Her book entitled model predictive control design and implementation using matlab was published by springerverlag in 2009, and the second edition of this book is currently under preparation. Thermal stress reduction of quasiz source inverter drive by model predictive control. So is control loop performance monitoring clpm software. Buy liuping wang ebooks to read online or download in pdf or epub on your pc, tablet or mobile device. Robust model predictive control for discrete uncertain. It is common that underactuated surface vessels sailing on the sea suffer from strong external sea disturbances, such that the large roll motion can be probably. An efficient nonlinear justintime learning jitl soft sensor method for online modeling of batch processes with uneven operating durations is proposed.
Leaving the technical details aside until chapter 3, this chapter will explain the basic idea of mpc and summarize the content of the thesis. The sparse optimal control family, developed by the boeing company, contains two advanced software packages, available separately or together. Model predictive control mpc has a long history in the. Adaptive cruise control acc system is a driver assistant system, which can provide safe and comfortable driving. The structure of the bilinear system is converted into a simple linear model by using nonlinear support vector machine svm dynamic approximation with analytical control law derived. But if both help practitioners to optimize control loop performance, then whats the difference. Path following for underactuated surface vessels with. A timely introduction to current research on pid and predictive control by one of the leading authors on the subjectpid and predictive control of electric drives and. In order to deal with nonlinear, timevarying and disturbanceinvolved characteristics in the practical industrial processes, an indirect adaptive statespace mpc model predictive control method based on subspace identification is proposed. Four major aspects of model predictive control make the design methodology attractive to both practitioners and academics.
Jul 23, 2014 modelpredictive control mpc is advanced technology that optimizes the control and performance of businesscritical production processes. Subspacebased model predictive control with data pre ltering. Model predictive control design liuping wang peter c. A timely introduction to current research on pid andpredictive control by one of the leading authors on thesubject. Liuping wang rmit university, melbourne rmit school of. Twothermalstates model predictive control for igbt in. Lee school of chemical and biomolecular engineering center for process systems engineering georgia inst. Young school of electrical and computer engineering rmit university, melbourne, australia centre for research on environmental syst. A vehicle driving with an adaptive cruise control system acc is usually controlled decentrally, based on the information of radar systems and in some publications based on c2xcommunication cacc to guarantee stable platoons. As the guide for researchers and engineers all over the world concerned with the latest. Pid and predictive control of electrical drives and power. Feb 14, 2009 model predictive control system design and implementation using matlab ebook written by liuping wang. Overview a timely introduction to current research on pid andpredictive control by one of the leading authors on thesubject. Liuping wang rmit university, melbourne rmit school.
Common mode current suppression for permanent magnet synchronous motor based on model predictive control. Model predictive control mpc refers to a class of control algorithms in which a dynamic process model is used to predict and optimize process performance. The toolbox lets you specify plant and disturbance models, horizons, constraints, and weights. Download it once and read it on your kindle device, pc, phones or tablets. Localizing root cause machines for software service failure mitigation. A model predictive control performance monitoring and grading strategy based on improved slow feature analysis. For this purpose, an adaptive cruise control acc algorithm with multiobjectives is proposed based on a model predictive control mpc framework. Compre o livro model predictive control system design and implementation using matlabr. Manufacturing planning and predictive process model integration using software agents shaw c.
Introducing computational guidance and control journal. List of computer science publications by liuping wang. Dr liuping wang has successfully applied the predictive. Ping wang 0008 chongqing university of posts and telecommunications, key laboratory of industrial internet of things and networked control, china and 1 more ping wang 0009 xian jiaotong university, school of electronic and information engineering, china. Ping wang 0001 york university, department of electrical engineering and computer science, toronto, canada and 2 more. Model predictive control system design and implementation using matlab advances in industrial control kindle edition by wang, liuping. Even though the main area of interest is avc, the software. In this chapter, the roundtrip time delay in an ncs is redefined such that it can describe the joint effect of random networkinduced delays, packet disorders, and packet dropouts in the feedback and forward channels. Cervical spondylotic is a clinical syndrome caused by cervical disc degeneration, cervical vertebrae hyperplasia, cervical vertebrae joint and ligament loosening and dislocation stimulation or oppression of cervical nerve roots, 25 accounting for 60% of cervical spondylosis 70%, mainly manifested as pain and numbness in the corresponding nerve distribution area. Liuping wang is the author of plate heat exchangers 3. Dr liuping wang has successfully applied the predictive control and system.
