MLD Systems: Modeling and Control — Experience With a Pilot Process

Abstract In this report, we present results of the modeling and control of a hydraulic pilot process, currently under construction at the Laboratory of Automatic of the ISA department of Universidad de Valladolid. The system is described by linear inequalities involving both, real and integer variables and the dynamical and logical decisions are heavily inter dependent. Hence the characterization as a Mixed Logical Dynamical system. Two MLD models are featured and both are suited to apply a Model Based Predictive Control strategy to command the system. Results of a simulation of the closed loop system are feature.

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Dynamic Modeling and Control of Packing Pressure in Injection Molding

Journal of Engineering Materials and Technology ◽

10.1115/1.2904280 ◽

1994 ◽

Vol 116 (2) ◽

pp. 244-249 ◽

Cited By ~ 8

Author(s):

J. Hu ◽

J. H. Vogel

Keyword(s):

Injection Molding ◽

Closed Loop ◽

Good Control ◽

Pressure Control ◽

Physical Parameters ◽

Closed Loop System ◽

Modeling And Control ◽

Packing Pressure ◽

And Control ◽

Plastic Injection

A dynamic model of injection molding developed from physical considerations is used to select PID gains for pressure control during the packing phase of thermo-plastic injection molding. The relative importance of various aspects of the model and values for particular physical parameters were identified experimentally. The controller gains were chosen by pole-zero cancellation and root-locus methods, resulting in good control performance. Both open and closed-loop system responses were predicted and verified, with good overall agreement.

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Modeling and control through leadership of a refined flocking system

Mathematical Models and Methods in Applied Sciences ◽

10.1142/s0218202515500098 ◽

2014 ◽

Vol 25 (02) ◽

pp. 255-282 ◽

Cited By ~ 38

Author(s):

Alfio Borzì ◽

Suttida Wongkaew

Keyword(s):

Predictive Control ◽

Control Strategy ◽

Social Systems ◽

Open Loop ◽

Modeling And Control ◽

Control Scheme ◽

Nonlinear Conjugate Gradient ◽

Optimality Systems ◽

And Control ◽

Conjugate Gradient Solver

A new refined flocking model that includes self-propelling, friction, attraction and repulsion, and alignment features is presented. This model takes into account various behavioral phenomena observed in biological and social systems. In addition, the presence of a leader is included in the system in order to develop a control strategy for the flocking model to accomplish desired objectives. Specifically, a model predictive control scheme is proposed that requires the solution of a sequence of open-loop optimality systems. An accurate Runge–Kutta scheme to discretize the optimality systems and a nonlinear conjugate gradient solver are implemented and discussed. Numerical experiments are performed that investigate the properties of the refined flocking model and demonstrate the ability of the control strategy to drive the flocking system to attain a desired target configuration and to follow a given trajectory.

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Modeling and Control of an Automotive All-Wheel Drive Clutch as a Piecewise Affine System

Journal of Dynamic Systems Measurement and Control ◽

10.1115/1.4025275 ◽

2013 ◽

Vol 136 (1) ◽

Cited By ~ 1

Author(s):

Shiming Duan ◽

Jun Ni ◽

A. Galip Ulsoy

Keyword(s):

Closed Loop ◽

Open Loop ◽

Lyapunov Theory ◽

Loop System ◽

Linear Matrix ◽

Closed Loop System ◽

Modeling And Control ◽

Piecewise Affine ◽

Wheel Drive ◽

And Control

Piecewise affine (PWA) systems belong to a subclass of switched systems and provide good flexibility and traceability for modeling a variety of nonlinear systems. In this paper, application of the PWA system framework to the modeling and control of an automotive all-wheel drive (AWD) clutch system is presented. The open-loop system is first modeled as a PWA system, followed by the design of a piecewise linear (i.e., switched) feedback controller. The stability of the closed-loop system, including model uncertainty and time delays, is examined using linear matrix inequalities based on Lyapunov theory. Finally, the responses of the closed-loop system under step and sine reference signals and temperature disturbance signals are simulated to illustrate the effectiveness of the design.

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DYNAMIC ANALYSIS AND CONTROL OF CABLE DRIVEN ROBOTS WITH ELASTIC CABLES

Transactions of the Canadian Society for Mechanical Engineering ◽

10.1139/tcsme-2011-0033 ◽

2011 ◽

Vol 35 (4) ◽

pp. 543-557 ◽

Cited By ~ 37

Author(s):

Mohammad A. Khosravi ◽

Hamid D. Taghirad

Keyword(s):

Control Algorithm ◽

Closed Loop ◽

Parallel Manipulators ◽

Lyapunov Theorem ◽

Closed Loop System ◽

Modeling And Control ◽

Internal Forces ◽

And Control ◽

Flexible Cables ◽

Elastic Cables

In this paper modeling and control of cable driven redundant parallel manipulators with flexible cables, are studied in detail. Based on new results, in fully constrained cable robots, cables can be modeled as axial linear springs. Considering this assumption the system dynamics formulation is developed using Lagrange approach. Since in this class of robots, all the cables should remain in tension for the whole workspace, the notion of internal forces are introduced and incorporated in the proposed control algorithm. The control algorithm is developed in cable coordinates in which the internal forces play an important role. Finally, asymptotic stability of the closed loop system is analyzed through Lyapunov theorem, and the performance of the proposed algorithm is studied by simulations.

