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A novel real-time non-linear wavelet-based model predictive controller for a coupled tank system

PROCEEDINGS OF THE INSTITUTION OF MECHANICAL ENGINEERS PART I-JOURNAL OF SYSTEMS AND control ENGINEERING 2014年第6期228卷 419-432页

作者： Owa, Kayode Sharma, Sanjay Sutton, Robert Univ Plymouth Sch Marine Sci & Engn Plymouth PL4 8AA Devon England Marine & Ind Dynam Anal Res MIDAS Grp Plymouth Devon England

This article presents the design, simulation and real-time implementation of a constrained non-linear model predictive controller for a coupled tank system. A novel wavelet-based function neural network model and a genetic algorithm online non-linear real-time optimisation approach were used in the non-linear model predictive controller strategy. A coupled tank system, which resembles operations in many chemical processes, is complex and has inherent non-linearity, and hence, controlling such system is a challenging task. Particularly important is low-level control where often instability and oscillatory responses are observed. This article designs a wavelet neural network with high predicting precision and time-frequency localisation characteristics for an online prediction model in the non-linear model predictive controller to show the effectiveness of this approach in controlling the liquid at low level. To speed up the training process, a fast global search stochastic non-linear conjugate wavelet gradient algorithm is initially used to train the wavelet neural network structure before the genetic algorithm optimisation technique is utilised to tune adaptively the wavelet neural network parameters. The non-linear model predictive controller algorithm is tested for both approaches: first, in a simulation using identified models, and second, in a real-time practical application to a single-input single-output system coupled tank system. The results show an excellent control performance with respect to mean square error and average control energy values obtained.

关键词： Wavelet neural network artificial neural network modelling system identification non-linear model predictive control real-time practical implementation genetic algorithms single input single output non-linear optimisation coupled tank system Simulink model

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non-linear control algorithms for an unmanned surface vehicle

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PROCEEDINGS OF THE INSTITUTION OF MECHANICAL ENGINEERS PART M-JOURNAL OF ENGINEERING FOR THE MARITIME ENVIRONMENT 2014年第2期228卷 146-155页

作者： Sharma, Sanjay K. Sutton, Robert Motwani, Amit Annamalai, Andy Univ Plymouth Marine & Ind Dynam Anal Grp Ctr Adv Engn Syst & Interact Sch Marine Sci & Engn Plymouth PL4 8AA Devon England

Although intrinsically marine craft are known to exhibit non-linear dynamic characteristics, modern marine autopilot system designs continue to be developed based on both linear and non-linear control approaches. This article evaluates two novel non-linear autopilot designs based on non-linear local control network and non-linear model predictive control approaches to establish their effectiveness in terms of control activity expenditure, power consumption and mission duration length under similar operating conditions. From practical point of view, autopilot with less energy consumption would in reality provide the battery-powered vehicle with longer mission duration. The autopilot systems are used to control the non-linear yaw dynamics of an unmanned surface vehicle named Springer. The yaw dynamics of the vehicle being modelled using a multi-layer perceptron-type neural network. Simulation results showed that the autopilot based on local control network method performed better for Springer. Furthermore, on the whole, the local control network methodology can be regarded as a plausible paradigm for marine control system design.

关键词： Unmanned surface vehicle autopilot design non-linear model predictive control local control network genetic algorithm neural networks

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Thermal comfort control using a non-linear MPC strategy: A real case of study in a bioclimatic building

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JOURNAL OF PROCESS control 2014年第6期24卷 703-713页

作者： Castilla, M. Alvarez, J. D. Normey-Rico, J. E. Rodriguez, F. Univ Almeria CIESOL Joint Ctr Univ Almeria CIEMAT Automat Control Elect & Robot Res Grp Almeria Spain Univ Seville Dept Automat & Syst Technol Seville Spain Univ Fed Santa Catarina Dept Automat & Syst Florianopolis SC Brazil

The aim to maintain thermal comfort conditions in confined environments may require complex regulation procedures and the proper management of an HVAC (heating, ventilation and air conditioning) system. This problem is being widely analyzed, since it has a direct effect on users' productivity, and an indirect effect on energy saving. This paper presents a hierarchical thermal comfort control system with two layers. The upper layer includes a non-linear model predictive controller that allows to obtain a high thermal comfort level by optimizing the use of an HVAC system in order to reduce, as much as possible, the energy consumption. On the other hand, the lower layer is formed by a PIE) (proportional, integrative and derivative) controller with anti-windup function which is in charge of reach the setpoints calculated by the non-linear model predictive controller. In order to probe the effectiveness of the proposed control system, suitable real results obtained in a bioclimatic building are included and commented. (C) 2013 Elsevier Ltd. All rights reserved.

