modelpredictivecontrol (MPC) has been considered as the most important development in the area of process control in the last two decades. This paper addresses the issue of controlling a nonlinear plant by the use o...
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ISBN:
(纸本)9781424417391
modelpredictivecontrol (MPC) has been considered as the most important development in the area of process control in the last two decades. This paper addresses the issue of controlling a nonlinear plant by the use of the nonlinearmodelpredictivecontrol formulation. To handle the nonlinearities, a Takagi-Sugeno neuro-fuzzy model is suggested as a means to model the plant with nonlinearities depending on the operating region. The developed model is used as a predictivemodel for a parallel distributed modelpredictivecontrol algorithm. In this paper, the parallel distributed neuro-fuzzy modelpredictivecontroller has been proposed to control a non-linearcontrol system of a hydro, turbine generator. The proposed technique has been tested and evaluated using this simulated industrial plant.
This paper surveys how the three central pillars of process control – PID control, conventional advanced control, and modelpredictivecontrol – have been used and how they have contributed to production activity fr...
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This paper surveys how the three central pillars of process control – PID control, conventional advanced control, and modelpredictivecontrol – have been used and how they have contributed to production activity from the viewpoint of the process control section in the Japanese chemical industry. In addition to introducing practical methods and their application results, the authors point out challenging problems, which include the development of a general model-based control technique to enhance batch process control.
This paper describes a multi-rate modelpredictivecontrol for a chemical reactor rig. Three multi-input single-output neural network models are developed with different sampling times;each for one reactor output. A m...
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This paper describes a multi-rate modelpredictivecontrol for a chemical reactor rig. Three multi-input single-output neural network models are developed with different sampling times;each for one reactor output. A multi-rate control strategy is proposed based on the multi-rate models, which enables reduced dimension optimisations to be used in majority of searching for optimal controls. In addition, some practical control techniques are also applied. Effectiveness of the proposed method is evaluated by both simulations and on-line control. A comparison with three decentralised PID controllers is presented. (C) 2007 Elsevier B.V. All rights reserved.
This paper concerns the simultaneous synthesis and control of walking gaits for biped robots. The goal is to propose an adaptable and reactive control law for two-legged machines. The problem is addressed with human l...
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This paper concerns the simultaneous synthesis and control of walking gaits for biped robots. The goal is to propose an adaptable and reactive control law for two-legged machines. The problem is addressed with human locomotion as a reference. The starting point of our work is an analysis of human walking from descriptive (biomechanics) as well as explicative (neuroscience and physiology) points of view, the objective being to stress the relevant elements for the approach of robot control. The adopted principles are then: no joint trajectory tracking;explicit distinction and integration of postural and walking control;use of evolutive optimization objectives;on-line event handling and environment adaptation and anticipation. This leads to the synthesis of an original control scheme based on non-linear model predictive control: Trajectory Free NMPC. The movement is specified implicitly through coherent physical inequality constraints. Dynamic model and internal limitations of the system are part of the problem constraints. This work is validated by simulation results obtained for the Bip and Rabbit biped robots in various walking and standing situations and compared to human data recorded in these same situations. (C) 2004 Elsevier B.V. All rights reserved.
This paper describes the application of nonlinearmodelpredictivecontrol (NMPC) to the thermal control of a batch or semi-batch chemical reactor fitted with an alternative heating/cooling system. The strategy of the...
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This paper describes the application of nonlinearmodelpredictivecontrol (NMPC) to the thermal control of a batch or semi-batch chemical reactor fitted with an alternative heating/cooling system. The strategy of the nonlinearcontrol system is based on an open-loop constrained optimisation problem which is solved repeatedly on-line by a sequential optimisation and solution strategy on a PC for a typical temperature sampling rate. The feasibility of such a controller is examined on simulations and experiments on a 16 litres pilot plant. The presented results are satisfactory and are promising for an industrial use of such a technique.
This paper describes the application of nonlinearmodelpredictivecontrol (NMPC) to the thermal control of a batch or semi-batch chemical reactor fitted with an alternative heating/cooling system. The strategy of the...
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This paper describes the application of nonlinearmodelpredictivecontrol (NMPC) to the thermal control of a batch or semi-batch chemical reactor fitted with an alternative heating/cooling system. The strategy of the nonlinearcontrol system is based on an open-loop constrained optimisation problem which is solved repeatedly on-line by a sequential optimisation and solution strategy on a PC for a typical temperature sampling rate. The feasibility of such a controller is examined on simulations and experiments on a 16 litres pilot plant. The presented results are satisfactory and are promising for an industrial use of such a technique.
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