Efficient Model Predictive Control Algorithm for Aircraft

Gibbens, Peter W.; Medagoda, Eran D. B.

doi:10.2514/1.52162

Cited by 34 publications

(26 citation statements)

References 16 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The future states resulting from control inputs given at the current time can be evaluated by applying a moving prediction horizon. These points in the moving prediction horizon will be referred to as prediction points [2]. General MPC formulations take the prediction horizon as the length of the moving time horizon and predict future outputs and controls.…”

Section: General Model Predictive Controlmentioning

confidence: 99%

“…Model predictive control (MPC) is popular because it is one of the few control methodologies that can stabilize both linear and nonlinear systems [1]. In the past 20 years, applications of MPC have grown steadily, and MPC is now in widespread use, particularly in the aerospace field [2][3][4][5], the process industry [6][7][8], and mechanical systems [9][10][11]. The popularity of the method is the result of the strong theoretical background that has been developed over the past few years, the development of efficient optimization algorithms and codes, and the substantial increase in computational power [1].…”

Section: Introductionmentioning

confidence: 99%

“…The objective of MPC is to determine an optimal control sequence online that minimizes the cost of reaching a reference condition within a given prediction horizon given knowledge of the system dynamics and current information [2]. However, for high sampling rates and large-scale systems, the computational time required by MPC becomes a limitation of the method [1].…”

Section: Introductionmentioning

confidence: 99%

“…Other methods for fast implementations of MPC have involved the design of the optimization algorithm for online solutions such as custom integrated circuit architecture [20], the online active-set qpOASES method [21], the interior-point method, and fast gradient methods. Recently, an algebraic model predictive control (AMPC) algorithm using fewer prediction points was introduced to reduce the number of computations [2]. Based on the direct algebraic solution of the state transition matrix and using the eigenvalues and eigenvectors of the system, AMPC is an approximate method that is efficient and accurate.…”

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Fast Model Predictive Control Method for Large-Scale Structural Dynamic Systems: Computational Aspects

Peng

Gao

et al. 2014

Shock and Vibration

View full text Add to dashboard Cite

A fast and accurate model predictive control method is presented for dynamic systems representing large-scale structures. The fast model predictive control formulation is based on highly efficient computations of the state transition matrix, that is, the matrix exponential, using an improved precise integration method. The enhanced efficiency for model predictive control is achieved by exploiting the sparse structure of the matrix exponential at each discrete time step. Accuracy is maintained using the precise integration method. Compared with the general model predictive control method, the reduced central processing unit (CPU) time required by the fast model predictive control scheme can result in a shorter control update interval and a lower online computational burden. Therefore, the proposed method is more efficient for large-scale structural dynamic systems.

show abstract

Section: General Model Predictive Controlmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Fast Model Predictive Control Method for Large-Scale Structural Dynamic Systems: Computational Aspects

Peng

Gao

et al. 2014

Shock and Vibration

View full text Add to dashboard Cite

show abstract

“…(Gibbens and Medagoda, 2011;Lamburn, et al, 2014;Medagoda and Gibbens, 2014;Medagoda and Gibbens, 2010). …”

Section: Other Control Schemesmentioning

confidence: 99%

1-Bit processing based model predictive control for fractionated satellite missions

Bai

2014

Acta Astronautica

View full text Add to dashboard Cite

In this thesis, a 1-bit processing based Model Predictive Control (OBMPC) structure is proposed for a fractionated satellite attitude control mission. Despite the appealing advantages of the MPC algorithm towards constrained MIMO control applications, implementing the MPC algorithm onboard a small satellite is certainly challenging due to the limited onboard resources. The proposed design is based on the 1-bit processing concept, which takes advantage of the affine relation between the 1-bit state feedback and multi-bit parameters to implement a multiplier free MPC controller.As multipliers are the major power consumer in online optimization, the OBMPC structure is proven to be more efficient in comparison to the conventional MPC implementation in term of power and circuit complexity. The system is in digital control nature, affected by quantization noise introduced by Δ∑ modulators. The stability issues and practical design criteria are also discussed in this work.Some other aspects are considered in this work to complete the control system. Firstly, the implementation of the OBMPC system relies on the 1-bit state feedbacks. Hence, 1-bit sensing components are needed to implement the OBMPC system. While the ∆∑ modulator based Microelectromechanical systems (MEMS) gyroscope is considered in this work, it is possible to implement this concept into other sensing components.Secondly, as the proposed attitude mission is based on the wireless inter-satellite link (ISL), a state estimator is required. However, conventional state estimators will once again introduce multi-bit signals, and compromise the simple, direct implementation of the OBMPC controller. Therefore, the 1-bit state estimator is also designed in this work to satisfy the requirements of the proposed fractionated attitude control mission.The simulation for the OBMPC is based on a 2U CubeSat model in a fractionated satellite structure, in which the payload and actuators are separated from the controller and controlled via the ISL. Matlab simulations and FPGA implementation based performance analysis shows that the OBMPC is feasible for fractionated satellite missions and is advantageous over the conventional MPC controllers. V VI

show abstract

Energy Saving via Integrated Passive and Active Morphing During Maneuvers

Oktay

Sal

2016

Sustainable Aviation

View full text Add to dashboard Cite

Efficient Model Predictive Control Algorithm for Aircraft

Cited by 34 publications

References 16 publications

Fast Model Predictive Control Method for Large-Scale Structural Dynamic Systems: Computational Aspects

Fast Model Predictive Control Method for Large-Scale Structural Dynamic Systems: Computational Aspects

1-Bit processing based model predictive control for fractionated satellite missions

Energy Saving via Integrated Passive and Active Morphing During Maneuvers

Contact Info

Product

Resources

About