Modelling of a Flexible Manoeuvring System Using ANFIS Techniques

The increased utilization of flexible structure systems, such as flexible manipulators and flexible aircraft in various applications, has been motivated by the requirements of industrial automation in recent years. Robust optimal control of flexible structures with active feedback techniques requires accurate models of the base structure, and knowledge of uncertainties of these models. Such information may not be easy to acquire for certain systems. An adaptive Neuro-Fuzzy inference Systems (ANFIS) use the learning ability of neural networks to adjust the membership function parameters in a fuzzy inference system. Hence, modelling using ANFIS is preferred in such applications. This paper discusses modelling of a nonlinear flexible system namely a twin rotor multi-input multi-output system using ANFIS techniques. Pitch and yaw motions are modelled and tested by model validation techniques. The obtained results indicate that ANFIS modelling is powerful to facilitate modelling of complex systems associated with nonlinearity and uncertainty

Design of Active Noise Control Systems with Compact and Distributed Sources.

A coherent method of design of active noise control systems for compact and distributed sources of noise in a three- dimensional non-dispersive propagation medium is presented. An analysis of single-input single-output, single-input multi-output and multi-input multi-output control structures is provided. Conditions for the robust operation of such systems on the basis of optimum cancellation, in relation to controller design, are determined. These conditions are interpreted as constraints on the geometric compositions of the system

Hybrid spiral-bacterial foraging algorithm for a fuzzy control design of a flexible manipulator

A novel hybrid strategy combining a spiral dynamic algorithm (SDA) and a bacterial foraging algorithm (BFA) is presented in this article. A spiral model is incorporated into the chemotaxis of the BFA algorithm to enhance the capability of exploration and exploitation phases of both SDA and BFA with the aim to improve the fitness accuracy for the SDA and the convergence speed as well as the fitness accuracy for BFA. The proposed algorithm is tested with the Congress on Evolutionary Computation 2013 (CEC2013) benchmark functions, and its performance in terms of accuracy is compared with its predecessor algorithms. Consequently, for solving a complex engineering problem, the proposed algorithm is employed to obtain and optimise the fuzzy logic control parameters for the hub angle tracking of a flexible manipulator system. Analysis of the performance test with the benchmark functions shows that the proposed algorithm outperforms its predecessor algorithms with significant improvements and has a competitive performance compared to other well-known algorithms. In the context of solving a real-world problem, it is shown that the proposed algorithm achieves a faster convergence speed and a more accurate solution. Moreover, the time-domain response of the hub angle shows that the controller optimised by the proposed algorithm tracks the desired system response very well

Modelling of extended de-weight fuzzy control for an upper-limb exoskeleton

Performing heavy physical tasks, overhead work and long working hours are some examples of activities that can lead to musculoskeletal problems in humans. To overcome this issue, automated robots such as the upper-limb exoskeleton is used to assist humans while performing tasks. However, several concerns in developing the exoskeleton have been raised such as the control strategies used. In this study, a control strategy known as the extended de-weight fuzz was proposed to ensure that the exoskeleton could be maneuvered to the desired position with the least number of errors and minimum torque requirement. The extended de-weight fuzzy is a combination of the fuzzy-based PD and fuzzy-based de-weight controller systems. The extended de-weight fuzzy was then compared with the fuzzy-based PD and PID controllers, and the performances of these controllers were compared in terms of their deviations and required torques to perform tasks. The findings show that the proposed control strategy performs better than the fuzzy-based PD and PID controller systems

A compact laser shearography system for on-site robotic inspection of wind turbine blades

Shearography is an optical technique in the field of non-destructive evaluation (NDE) of various materials. Its main advantages are that it is non-contact type and can cover a large area in a single inspection. As a result, although it has been widely acknowledged as an effective technique particularly for NDE of composite materials to detect subsurface defects such as delamination, disbond, cracks and impact damages, the use of shearography for on-site inspection of wind turbine blades (WTBs) has not been reported. This is due to wind causing structural vibration in the WTB. The solution in this paper is to make the shearography sit on the WTB during inspection when the WTB is parked, so that the relative motion between the shearography and the WTB is minimized within the tolerance of the shearography system. The ultimate goal of the solution is to enable a robot assisted shearography system to inspect the WTB on-site. This paper presents the research work on a new shearography design for integration with a robotic climber for on-site WTB inspection. The approach is tested and evaluated in experimental settings, and comparative assessment of the approach with other robotic NDE techniques is carried out. The results demonstrate the potential benefits and suitability of the approach for on-site robotic inspection of WTBs

