Adaptive active control of noise and vibration

This paper presents the development of a unified approach to active control of noise and vibration. The design of an active control system is initially considered on the basis of a single-input single-output (SISO) structure. The design procedure is formulated so as to allow on-line adaptation and control, and accordingly an adaptive control algorithm is devised. The design is then extended to the case of a single-input multi-output (SIMO) control structure. The control strategies thus devised are verified in the cancellation of broadband noise in a free-field medium, and in vibration suppression in a cantilever beam in fixed-free and fixed-fixed modes. A comparative assessment of the results with SISO and SIMO control structures is presented and discussed

Mobile robotics moves forward on standardisation

Over the last decade considerable effort has gone into developing generic or application-specific approaches for characterisation, control and design of mobile robotic systems. The research efforts have accordingly concentrated on locomotion techniques and component-level and system architectures with conventional and new approaches. While conventional approaches allow the system to perform to some degree of satisfaction, they are best suited for relatively simple systems and applications where performance demands are not high. With complex systems and where performance demands are high, researchers have investigated the development of new and novel approaches taking account of accuracy requirements, computational efficiency and practical realisation. Such efforts have opened up a whole range of application areas for mobile robotics in industry, public and domestic sectors. The time has now come that robots are making their way out of the factory environment and benefiting the public and domestic sectors of society

System identification of a twin rotor multi-input multi-output system using adaptive filters with pseudo random binary input

This paper presents an investigation into the development of a parametric model of pitch movement of a twin rotor multi-input multi-output system (TRMS) using adaptive finite impulse response (FIR) models. The TRMS is a laboratory platform designed for control experiments. In certain aspects, its behaviour resembles that of a helicopter. It typifies a high-order nonlinear system with significant cross coupling between its two channels. The system is initially excited with PRBS signals of different bandwidths to ensure that all resonance modes are captured. The PRBS magnitude is selected so that it does not drive the system out of its linear operating range. Then, an adaptive FIR filter structure with LMS, NLMS, and genetic algorithm (GA) with LMS algorithms is investigated to identify the system and extract its parametric model. Effects of filter taps, step-size and system convergence are also studied. Performances of the employed techniques are assessed and presented in time and frequency domains

GA-based neural fuzzy control of flexible-link manipulators

The limitations of conventional model-based control mechanisms for flexible manipulator systems have stimulated the development of intelligent control mechanisms incorporating fuzzy logic and neural networks. Problems have been encountered in applying the traditional PD-, PI-, and PID-type fuzzy controllers to flexible-link manipulators. A PD-PI-type fuzzy controller has been developed where the membership functions are adjusted by tuning the scaling factors using a neural network. Such a network needs a sufficient number of neurons in the hidden layer to approximate the nonlinearity of the system. A simple realisable network is desirable and hence a single neuron network with a nonlinear activation function is used. It has been demonstrated that the sigmoidal function and its shape can represent the nonlinearity of the system. A genetic algorithm is used to learn the weights, biases and shape of the sigmoidal function of the neural network

Vibration control of pitch movement using command shaping techniques– Experimental investigation

This paper investigates the development of feedforward control strategies for vibration control of pitch movement (1 DOF) of a twin rotor multi-input multi-output system (TRMS) using command shaping techniques. Command shaping is a feedforward method used to reduce residual vibrations during motion in flexible systems. The TRMS is a laboratory platform designed for control experiments. In certain aspects, its behaviour resembles that of a helicopter. Feedforward controllers are designed for resonance suppression produced by the main rotor, which produces pitch movement around the longitudinal axis, while the lateral axis (yaw movement) is physically constrained. Three feed-forward controllers: input-shaper, low-pass filter and band-stop filter are designed based on the natural frequencies and damping ratios of the system. The three controllers are assessed in terms of level of vibration reduction at the system’s natural frequencies. Their performances are compared with an unshaped input (single-switch bang-bang signal) that is used to determine the dynamic response of the system

Active noise and vibration control–Part II

Editoria

Modelling and control of a water-based system of multiple mobile robots for unmanned rescue

With the technique from applied engineering and the advent of wireless communication, the nature of rescuing the victims has changed in developing countries where major means of transportation and communication are through rivers using marine vessels/crafts. This paper presents the modelling and control of a water-based system of Multiple Mobile Robots (MMR) for unmanned rescue based on laser optics. The major components of the system prototype are shown unit-wise in a framework. The move-ability and inter-relationships of the MMR are examined along with the use of electronic devices/components described. Performance of the system is discussed, and comparative assessments of the proposed system with other systems are presented in this paper

Dynamic modelling of a single-link flexible manipulator: Parametric and non-parametric approaches

This paper presents an investigation into the development of parametric and non-parametric approaches for dynamic modelling of a flexible manipulator system. The least mean squares, recursive least squares and genetic algorithms are used to obtain linear parametric models of the system. Moreover, non-parametric models of the system are developed using a non-linear AutoRegressive process with eXogeneous input model structure with multi-layered perceptron and radial basis function neural networks. The system is in each case modelled from the input torque to hub-angle, hub-velocity and end-point acceleration outputs. The models are validated using several validation tests. Finally, a comparative assessment of the approaches used is presented and discussed in terms of accuracy, efficiency and estimation of the vibration modes of the system

Modelling, simulation and proportional integral control of a pneumatic motor

Researchers have shown a considerable amount of interest in the control of pneumatic drives over the past decade, for two main reasons, firstly, the response of the system is very slow and it is difficult to attain set points due to hysteresis and secondly, the dynamic model of the system is highly non-linear, which greatly complicates controller design and development. To address these problems, two streams of research effort have evolved and these are: (i) using conventional methods to develop a modelling and control strategy, (ii) adopting a strategy that does not require mathematical model of the system. This paper presents an investigation into the modelling and control of an air motor incorporating a pneumatic equivalent of the electric H-bridge. The pneumatic H-bridge has been devised for speed and direction control of the motor. The system characteristics are divided into three regions, namely low speed, medium speed and high speed. The system is highly nonlinear in the low speed region, for which neuro-modelling, simulation and control strategies are developed

Design and parametric investigations of permanent magnet adhesion mechanism for robots climbing on reinforced concrete walls

Wall Climbing Robots (WCRs) have found extensive applications in the past decade in numerous engineering fields, however, the design of efficient adhesion mechanism for robots climbing on concrete surfaces remains a challenge and attracts research attention. This paper proposes various designs of magnetic adhesion mechanism for concrete surfaces and investigates the adhesion force and payload capacities each design would accommodate for wall climbing robot applications. Permanent magnet is used as the magnetic adhesion mechanism and a yoke structure helps in holding the magnets and influences the adhesion characteristics of the mechanism. The effect of various structural designs of adhesion mechanisms on the adhesion force and payload capacity on the concrete surface is studied in this work. The adhesion forces against the different standoff distances which comprise the gap between the magnet and the concrete surface are also investigated therein. The results show that the developed adhesion mechanism can be applied for concrete walls generating the required adhesion forces and providing a better insight in choosing the best configuration, number of magnets and standoff distances for the design of adhesion mechanism against the required payload of WCR