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Ellipsoidal Lyapunov-based hybrid model predictive control for mixed logical dynamical systems with a recursive feasibility guarantee

Transactions of the Institute of Measurement and Control ◽

10.1177/0142331218801126 ◽

2018 ◽

Vol 41 (9) ◽

pp. 2475-2487

Author(s):

Alireza Olama ◽

Mokhtar Shasadeghi ◽

Amin Ramezani ◽

Mostafa Khorramizadeh ◽

Paulo R C Mendes

Keyword(s):

Dynamical Systems ◽

Model Predictive Control ◽

Hybrid Model ◽

Predictive Control ◽

Robust Stability ◽

Optimization Problem ◽

Closed Loop ◽

Loop System ◽

Closed Loop System ◽

Mixed Logical Dynamical

This paper proposes an ellipsoidal hybrid model predictive control approach to solve the robust stability problem of uncertain hybrid dynamical systems modelled by the mixed logical dynamical framework. In this approach, the traditional terminal equality constraint is replaced by an ellipsoid that results in a maximal positive invariant set for the closed-loop system. Then, a Lyapunov decreasing condition along with the robustness criterion is introduced to the optimization problem to achieve the robust stability of the closed-loop system. As the main advantages, the ellipsoidal terminal set proposed in this paper attains a larger domain of attraction along with the recursive feasibility guarantee. Moreover, the stability and robustness constraints are achieved by a lower prediction horizon, which leads to a smaller dimension optimization problem. In addition, to reduce the computational complexity of the corresponding optimization problem, a suboptimal version of the proposed algorithm is introduced. Finally, numerical and car suspension system examples show the capabilities of the proposed method.

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An Effective Modeling and Control Strategy for Supply Chain Design and Planning

Key Engineering Materials ◽

10.4028/www.scientific.net/kem.467-469.1132 ◽

2011 ◽

Vol 467-469 ◽

pp. 1132-1135

Author(s):

Hai Dong ◽

Wei Ling Zhao ◽

Yan Ping Li

Keyword(s):

Supply Chain ◽

Model Predictive Control ◽

Predictive Control ◽

Control Strategy ◽

Planning Process ◽

Supply Chain Design ◽

Supply Chain Network ◽

Modeling And Control ◽

Work Model ◽

And Control

The dynamics and uncertainty of the business and the market makes difficult to coordinate the activities of a supply chain. Therefore, it is important to review systematically and to take into account the variability in the planning formulation in order to manage a supply chain network efficiently. A novel stochastic multi-period design and planning MILP model of a multiechelon supply chain network is used as a predictive model in this work. Model predictive control is presented as a way to manage supply chain in the presence of uncertainty by incorporating unforeseen events into the planning process. Illustrative example shows control strategy based on model predictive control framework is effective in the supply chain network design and planning.

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Integrated Toolkit for Closed-Loop Flow Control: Flow Simulation, Reduced-Order Modeling, and Control Design (Invited)

38th Fluid Dynamics Conference and Exhibit ◽

10.2514/6.2008-3980 ◽

2008 ◽

Author(s):

Tim Colonius ◽

Kunihiko Taira ◽

Won Joe ◽

Clancy Rowley ◽

Sunil Ahuja

Keyword(s):

Flow Control ◽

Closed Loop ◽

Control Design ◽

Flow Simulation ◽

Reduced Order Modeling ◽

Control Flow ◽

Modeling And Control ◽

Reduced Order ◽

And Control

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Design, Construction, and Control for an Underwater Vehicle Type Sepiida

Robotica ◽

10.1017/s0263574720000739 ◽

2020 ◽

pp. 1-18

Author(s):

M. Garcia ◽

P. Castillo ◽

E. Campos ◽

R. Lozano

Keyword(s):

Embedded System ◽

Closed Loop ◽

Underwater Vehicle ◽

Mathematical Representation ◽

Closed Loop System ◽

Vehicle Type ◽

Mathematical Equations ◽

And Control ◽

Design Construction

SUMMARY A novel underwater vehicle configuration with an operating principle as the Sepiida animal is presented and developed in this paper. The mathematical equations describing the movements of the vehicle are obtained using the Newton–Euler approach. An analysis of the dynamic model is done for control purposes. A prototype and its embedded system are developed for validating analytically and experimentally the proposed mathematical representation. A real-time characterization of one mass is done to relate the pitch angle with the radio of displacement of the mass. In addition, first validation of the closed-loop system is done using a linear controller.

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