Time scale analysis and synthesis for Model Predictive Control under stochastic environments

Zhang, Yan; Naidu, D. Subbaram; Nguyen, Hoa M.; Cai, Chenxiao; Zou, Yun

doi:10.1109/isrcs.2014.6900085

Cited by 7 publications

(12 citation statements)

References 11 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The solution pairs (21)(22)(23) and (24)(25) satisfy the equation (10) under the condition (11) [24].…”

Section: Time Scaling and Upsampled Solutions Of Lti Plantmentioning

confidence: 99%

“…• Implementing the combination of the slow and fast MPC algorithms to plant, which can be divided into slow and fast subsystems [22].…”

Section: Introductionmentioning

confidence: 99%

“…When the free times are not used for the improvement of MPC algorithms, UMPC has energy efficiency according to the original MPC. The method can be applied to the MPC methods [4][5][6][7][8][9][10][11][12][13][14][15][16][17][18][19][20][21][22], and extended to nonlinear plant models. In the study, the main idea of the method and its application results on a simulation are discussed.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

A Fast Strategy for Model Predictive Control

Dundar

Cihanbegendi

2020

int.jour.sci.res.mana.

View full text Add to dashboard Cite

This article proposes a method to speed the slow response issues (rise time, settling time and prediction) of the existing MPC algorithms up due to the computation load of online optimization without reducing computation load. In the method, original MPC strategy is warped using an integer time scaling factor in time domain. The aim is to speed this strategy up by exploiting the speeds of fast microprocessors. For this aim, an integer time scaling factor is selected according to the limit of the used microprocessor. The solution of the plant is contracted and sampled by this scaling factor. Standard MPC problem is based on this modification of the plant. First elements of fast computed control law vectors are dilated until original online optimization sampling period is reached again and applied to plant at each sampling period. Modified MPC strategy, which is called Upsampled MPC (UMPC), settles faster to desired output than original MPC strategy and also satisfies faster prediction at each sampling period. Since the method is more compatible with fast microprocessor and speed of the UMPC results from microprocessor, slow operation issue of MPC algorithms is solved for different time scaling factors by this method. Therefore, control energy of UMPC is lower. There also exists free times between online optimization sampling periods of original MPC and UMPC strategies. These free times can be used for improvement of existing MPC algorithms.

show abstract

“…The solution pairs (21)(22)(23) and (24)(25) satisfy the equation (10) under the condition (11) [24].…”

Section: Time Scaling and Upsampled Solutions Of Lti Plantmentioning

confidence: 99%

“…• Implementing the combination of the slow and fast MPC algorithms to plant, which can be divided into slow and fast subsystems [22].…”

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

A Fast Strategy for Model Predictive Control

Dundar

Cihanbegendi

2020

int.jour.sci.res.mana.

View full text Add to dashboard Cite

show abstract

“…This algorithm can only be applied to the point ∈ Θ, where Θ is defined by (19). If ∉ Θ, it can not be guaranteed that we can compute > 0, = 1, .…”

Section: Remarkmentioning

confidence: 99%

“…As known to all, the wind conversion systems include mechanical part and electromagnetic part, and the time scales of mechanical dynamics (slow) and electrical dynamics (fast) are quite different from each other [2,19]. So the wind conversion systems have two-time-scale property, which means these kinds of systems have high dimension and stiffness problems.…”

Section: Introductionmentioning

confidence: 99%

Robust Control of Wind Turbines by Using Singular Perturbation Method and Linear Parameter Varying Model

Yan

Liu

Yang

et al. 2016

Journal of Control Science and Engineering

Self Cite

View full text Add to dashboard Cite

The maximum power point tracking problem of variable-speed wind turbine systems is studied in this paper. The wind conversion systems contain both mechanical part and electromagnetic part, which means the systems have time scale property. The wind turbine systems are modeled using singular perturbation methodology. A linear parameter varying (LPV) model is developed to approximate the nonlinear singularly perturbed model. Then stability and robust properties of the open-loop linear singularly perturbed system are analyzed using linear matrix inequalities (LMIs). An algorithm of designing a stabilizing state-feedback controller is proposed which can guarantee the robust property of the closed-loop system. Two numerical examples are provided to demonstrate the effectiveness of the control scheme proposed.

show abstract

Combined model predictive control and scheduling with dominant time constant compensation

Beal

Park

Petersen

et al. 2017

Computers & Chemical Engineering

View full text Add to dashboard Cite

Linear model predictive control is extended to both control and optimize a product grade schedule. The proposed methods are time scaling of the linear dynamics based on throughput rates and grade-based objectives for product scheduling based on a mathematical program with complementarity constraints. The linear model is adjusted with a residence time approximation to timescale the dynamics based on throughput. Although nonlinear models directly account for changing dynamics, the model form is restricted to linear differential equations to enable fast online cycle times for large-scale and real-time systems. This method of extending a linear time-invariant model for scheduling is designed for many advanced control applications that currently use linear models. Simultaneous product switching and grade target management is demonstrated on a reactor benchmark application. The objective is a continuous form of discrete ranges for product targets and economic terms that maximize overall profitability.

show abstract

Time scale analysis and synthesis for Model Predictive Control under stochastic environments

Cited by 7 publications

References 11 publications

A Fast Strategy for Model Predictive Control

A Fast Strategy for Model Predictive Control

Robust Control of Wind Turbines by Using Singular Perturbation Method and Linear Parameter Varying Model

Combined model predictive control and scheduling with dominant time constant compensation

Contact Info

Product

Resources

About