Pulse-Step Control

Wallén, Anders; Åström, Karl Johan

doi:10.3182/20020721-6-es-1901.00110

Cited by 21 publications

(7 citation statements)

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“…In this paper, a control planning set algorithm is combined with DMPC controller to reduce the controller information communication delay and meanwhile it also can decrease the DMPC controller calculation demand without degrading the whole system performance much. The control planning set method presented in the paper is inspired by the pulse-step control strategy [20]. Suboptimal strategies can be obtained by restricting the future control sequence…”

Section: Improved Distributed Model Predictive Control With Control Pmentioning

confidence: 99%

Improved Distributed Model Predictive Control with Control Planning Set

Chen

2016

Journal of Control Science and Engineering

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We focus on distributed model predictive control algorithm. Each distributed model predictive controller communicates with the others in order to compute the control sequence. But there are not enough communication resources to exchange information between the subsystems because of the limited communication network. This paper presents an improved distributed model predictive control scheme with control planning set. Control planning set algorithm approximates the future control sequences by designed planning set, which can reduce the exchange information among the controllers and can also decrease the distributed MPC controller calculation demand without degrading the whole system performance much. The stability and system performance analysis for distributed model predictive control are given. Simulations of the four-tank control problem and multirobot multitarget tracking problem are illustrated to verify the effectiveness of the proposed control algorithm.

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Section: Improved Distributed Model Predictive Control With Control Pmentioning

confidence: 99%

Improved Distributed Model Predictive Control with Control Planning Set

Chen

2016

Journal of Control Science and Engineering

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“…One of these additional functionalities is the feedforward control action, which can be suitably applied in order to improve the set-point following performance, especially when the tuning of the PID parameters is devoted to the load disturbance rejection performance. Actually, different techniques have been devised for the synthesis of a feedforward action in the context of SISO systems, exploiting different concepts such as set-point weight [6,7], bangbang control [8,9], and input-output inversion [10]. Some of these techniques have been also extended to MIMO processes [11,12].…”

Section: Introductionmentioning

confidence: 99%

Minimum-time rest-to-rest feedforward action for PID feedback MIMO systems

Consolini

Lini

Piazzi

et al. 2012

IFAC Proceedings Volumes

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In this paper we present a methodology for the design of a feedforward control law to be applied to a closed-loop PID-based control system for a multi-input multi-output process in order to achieve a minimum-time rest-to-rest transition of the system from an equilibrium point to another subject to constraints on both the control and process variables. In particular, the proposed approach uses decentralized PID controllers which can be designed by any of the conventional methods, such as, for example, those aiming at rejection of load disturbances. Then, the closed-loop generalized bang-bang command input vector is determined by applying a linear programming approach in order to minimize the rest-to-rest output transitions. Conditions for the constraints for which the problem admits a solution are given. Simulations for a two-inputs two-outputs plant highlight the effectiveness of the approach.

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“…In this context a particular attention has been paid by researchers to the synthesis of a suitable feedforward control action (Åström and Hägglund, 2006;Kuo, 1995) in order to improve the set-point following performance, which is of particular concern in many cases, especially in the control of batch processes when load disturbances are not critical. Among the different approaches proposed in the literature (see, for example, (Araki, 1988;Hang and Cao, 1996;Visioli, 1999;Bascetta, 2007, 2008;Wallen, 2000;Wallen andÅström, 2002;Visioli, 2004;Piazzi and Visioli, 2006)), a methodology that takes into account explicitly the constraints on both the manipulated and the process variable has been proposed in (Piccagli and Visioli, 2009). Therein, a feedback control system with an already tuned PID controller is considered.…”

Section: Introductionmentioning

confidence: 99%