Author links open overlay panel yi liu a c ping liu b c huai wang c meng huang a xiaoming zha a. The results show that, compared with the autoregressive exogenous model, the extreme learning machineautoregressive exogenous model has good control performance on the multivariable and nonlinear system and can reduce computing resource requirements during the online running. Ping wang 0003 peking university, school of software and microelectronics national engineering research center for software engineering, beijing, china. Applications include trajectory optimization, chemical process control and machine tool path definition. Sparse optimal control software socs is generalpurpose software for solving optimal control problems. Model predictive control mpc is unusual in receiving ongoing interest in both industrial and academic circles.
Model predictive control also has the advantage that couplings between variables in the process are taken into account. The book gives an introduction to model predictive control mpc, and recent developments in design and implementation. Pid and predictive control of electrical drives and power converters using matlab simulink a timely introduction to current research on pid andpredictive control by one of the leading authors on thesubjectpid and predictive control of electric drives and powersupplies using matlabsimulink examines the classical controlsystem strategies, such as pid control, feedforward control andcascade. Thermal stress reduction of quasiz source inverter drive. Professor wang aims to provide both the industrial and the academic reader with a direct but graded route into understanding mpc as used in the solution of industrial control problems.
View ping lius profile on linkedin, the worlds largest professional community. Ping wang 0002 pla university of science and technology, college of defense engineering, nanjing, china. Zibo meng, ping liu, jie cai, shizhong han, yan tong. Based on the analysis of acc system, a parameter selftuning fuzzypid algorithm is developed to design the acc control strategy. Wang associate editors journal of process control journals. A widelydeployable framework to automatically localizing root cause machines for software service failure mitigation.
National laboratory of industrial control technology, institute of advanced process control, zhejiang university, hangzhou 310027, china. Learningbased model predictive control for markov decision processes rudy r. On identification of hammerstein and wiener model with application to virtualised software system. This cited by count includes citations to the following articles in scholar. In addition, the models predictive control was used only for temperature control inside the rotary kiln. In addition to comfort and fueleconomy, automated vehicles also have the basic requirements of safety and carfollowing. P model predictive control mpc is unusual in receiving ongoing interest in both industrial and academic circles. According to the random timedelay exist in sensorcontroller channel and controlleractuator channel in networked control systems, an adaptive predictive control strategy was proposed. Model predictive control system design and implementation using matlab. Bs in information engineering, university of science and technology, beijing, 2008.
This paper recalls a few past achievements in model predictive control, gives an overview of some current developments and suggests a few avenues for future research. Research on networked control systems based on adaptive predictive control authors. The similarity between the query sample and the most relevant samples, including the. Model predictive control of an electric vehicle motor drive integrated battery. Subspacebased indirect adaptive statespace model predictive. Dr liuping wang has successfully applied the predictive control technologies to from mebm e4439 at columbia university. Liu, model based predictive controller design for a class of nonlinear networked systems with communication delays. The books approach is expected to appeal to a wide readership ranging from the industrial control engineer to the postgraduate student in the process and control disciplines. Model predictive control system design and implementation. Model predictive control mpc is a particular branch of modelbased design. This volume includes numerous analytical examples and problems and matlab r programs and exercises. Model predictive control system design and implementation using matlab advances in industrial control kindle edition by liuping wang.
A provoking analogy between mpc and classical control can be found in 15. Abstract a new multistep adaptive predictive control algorithm for a class of bilinear systems is presented. Her book entitled model predictive control design and implementation using. Model predictive control toolbox provides functions, an app, and simulink blocks for designing and simulating model predictive controllers mpcs. New trends and tools alberto bemporad abstractmodelbased design is well recognized in industry as a systematic approach to the development, evaluation, and implementation of feedback controllers. Liu,tradeoffsbetween transmission intervals and delays for decentralized networked control systems based on a. Model predictive control mpc is an advanced method of process control that is used to control a process while satisfying a set of constraints. Compensation for performance management in virtualized software system. Identityaware convolutional neural network for facial expression recognition. Model predictive control for adaptive cruise control with. Download for offline reading, highlight, bookmark or take notes while you read model predictive control system design and implementation using matlab. However, the established model is linear and cannot accurately describe the nonlinear characteristics of a rotary cement kiln system. Model predictive control design using nonminimal state space model liuping wang peter c. The corresponding operating region of the considered systems in state space is described as ellipsoid which can be characterized by a set of vector inequalities.
