    This paper presents an investigation into the development of a hybrid control scheme with iterative learning for input tracking and end-point vibration suppression of a flexible manipulator system. The dynamic model of the system is derived using the finite element method. Initially, a collocated proportional-derivative (PD) controller using hub angle and hub velocity feedback is developed for control of rigid-body motion of the system. This is then extended to incorporate a non-collocated proportional-integral-derivative (PID) controller with iterative learning for control of vibration of the system. Simulation results of the response of the manipulator with the controllers are presented in the time and frequency domains. The performance of the hybrid iterative learning control scheme is assessed in terms of input tracking and level of vibration reduction in comparison to a conventionally designed PD-PID control scheme. The effectiveness of the control scheme in handling various payloads is also studied

    Multi-Objective Genetic Algorithm Optimisation Approach for the Geometrical Design of an Active Noise Control Systems

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    This paper focuses on the geometrical design of active noise control (ANC) in free- field propagation medium. The development and performance assessment uses genetic optimisation techniques to arrange system components so as to satisfy several performance requirements, such as physical extent of cancellation, controller design restriction and system stability. The ANC system design can be effectively addressed if it is considered as multi – objective optimisation problems. The multi-objective genetic algorithms (MOGAs) are well suited to the design of an ANC system and the approach used for it is based on a multi - objective method, with which the physical extent of cancellation and relative stability assessment are dealt with simultaneously

    Forward and backward motion control of wheelchair on two wheels

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    The challenge in designing wheelchair on two wheels involves the design and implementation of suitable control strategies for a two wheeled wheelchair to perform comparably similar to a normal four wheeled wheelchair. It is important to note that a wheelchair on two wheels is expected not to take much space during mobility as compared to when it is on four wheels. Moreover, disabled people are encouraged and expected to perform most activities that others can do and hence lead an independent life. Thus, wheelchairs on two wheels are needed for disabled persons to perform some of the essential tasks in their living and work environments. In this research a model of the standard wheelchair is developed as a test and verification platform using Visual Nastran software. Novel fuzzy logic control strategies are designed for lifting up the chair transforming a four-wheeled wheelchair to a two-wheeled wheelchair) and maintaining stability and balance while on two wheels. Furthermore, position control for forward and backward mobility of the wheelchair on two wheels is developed using fuzzy logic control. Simulation results of the proposed control strategy are presented and discussed

    Modelling and control of a wheelchair on two wheels

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    Wheelchairs on two wheels are needed for disabled persons to perform some of the essential tasks in their living and work environments. In fact it offers great advantages and efficiency for the user. Besides allowing a disabled to lead independent life, it is expected not to take much space during mobility as compared to when it is on four wheels and thus a wheelchair on two wheels has associated design and development challenges. These include modelling and controller design for the system to perform comparably similar to normal four-wheeled wheelchair. In this paper physical model of a wheelchair on two wheels that mimics double inverted pendulum is designed and a novel fuzzy logic control mechanism is developed and tested with control of the two-wheeled wheelchair

    Genetic Algorithms Based Approach for Designing Spring Brake Orthosis โ€“ Part Ii: Control of FES Induced Movement

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    Spring brake orthotic swing phase for paraplegic gait is initiated through releasing the brake on the knee mounted with a torsion spring. The stored potential energy in the spring, gained from the previous swing phase, is solely responsible for swing phase knee flexion. Hence the later part of the SBO operation, functional electrical stimulation (FES) assisted extension movement of the knee has to serve an additional purpose of restoring the spring potential energy on the fly. While control of FES induced movement as such is often a challenging task, a torsion spring, being antagonistically paired up with the muscle actuator, as in spring brake orthosis (SBO), only adds to the challenge. Two new schemes are proposed for the control of FES induced knee extension movement in SBO assisted swing phase. Even though the control schemes are closed-loop in nature, special attention is paid to accommodate the natural dynamics of the mechanical combination being controlled (the leg segment) as a major role playing feature. The schemes are thus found to be immune from some drawbacks associated with both closed-loop tracking as well as open-loop control of FES induced movement. A leg model including the FES knee joint model of the knee extensor muscle vasti along with the passive properties is used in the simulation. The optimized parameters for the SBO spring are obtained from the earlier part of this work. Genetic algorithm (GA) and multi-objective GA (MOGA) are used to optimize the parameters associated with the control schemes with minimum fatigue as one of the control objectives. The control schemes are evaluated in terms of three criteria based on their ability to cope with muscle fatigue

    ANFIS modelling of a twin rotor system using particle swarm optimisation and RLS

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    Artificial intelligence techniques, such as neural networks and fuzzy logic have shown promising results for modelling of nonlinear systems whilst traditional approaches are rather insufficient due to difficulty in modelling of highly nonlinear components in the system. A laboratory set-up that resembles the behaviour of a helicopter, namely twin rotor multiinput multi-output system (TRMS) is used as an experimental rig in this research. An adaptive neuro-fuzzy inference system (ANFIS) tuned by particle swarm optimization (PSO) algorithm is developed in search for non-parametric model for the TRMS. The antecedent parameters of the ANFIS are optimized by a PSO algorithm and the consequent parameters are updated using recursive least squares (RLS). The results show that the proposed technique has better convergence and better performance in modeling of a nonlinear process. The identified model is justified and validated in both time domain and frequency domai
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