关键词： Hierarchical control non-linear model predictive control Thermal comfort PMV index Energy efficiency

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Optimal dosing of cancer chemotherapy using model predictive control and moving horizon state/parameter estimation

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COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE 2012年第3期108卷 973-983页

作者： Chen, Tao Kirkby, Norman F. Jena, Raj Univ Surrey Div Civil Chem & Environm Engn Guildford GU2 7XH Surrey England Cambridge Univ Hosp NHS Fdn Trust Ctr Oncol Cambridge CB2 2QQ England

model predictive control (MPC), originally developed in the community of industrial process control, is a potentially effective approach to optimal scheduling of cancer therapy. The basis of MPC is usually a state-space model (a system of ordinary differential equations), whereby existing studies usually assume that the entire states can be directly measured. This paper aims to demonstrate that when the system states are not fully measurable, in conjunction with model parameter discrepancy, MPC is still a useful method for cancer treatment. This aim is achieved through the application of moving horizon estimation (MHE), an optimisation-based method to jointly estimate the system states and parameters. The effectiveness of the MPC-MHE scheme is illustrated through scheduling the dose of tamoxifen for simulated tumour-bearing patients, and the impact of estimation horizon and magnitude of parameter discrepancy is also investigated. (C) 2012 Elsevier Ireland Ltd. All rights reserved.

关键词： Cancer therapy Dynamic system Moving horizon estimation non-linear model predictive control Pharmacodynamics Pharmacokinetics

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Adaptive cruise control with stop&go function using the state-dependent nonlinear model predictive control approach

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ISA TRANSACTIONS 2012年第5期51卷 622-631页

作者： Shakouri, Payman Ordys, Andrzej Askari, Mohamad R. Kingston Univ London Sch Mech & Automot Engn Fac Sci Engn & Comp London SW15 3DW England

In the design of adaptive cruise control (ACC) system two separate control loops - an outer loop to maintain the safe distance from the vehicle traveling in front and an inner loop to control the brake pedal and throttle opening position - are commonly used. In this paper a different approach is proposed in which a single control loop is utilized. The objective of the distance tracking is incorporated into the single nonlinear model predictive control (NMPC) by extending the original linear time invariant (LTI) models obtained by linearizing the nonlinear dynamic model of the vehicle. This is achieved by introducing the additional states corresponding to the relative distance between leading and following vehicles, and also the velocity of the leading vehicle. control of the brake and throttle position is implemented by taking the state-dependent approach. The model demonstrates to be more effective in tracking the speed and distance by eliminating the necessity of switching between the two controllers. It also offers smooth variation in brake and throttle controlling signal which subsequently results in a more uniform acceleration of the vehicle. The results of proposed method are compared with other ACC systems using two separate control loops. Furthermore, an ACC simulation results using a stop&go scenario are shown, demonstrating a better fulfillment of the design requirements. (C) 2012 ISA. Published by Elsevier Ltd. All rights reserved.

关键词： Vehicle dynamic Adaptive cruise control non-linear model predictive control State-dependent linear model

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nonlinear model predictive control of a dual-independent variable valve timing engine with electronic throttle control

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PROCEEDINGS OF THE INSTITUTION OF MECHANICAL ENGINEERS PART D-JOURNAL OF AUTOMOBILE ENGINEERING 2011年第D9期225卷 1221-1234页

作者： Lee, T-K Filipi, Z. S. Univ Michigan Dept Mech Engn Ann Arbor MI 48109 USA

Significant excursions of engine variables occur during fast transients because of slow actuator responses and system dynamics. This creates adverse effects on dynamic performance and often causes emissions penalties. The challenge is particularly pronounced in engines with an increased number of actuators. In this paper, non-linear model predictive control (NMPC) is introduced to improve the dynamic response of a flexible engine system. NMPC combines advantages of both feed forward and feedback control while considering their constraints. The length of control horizon and prediction horizon are determined to achieve the dead-beat-like optimal control during transients and ensure smooth responses. The NMPC significantly improves the engine torque response and minimizes the excursions of in-cylinder variables under highly transient operation by adjusting each actuator control input simultaneously to achieve the control objectives.

