Repetitive, or multipass, processes are a class of 2D systems of both practical and algorithmic/theoretical interest whose dynamics cannot be analysed or controlled using standard (1D) systems theory. Recently it has ...
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Repetitive, or multipass, processes are a class of 2D systems of both practical and algorithmic/theoretical interest whose dynamics cannot be analysed or controlled using standard (1D) systems theory. Recently it has been shown that the modelling of the boundary conditions, also known as the process initial conditions, is a crucial feature in the analysis and control of these processes. This paper presents some further results on the effects of so-called 'dynamic' process initial conditions on the controllability and stability properties of discrete linear repetitive processes. Previous work has shown that these dynamic process initial conditions alone can destroy the stability properties of these processes. Hence their effects must be 'adequately' accounted for the process modelling stage in order to ensure that subsequent analysis does not lead to incorrect results/conclusions. The main results developed in this paper can be summarised as follows. (i) Computationally efficient stability tests which can, in effect, be applied using standard, or 1D, linear systems tests. (ii) Characterisation of so-called pass controllability in the form of matrix rank based conditions. (iii) Conditions under which the dynamic process initial conditions can be selected to ensure stability and pass controllability.
Thruster propulsion is a significant component for making accurate motion control possible as well as achieving superior navigational performance of remotely operated vehicles (ROV), both for tethered and untethered c...
Thruster propulsion is a significant component for making accurate motion control possible as well as achieving superior navigational performance of remotely operated vehicles (ROV), both for tethered and untethered classes. As a result, the contents of this paper mainly focus upon thruster functioning enhancement by forming an effective real-time closed-loop compensation. An electric-driven thruster, instrumented with drive and embedded electronics, is employed as a test-bed. Its electrical and mechanical properties are briefly described and the inherent existence of stiction (static friction) will be highlighted since such nonlinearity directly degrades the dynamic behaviour of the thruster. Therefore, a nonlinear optimisation technique, serving as a 1-step-ahead predictive controller, has been structured not only to eliminate this unwanted stiction effect, but also to have the following additional attributes: 1) to maintain commanded rotational direction, 2) to regulate angular velocity with respect to set-point, and 3) to produce a robust system with better noise immunity. The intelligent predictive algorithm is based upon a multilayer perceptron (MLP) neural network configured as a state-estimator, whereas a model-reference gives the desired response characteristic. The outcome of such combined modules will clearly outperform the classical methodologies as indicated by the comparison with: i) an ordinary predictive strategy, and ii) an industrial three-term PID regulation.
Fuzzy classifier systems (FCS) implement a mapping from real numbers to real numbers, through fuzzy interpretation of input and output. Reinforcement learning (RL) algorithms can be successfully applied to develop lea...
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Fuzzy classifier systems (FCS) implement a mapping from real numbers to real numbers, through fuzzy interpretation of input and output. Reinforcement learning (RL) algorithms can be successfully applied to develop learning FCS analogously to what can be done with learning classifier systems (LCS). The author motivates this approach and presents a methodology to extend straightforwardly reinforcement distribution algorithms originally designed for crisp input and output to fully exploit the features of FCS.
The basic unique control problem for repetitive processes arises from the explicit interaction between successive pass profiles. In particular, the output sequence of pass profiles can contain oscillations that increa...
The basic unique control problem for repetitive processes arises from the explicit interaction between successive pass profiles. In particular, the output sequence of pass profiles can contain oscillations that increase in amplitude in the pass to pass direction. Such behaviour is easily generated in simulation studies and in experiments on scaled models of industrial examples such as long-wall coal cutting. In long-wall coal cutting this problem appears as severe undulations in the newly cut floor profile which means that cutting operations (i.e. productive work) must be suspended to enable their manual removal. This problem is one of the key factors behind the stop/start cutting pattern of a typical working cycle in a coal mine. In general, this problem cannot be removed by standard, i.e. 1D, control action. The basic reason for this is that such an approach essentially ignores their inherent 2D systems structure. Motivated by this key fact, Rogers and Owens (1992) have developed a stability theory for repetitive processes with linear dynamics and a constant pass length. This theory is based on an abstract model in a Banach space setting which includes all such processes as special cases. The results of applying this theory to a range of special cases are also known including discrete linear repetitive processes which are the subject of this paper.