From lower request of modeling accuracy and robustness to complicated process plants, mpc has been widely accepted in many practical fields. Multivariable nonlinear predictive control of a clinker. Model predictive control system design and implementation using. Online approximated justintime model predictive control for batch trajectory tracking. Linyuan shang, yanjiang wang, xiaogang deng, yuping cao, ping wang, yuhong wang. Design and implementation of model predictive controller for. In this thesis, we deal with aspects of linear model predictive control, or mpc for short. She leads the control systems program at the australian advanced manufacturing. According to the traffic condition, the parameters of pid controller are adapted online by fuzzy rule. Manufacturing planning and predictive process model. Thus, this paper proposes a thermal stress reduction scheme for qzsi drive, which utilizes finite control set model predictive control.
Use features like bookmarks, note taking and highlighting while reading model predictive control system design and implementation using matlab advances in industrial control. It is one of the few areas that has received ongoing interest from researchers in both the industrial and academic communities. This chapter is devoted to the implementation of model predictive control mpc algorithms in active vibration control avc applications. Tutorial overview of model predictive control ieee control. In recent years, much e ort has been spent to incorporate the robustness problem into this framework. Delft center for systems and control delft university of technology, delft, the netherlands institute of information and computing sciences utrecht university, utrecht, the netherlands.
An improved structure for model predictive control using nonminimal state space realisation. See the complete profile on linkedin and discover pings connections. Model predictive control mpc, also referred to asreceding horizon control and moving horizon optimal control, has been widely adopted in industry as an e ective means to deal with multivariable constrained control problems lee and cooley 1997, qin and badgewell 1997. Model predictive control system design and implementation using matlab r by liuping wang, 9781848823303, available at. Tutorial overview of model predictive control ieee control systems mag azine author. Model predictive control system design and implementation using matlab r proposes methods for design and implementation of mpc systems using basis functions that confer the following advantages. A read is counted each time someone views a publication summary such as the title, abstract, and list of authors, clicks on a figure, or views or downloads the fulltext. Pid and predictive control of electric drives and powersupplies using matlabsimulink examines the classical controlsystem strategies, such as pid control, feedforward control andcascade control, which are widely used in current practice. The method is fulfilled by changing the coefficients of the. Liu, model based predictive controller design for a class of. A timely introduction to current research on pid and predictive control by one of the leading authors on the subject pid and predictive control of electric drives and power supplies using matlabsimulink examines the classical control system strategies, such as pid. Model predictive control system design and implementation using matlab advances in industrial control liuping wang on. Ping liu analysis and synthesis of networked control systems.
Metaanalysis of the therapeutic effect of acupuncture and. It has been in use in the process industries in chemical plants and oil refineries since the 1980s. Justintime kernel learning with adaptive parameter. Optimal rocket landing guidance using convex optimization and model predictive control.
Read model predictive control for adaptive cruise control with multiobjectives. The basic idea in mpc is to repeatedly solve optimization problems online to nd an optimal input to the controlled system. Robust model predictive control for discrete uncertain nonlinear systems with timedelay via fuzzy model. Motivated by aerospace applications, this paper presents a methodology to use secondorder cone programming to solve nonconvex optimal control problems. In this control strategy, an improved generalized predictive control algorithm is adopted to compensate the networked. Model predictive control system design and implementation using matlab advances in industrial control series by liuping wang. Solving nonconvex optimal control problems by convex. Issues such as plant optimization and constrained control which are critical to industrial engineers are naturally embedded in its designs. Liuping wang of rmit university, melbourne rmit read 235 publications. A model predictive control mpc is proposed for the piecewise affine pwa systems with constrained input and time delay. Preliminaries for networked predictive control springerlink. A recursive leastsquares support vector regression rlssvr approach is combined with the jitl manner to model the nonlinearity of batch processes.
Justintime kernel learning with adaptive parameter selection for soft sensor modeling of batch processes. It uses nonlinear mechanistic models which makes it better and more robust than alternative technologies that often rely on. Model predictive control system design and implementation using matlab advances in industrial control feb 14, 2009. Model predictive control mpc this example, from control systems, shows a typical model predictive control problem. Subspacebased model predictive control with data pre ltering noor a. Mpc implementation for vibration control springerlink. She is the leading author of the book entilted pid and predictive control.
See this paper for the precise problem formulation and meanings of the algorithm parameters. See the paper by mattingley, wang and boyd for some detailed examples of mpc with cvxgen. Search for more papers by this author published online. Predictive control of a class of bilinear systems based on. Efficient model predictive control of fullbridge dcdc converter using laguerre. Pid and predictive control of electrical drives and power converters using matlab simulink by liuping wang, 9781118339442, available at book depository with free delivery worldwide. The cost function is designed by including terms of. Mardi liuping wang school of electrical and computer engineering, royal melbourne. In this paper we present a model predictive control mpc design of a centralized, serverbased accsystem, whereby the vehicular platoon is modeled and controlled as.
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