关键词： non-linear model predictive control engine control control oriented model variable valve timing electronic throttle control

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Real-Time Optimizing nonlinear control Applied to a Continuous Reactive Distillation Process

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IFAC Proceedings Volumes 2011年第1期44卷 4892-4897页

作者： Elrashid Idris Sebastian Engell Faculty of Bio-Chemical & Chemical Engineering TU-Dortmund 44227 Dortmund Germany

Abstract Chemical processes are usually operated under feedback control of critical operating conditions to maintain process safety, product quality and economic performance. Increasingly, linear model predictive is applied to these coupled multivariable control problems and in some cases the reference values are adapted infrequently by an optimization based as a rigorous nonlinear stationary plant model (RTO). However, in between these optimizations that plant may operate suboptimally due to the presence of disturbances. In recent years, it has been proposed to use nonlinear model-based optimization of the available degrees of freedom of a process over a finite moving horizon to integrate set-point optimization and feedback control (for a survey see Engell (2007)). In this paper we demonstrate the feasibility and the potential of the optimizing nonlinear control for a challenging example, a reactive distillation column. The performance of the controller is an economics-driven response since the profit function represents the main part of the objective criterion while the quality specifications as well as the physical limitations of the process were incorporated as optimization constraints. A performance comparison between the tracking controller and the optimizing nonlinear controller is also shown.

关键词： Reactive distillation non-linear model predictive control non-minimum phase behavior Tracking and optimizing control Static gain sign change

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On robustness of constrained non-linear H_∞ predictive controllers with disturbances

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INTERNATIONAL JOURNAL OF SYSTEMS SCIENCE 2010年第2期41卷 203-212页

作者： He, De-Feng Ji, Hai-Bo Zheng, Tao Univ Sci & Technol China Dept Automat Hefei 230026 Anhui Peoples R China

This article considers the robustness problem of H-infinity model predictive controllers for constrained non-linear discrete-time systems subject to disturbances, which are dependent on the system state and input. The notions of input-to-state stability and finite L-2-gain of non-linear systems are introduced and exploited to investigate the robustness properties of this predictive controller under the state and input constraints and the disturbance. Moreover, this robustness of the controller is extended to the case of suboptimality of the solution. With its feasibility at initial time, the feasibility of the online optimisation problem is guaranteed for all times in the presence of disturbances and constraints. Finally, an example is employed to illustrate the proposed results.

关键词： non-linear model predictive control input-to-state stability finite L-2-gain non-linear H-infinity control suboptimal control

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NMPC of a Continuous Fermenter Using Wiener-Hammerstein model Developed from Irregularly Sampled Multi-rate Data

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IFAC Proceedings Volumes 2010年第5期43卷 637-642页

作者： Dwaipayan Dasgupta Sachin C. Patwardhan Chemical Engineering Department Indian Institute of Technology Bombay Powai Mumbai 400076 India

control of a bio-reactor is a complex task due to inherent non-linearities and unavailability of measurements of the quality variables at regular sampling intervals. In this work, it proposed to identify Wiener-Hammerstein type fast-rate time series models for the quality variables directly from the irregularly sampled multi-rate input-output data. The identified models are further used to develop a multi-rate nonlinear predictive controller. The efficacy of the proposed modelling and control scheme is demonstrated by conducting simulation studies on a continuous fermenter system that exhibits input multiplicity and gain reversal in the desired operating region.

关键词： Irregular sampling Multi-rate systems Hammerstein-Wiener model Inferential control non-linear model predictive control

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Logic Embedded NMPC of a Solar Air Conditioning Plant

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EUROPEAN JOURNAL OF control 2008年第6期14卷 484-500页

作者： Rodriguez, M. De Prada, C. Capraro, F. Cristea, S. Univ Valladolid Dept Syst Engn & Automat Control Valladolid Spain

This paper presents a hybrid controller for a solar air conditioning plant, located at the University of Seville, Spain, and used as a benchmark for the HYCON NoE of the European Union (EU). The plant uses two sources of energy: solar and gas, plus a set of accumulation tanks and an absorption tower to provide conditioned air to a university building. The hybrid character comes from the discrete decisions that have to be taken in relation with the energy source in use, which is selected by means of on/off valves, plus the continuous nature of the process and other manipulated variables. The control aim is to operate the conditioned air system using the smaller possible amount of energy from gas and maintaining other variables close to their set points. The hybrid control is based on a model predictive control strategy developed with the objective of dealing with the mixed discrete-continuous nature of the process in an efficient way. A novel approach incorporating an internal model with embedded logic control is used to transform the hybrid problem in a continuous-nonlinear one where NMPC can be applied. The paper presents results obtained both, in simulation and in the realsystem.

关键词： Hybrid control non-linear model predictive control solar air conditioning plants dynamic optimization

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