Repetitive, or multipass, processes are a class of systems characterised by a series of sweeps through a set of dynamics defined over a finite fixed duration. The class of so-called discrete linear repetitive processe...
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ISBN:
(纸本)9783952426906
Repetitive, or multipass, processes are a class of systems characterised by a series of sweeps through a set of dynamics defined over a finite fixed duration. The class of so-called discrete linear repetitive processes have strong structural links with well studied classes of 2D linear systems and also with standard (1D) linear systems. One possible approach to the (control related) analysis of these processes is to embed their basic 2D structure in a 1D representation. This paper develops such a representation and uses it to characterise the key systems theoretic property of controllability for this class of linear repetitive processes.
In this paper so-called multitime scale systems are described in terms of discrete repetitive processes which belong to the wide family of so-called 2D systems.
In this paper so-called multitime scale systems are described in terms of discrete repetitive processes which belong to the wide family of so-called 2D systems.
In this paper a method for collision detection and collision avoidance for dual arm robots is proposed. The collision detection, a fast geometric approach based on link intersection, detects the collision and construc...
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In this paper a method for collision detection and collision avoidance for dual arm robots is proposed. The collision detection, a fast geometric approach based on link intersection, detects the collision and constructs the collision region for given trajectories. The time delay planning determines the minimum necessary time delay to avoid collisions using a potential field representation for collision regions. The planning is based on a flexible, massively parallel approach. It effectively avoids any local minima problems due to the potential field representation and can be used regardless of the complexity of the collision region (e.g., concave or complicated regions).
An object-oriented modular approach to the engineering of complex robotic systems emphasizes reliability, reusability, ease of development, and user and network interfaces. This modular approach integrates many archit...
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An object-oriented modular approach to the engineering of complex robotic systems emphasizes reliability, reusability, ease of development, and user and network interfaces. This modular approach integrates many architectural principles and computational techniques which support adaptive and learning capability at the local, modular level. The TETROBOT is a modular and reconfigurable robotic system which was developed to demonstrate the reliable performance in a wide variety of task domains through reconfiguration of the same fundamental hardware and software components. Such a modular approach emphasizes the synthesis and integration of engineering modules and takes advantage of object-oriented engineering principles to design for a family of tasks. This paper provides an overview of the TETROBOT modular system and describes three modular systems in other applications domains.
The classical Bayesian decision theory and the hypothesis testing for processing distributed decision fusion problems have an important shortcoming-lack of flexibility. In other words, they can not discriminate uncert...
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The classical Bayesian decision theory and the hypothesis testing for processing distributed decision fusion problems have an important shortcoming-lack of flexibility. In other words, they can not discriminate uncertainty and ignorance. The Dempster-Shafer (DS) theory overcomes this shortcoming, but its mathematical basis, the axiomatic definition of evidence is not very rigorous. Therefore, a perfect, reliable, and general method of statistical decision and evidence combination is demanded. In this respect, Thomopoulos presented a generalized evidence processing (GEP) method, based on Bayesian theory and DS theory. This paper presents a new strategy for statistical decision and evidence combination-the double bound testing (DBT). Compared with GEP, DBT not only increases the flexibility of decision, but also presents a sound mathematical basis and an explicit concept.
A mathematical model for predictive/adaptive control of weld bead penetration and seam tracking in tungsten inert gas welding as an approach to process control of robotic GTAW has been developed. Weld process paramete...
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A mathematical model for predictive/adaptive control of weld bead penetration and seam tracking in tungsten inert gas welding as an approach to process control of robotic GTAW has been developed. Weld process parameters such as : base current and time, pulse current and time, electrode tip to workpiece distance, filler traveling speed, torch traveling speed and workpiece thickness have been used for finding the equations which describing interrelationship between the aforementioned variables and penetration depth as well as bead width. The calculation of these equations developed from the statistical regression analysis of 80 welds deposited using various combinations of welding parameters. For monitoring of workpiece thickness variations,an ultrasonic device has been used. In order to accurately control weld bead width and also seam tracking, a CCD camera was used. The results show that the misalignment or asymmetry of progressive HAZ adjacent to the weld puddle is detectable and can be used for control of trajectory. Scanning of a certain area of a captured image in front ofthe weld puddle decreases the data processing time drastically.
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