Wyniki wyszukiwania - BazTech

1

Non‐linear model‐based predictive control for trajectory tracking and control effort minimization in a smartphone‐based quadrotor

García Luis, Rosero Esteban

Journal of Automation Mobile Robotics and Intelligent Systems

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2022

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Vol. 16, No. 4

13--18

EN

In this paper, the design and implementation of a nonlinear model‐based predictive controller (NMPC) for predefined trajectory tracking and to minimize the control effort of a smartphone‐based quadrotor are developed. The optimal control actions are calculated in each iteration by means of an optimal control algorithm based on the non‐linear model of the quadrotor, considering some aerodynamic effects. Control algorithm implementation and simulation tests are executed on a smartphone using the CasADi framework. In addition, a technique for estimating the energy consumed based on control signals is presented. NMPC controller performance was compared with other works developed towards the con‐ trol of quadrotors, based on an H∞ controller and an LQI controller, and using three predefined trajectories, where the NMPC average tracking error was around 50% lower, and average estimated power and energy consumption slightly higher, with respect to the H∞ and LQI controllers.

2

Specialized genetic operators in drinking water distribution systems control

Cimiński A., Duzinkiewicz K.

Prace Naukowe Politechniki Warszawskiej. Elektronika

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2009

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z. 169

35-42

EN

Model-based predictive control (MPC) is an effective method for control of the large scale systems. The method relying on repeating applying the first element of the calculated control sequence to the system, based on the model of the system and available system output measurements. A time duration of control calculation is a crucial criterion for applying this method. In this paper effective algorithm of control the drinking water distribution system (DWDS) is presented. Algorithm is based on genetic algorithm (GA), specialized genetic operators (SPO) and simulator Epanet. To improve the GA convergence, specialized genetic operators based on system operator knowledge of practical system control are proposed. Effectiveness of proposed specialized genetic operators on the example DWDS of the Chojnice city is presented.

3

Suboptimal model predictive control for MIMO active suspension

Ogonowski Z.

Mechanics / AGH University of Science and Technology

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2005

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Vol. 24, no. 2

130-134

EN

The paper presents nonlinear Model Predictive Control algorithm applied to full-active four-dimensional magnetic bearing system MBC500 being produced by Magnetic Moments, USA. The system is nonlinear due to the measurement units and the current amplifiers (actuators). Nonlinear model of the system has been established basing on the phenomenological description with parameters identified. The model is used to predict response of the suspension system. The control law bases on this prediction as it is in the linear case. However, in the nonlinear case this control law is suboptimal because it assures only that the states and controls are feasible. The feasibility means that the rotating shaft-ends deviation form the nominal position is below the limit as well as the control signals do not exceed constraints. The performance of the active suspension control system is compared with lead compensators being build in the MBC500 system as well as with weighted minimumvariance control and linear quadratic regulator with observer. It is shown that nonlinear MIMO predictive control assures significant improvement of the control quality.

PL

W pracy przedstawiony jest nieliniowy algorytm sterowania predykcyjnego zastosowanego do aktywnego tłumienia drgań w zawieszeniu magnetycznym laboratoryjnego modelu maszyny wirnikowej MBC500 firmy Magnetic Moments. Sterowany obiekt jest nieliniowy z uwagi na hallotronowy pomiar położenia końców wirującego wałka oraz nieliniową charakterystykę wzmacniaczy prądowych zasilających układ elektromagnetyczny. Parametry nieliniowego modelu fenomenologicznego zostały zidentyfikowane specjalną procedurą optymalizacyjną. Za pomocą modelu wyznacza się predykcję wyjścia układu drgającego podczas wirowania wału. Predykcję wykorzystuje się do obliczania sterowania. Nieliniowość powoduje jednak, że tak sformułowane prawo sterowania nie jest optymalne ze względu na kwadratowy wskaźnik jakości. Jednakże dopuszczalność rozwiązania w sensie spełnienia ograniczeń na przemieszczenia końców wałka zapewnia stabilność układu. Jego działanie porównane jest w pracy z działaniem wbudowanych regulatorów PD, regulatora minimalizującego wariancję oraz regulatora liniowo-kwadratowego.

4

Fuzzy adaptive-predictive decentralized control of discrete time interconnected systems

Tzafestas S., Kyriannakis E., Apostolikas G.

Systems Science

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2002

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Vol. 28, nr 1

5-24

EN

Proposes an approach for the design of discrete-time decentralized control systems with m-step delay sharing information pattern, employing model-based predictive control (MBPC) combined with fuzzy prediction for the interconnections among the subsystems. A state space model is used at each control station to predict the corresponding subsystem output over a long-range time period. The interaction trajectories are considered to be non-linear functions of the states of the subsystems. For all cases the interconnections and the necessary predictions for them are estimated by an appropriate adaptive fuzzy identifier based on the generation of linguistic IF-THEN rules and the on-line construction of a common fuzzy rule base. Representative computer simulation results are provided and compared for nontrivial example systems.

5

Ehmac - a New Simple Tool for Robust Linear Multivariable Control

Latawiec K. J., Rojek R.

International Journal of Applied Mathematics and Computer Science

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2000

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Vol. 10, no 3

575-590

EN

A combination of long range predictive control-originated EHPC and internal model control-structured MAC is shown to produce a new, simple but effective Extended Horizon Model Algorithmic Control (EHMAC). The EHMAC strategy can be used to robustly control open-loop stable non-minimum phase (possibly non-square) MIMO systems under very large model-plant mismatches. Robust EHMAC design is made straightforward by means of a separate selection of a single prediction horizon and an IMC filter parameter, which can be easily auto-tuned.

6

Adaptive Predictive Controller Using Orthonormal Series Functions

Oliveira G. H. C., Amaral W. C., Favier G.

International Journal of Applied Mathematics and Computer Science

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1999

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Vol. 9, no 1

175-191

EN

A constrained adaptive predictive control method that uses uncertain process modelling based on orthonormal series functions is considered. Such unstructured modelling is described as a weighted sum of orthonormal functions using approximate information about the time constant of the process. The orthonormal series functions model can thus be used to derive a j-step-ahead output prediction according to the constrained adaptive predictive control law. In relation to predictive controllers based on structured models, this approach presents the advantage of not requiring prior knowledge of the order or time delay, which decrease prediction errors and lead to a better closed loop performance when these parameters are not well known. Stability issues of the proposed control scheme are discussed and, finally, a simulation example is given to show the performance of the algorithm.