Repetitive processes are a distinct class of two-dimensional (2D) systems (i.e. information propagation in two independent directions occurs) of both systems theoretic and applications interest. They cannot be control...
详细信息
Repetitive processes are a distinct class of two-dimensional (2D) systems (i.e. information propagation in two independent directions occurs) of both systems theoretic and applications interest. They cannot be controlled by direct extension of existing techniques from either standard (termed 1D here) or (most often) 2D systems theory. In this paper we define a new model for these processes necessary to represent dynamics which arise in some applications areas and which are not included in the currently used models. Then we proceed to define quadratic stability for this case, obtain conditions for its existence, and also solve the problem of designing a control law to stabilize the process dynamics (including the case when there is uncertainty associated with the defining state space model)
Repetitive processes are a distinct class of two-dimensional systems (i.e. information propagation in two independent directions) of both systems theoretic and applications interest. They cannot be controlled by direc...
详细信息
Repetitive processes are a distinct class of two-dimensional systems (i.e. information propagation in two independent directions) of both systems theoretic and applications interest. They cannot be controlled by direct extension of existing techniques from either standard (termed 1D here) or two-dimensional (2D) systems theory. Here we give new results on the design of physically based control laws using an H 2 setting. These results are for the sub-class of so-called differential linear repetitive processes which arise in applications areas such as iterative learning control.
Norm-optimal iterative learning control has potential to significantly increase the accuracy of many trajectory tracking tasks which can be found in industry. The algorithm can achieve very low levels of tracking erro...
详细信息
Norm-optimal iterative learning control has potential to significantly increase the accuracy of many trajectory tracking tasks which can be found in industry. The algorithm can achieve very low levels of tracking error and the number of iterations required to reach minimal error is small compared to many other iterative learning control algorithms. However, in the current format, the algorithm is not attractive to industry because it requires a large number of calculations to be performed at each sample instant. This implies that control hardware must be very fast which is expensive, or that the sample frequency must be reduced which can result in reduced performance. To remedy these problems, a revised version, fast norm-optimal iterative learning control is proposed which is significantly simpler and faster to implement. The new version is tested both in simulation and in practice on a three axis industrial gantry robot.
This paper considers the problem of stabilizing an uncertain discrete linear repetitive process where the model uncertainty is a result of the choice of the sampling period. The results obtained are applied to the eng...
详细信息
This paper considers the problem of stabilizing an uncertain discrete linear repetitive process where the model uncertainty is a result of the choice of the sampling period. The results obtained are applied to the engineering example of a material rolling process. The required computations to determine the control law are undertaken using LMIs.
Developing robust and reliable control code for autonomous mobile robots is difficult, because the interaction between a physical robot and the environment is highly complex, it is subject to noise and variation, and ...
详细信息
Developing robust and reliable control code for autonomous mobile robots is difficult, because the interaction between a physical robot and the environment is highly complex, it is subject to noise and variation, and therefore partly unpredictable. This means that to date it is not possible to predict robot behaviour, based on theoretical models. Instead, current methods to develop robot control code still require a substantial trial-and-error component to the software design *** iterative refinement could be reduced, we argue, if a more profound theoretical understanding of robot-environment interaction existed. In this paper, we therefore present a modelling method that generates a faithful model of a robot's interaction with its environment, based on data logged while observing a physical robot's behaviour. Because this modelling method — nonlinear modelling using polynomials — is commonly used in the engineering discipline of system identification, we refer to it here as “robot identification”.We show in this paper that using robot identification to obtain a computer model of robot-environment interaction offers several distinct advantages:*** compact representations (one-line programs) of the robot control program are *** model can be analysed, for example through sensitivity analysis, leading to a better understanding of the essential parameters underlying the robot's behaviour, *** generated, compact robot code can be used for cross-platform robot programming, allowing fast transfer of robot code from one type of robot to *** demonstrate these points through experiments with a Magellan Pro and a Nomad 200 mobile robot.
This paper discusses predictive motion control of a MiRoSoT robot. The dynamic model of the robot is deduced by taking into account the whole process - robot, vision, control and transmission systems. Based on the obt...
详细信息
ISBN:
(纸本)1889335215
This paper discusses predictive motion control of a MiRoSoT robot. The dynamic model of the robot is deduced by taking into account the whole process - robot, vision, control and transmission systems. Based on the obtained dynamic model, an integrated predictive control algorithm is proposed to position precisely with either stationary or moving obstacle avoidance. This objective is achieved automatically by introducing distant constraints into the open-loop optimization of control inputs. Simulation results demonstrate the feasibility of such control strategy for the deduced dynamic model.
The optimization problems of nonlinear model predictive control are generally non-convex and their convergence to global optima can hardly be assured. In mis paper, interval analysis is applied to such non-convex opti...
详细信息
The problem of either elimination or extraction of an unknown number of nonstationary complex sinusoidal signals burried in noise is considered. We derive a class of adaptive notch filtering algorithms which can be ef...
详细信息
The problem of identification/tracking of quasi-periodically varying systems is considered. This problem is a generalization, to the system case, of a classical signal processing task of either elimination or extracti...
详细信息
The paper presents the requirements of measurement system for electric arc furnace parameters measurement and for working characteristic calculating. On this basis measurement signals were specified and measurement al...
详细信息
暂无评论