An improved neuroendocrine–proportional–integral–derivative controller with sigmoid-based secretion rate for nonlinear multi-input–multi-output crane systems

This paper proposes an improved neuroendocrine–proportional–integral–derivative controller for nonlinear multi-input–multi-output crane systems using a sigmoid-based secretion rate of the hormone regulation. The main advantage of the sigmoid-based secretion rate neuroendocrine–proportional–integral–derivative is that the hormone secretion rate of neuroendocrine–proportional–integral–derivative can be varied according to the change of error. As a result, it can provide high accuracy control performance, especially in nonlinear multi-input–multi-output crane systems. In particular, the hormone secretion rate is designed to adapt with the changes of error using a sigmoid function, thus contributing to enhanced control accuracy. The parameters of the sigmoid-based secretion rate neuroendocrine–proportional–integral–derivative controller are tuned using the safe experimentation dynamics algorithm. The performance of the proposed sigmoid-based secretion rate neuroendocrine–proportional–integral–derivative controller-based safe experimentation dynamics algorithm is evaluated by tracking the error and the control input. In addition, the performances of proportional–integral–derivative and neuroendocrine–proportional–integral–derivative controllers are compared with the proposed sigmoid-based secretion rate neuroendocrine–proportional–integral–derivative performance. From the simulation work, it is discovered that the sigmoid-based secretion rate neuroendocrine–proportional–integral–derivative design provides better control performances in terms of the objective function, the total norm of error and the total norm of input compared to proportional–integral–derivative and neuroendocrine–proportional–integral–derivative controllers. In particular, it is shown the proposed sigmoid-based secretion rate neuroendocrine–proportional–integral–derivative controller contributes 5.12% of control accuracy improvement by changing the fixed hormone secretion rate into a variable hormone secretion rate based on the change of error

Adaptive Active Control of Noise and Vibration

The design implementation of an active control mechanism for noise cancellation vibration suppression within an adaptive control framework is presented. A control mechanism is designed within a feedforward control structure on the basis of optimum cancellation at an observation point. The design relations are formulated such that to allow on-line design and implementation and thus result in a self-tuning control algorithm. The algorithm is implemented on an integrated digital signal processing and transputer system and results verifying the performance of the algorithm are presented and discussed

Modeling and control of a novel FES driven assisted cycling mechanism

Functional Electrical Stimulation (FES) driven cycling using single muscle group, the quadriceps, is achieved using PID controller with a novel assisting mechanism represented by a flywheel with an electrical clutch. This mechanism is useful for disabled individuals whose muscles are weak and unable to push a fix-geared flywheel. The flywheel is engaged and disengaged by the clutch when necessary to assist or retard the cycling without imposing additional load on the person's leg muscle. A comparison between this new mechanism and a previously proposed method show positive results of the new mechanism towards reducing the number of muscle stimulation which leads to delay muscle fatigue and consequently promoting prolonged FES driven cycling for paralyzed people

Self-Tuning Active Vibration Control of Flexible Beam Structures

This paper presents the design and performance evaluation of an adaptive active control mechanism for vibration suppression in flexible beam structures. A cantilever beam system in transverse vibration is considered. First order control finite difference methods are used to study the behaviour of the beam and develop a suitable test and verification platform. An active vibration control algorithm is developed within an adaptive control framework for broadband cancellation of vibration along the beam using a single-input multi-output (SIMO) control structure. The algorithm is implemented on a digital processor incorporating a digital signal processing (DSP) and transputer system. Simulation results verifying the performance of the algorithm in the suppression of vibration along the beam, using single-input single-output and SIMO control structures are presented and discussed

CISC, Risc and DSP Processors in Real-Time Signal Processing and Control

This paper presents an investigation into the nature of advanced high performance complex instruction set computer (CISC) processors, reduced instruction set computer (RISC) processors and digital signal processing (DSP) devices. Several DSP and control algorithms of regular and irregular nature are considered to explore the real-time characteristics of the different processors. The algorithms are implemented on several CISC, RISC and DSP processors. The hardware and software resources and capabilities of the processors and the characteristics of the algorithms are discussed to provide a matching between the algorithms and the architectures. Finally, a comparison of the results of the implementations is made, on the basis of real-time computation performance, to lead to merits of development of fast processing techniques for real-time DSP and control applications