Switching Perfect Control Algorithm

Krok, Marek; Hunek, Wojciech P.; Feliks, Tomasz

doi:10.3390/sym12050816

Cited by 6 publications

(12 citation statements)

References 19 publications

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“…Having dynamic or static properties of the system, it is possible not only to precisely determine the control parameters for the assumed operating point but also to obtain highly positive results of the complex plant operations. This is confirmed, for instance, by the multivariable state-space perfect control procedure, which allows us to receive a reference value for the single-delayed object just after one simulation step time [1,2]. Thus, the proper modeling and identification often provide the efficient control plants.…”

Section: Introductionmentioning

confidence: 92%

Toward Optimal Control of a Multivariable Magnetic Levitation System

et al. 2022

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In the paper, a comparative case study covering different control strategies of unstable and nonlinear magnetic levitation process is investigated. Three control procedures are examined in order to fulfill the specified performance indices. Thus, a dedicated PD regulator along with the hybrid fuzzy logic PID one as well as feed-forward neural network regulator are respected and summarized according to generally understood tuning techniques. It should be emphasized that the second PID controller is strictly derived from both arbitrary chosen membership functions and those ones selected through the genetic algorithm mechanism. Simulation examples have successfully confirmed the correctness of obtained results, especially in terms of entire control process quality of the magnetic levitation system. It has been observed that the artificial-intelligence-originated approaches have outperformed the classical one in the context of control accuracy and control speed properties in contrary to the energy-saving behavior whereby the conventional method has become a leader. The feature-related compromise, which has never been seen before, along with other crucial peculiarities, is effectively discussed within this paper.

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Section: Introductionmentioning

confidence: 92%

Toward Optimal Control of a Multivariable Magnetic Levitation System

et al. 2022

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“…Nevertheless, studies have shown that, in non-square plants, it is possible to reduce the said energy injection even up to 80% in the context of an appropriate choice of so-called degrees of freedom emerging in a properly selected inverse [ 18 ]. Moreover, it is possible to select good control parameters for the selected operating point while maintaining low energy consumption and high accuracy [ 9 , 15 , 18 , 19 , 20 , 21 , 22 ]. However, the reduction mentioned here, even at the level of ten percent, may not be sufficient for some systems.…”

Section: Introductionmentioning

confidence: 99%

A Sensor-Aided System for Physical Perfect Control Applications in the Continuous-Time Domain

Majewski

Hunek

Pawuś

et al. 2023

Sensors

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The recently introduced continuous-time perfect control algorithm has revealed a great potential in terms of the maximum-speed and maximum-accuracy behaviors. However, the discussed inverse model-originated control strategy is associated with considerable energy consumption, which has exceeded a technological limitation in a number of industrial cases. In order to prevent such an important drawback, several solutions could be considered. Therefore, an innovative perfect control scheme devoted to the multivariable real-life objects is investigated in this paper. Henceforth, the new IMC-related approach, strongly supported by the vital sensor-aided system, can successfully be employed in every real-time engineering task, where the precision of conducted processes plays an important role. Theoretical and practical examples strictly confirm the big implementation potential of the new established method over existing ones. It has been seen that the new perfect control algorithm outperforms the classical control law in the form of LQR (considered in two separate ways), which is clearly manifested by almost all simulation examples. For instance, in the case of the multi-tank system, the performance indices ISE, RT, and MOE for LQR without an integration action have been equal to 2.431, 2.4×102, and 3.655×10−6, respectively, whilst the respective values 1.638, 1.58×102, and 1.514×10−7 have been received for the proposed approach.

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“…The inverse model control (IMC) has widely been investigated over the past decades due to its application in many scientific and engineering fields [1], [2], [3], [4], [5], [6], [7], [8], [9], [10], [11], [12], [13], [14], [15], [16], [17], [18], [19], [20], [21], [22], [23], [24], [25]. The unique behaviors of the discussed technique such as robustness, maximumspeed or minimum-energy properties make it attractive in many practical implementations [1], [9], [12], [23], [26], [27], [28].…”

Section: Introductionmentioning

confidence: 99%

“…In fact, the multivariable nonsquare right-invertible plants, i.e. systems with greater number of input than output variables, can also be subjected by such noise-free control law [3]. In such a case, through the application of nonunique parameter/polynomial right inverses, we can redefine the special properties of the closed-loop state-feedback plant [1], [9], [26].…”

Section: Introductionmentioning

confidence: 99%

A New Non-Full Rank Algorithm for the IMC-Derived d-Step MIMO Structures in the Pole-Free State Space

Feliks

Hunek

2020

IEEE Access

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In this paper, the powerful issue of a non-full rank inverse model control investigation is provided. It is broadly known, that the inverse-based methodology is associated with the full-rank control systems only. However, following the recently obtained authors' results in this matter, it should be concluded, that for single-delayed non-full rank state-space plants, the inverse model control-related perfect control expression can also be established. It is shown here, that for all right-and left-oriented multivariable LTI non-full rank systems, including the square ones, governed by the discrete-time statespace domain arranging the zero-reference value, the maximum-speed pole-free instance of such inverse model control strategy can be achieved. Thus, the new non-full rank algorithm does not coincide with the z-transfer-function scenario, which additionally sounds the intriguing peculiarity. The innovative content of the manuscript, that has never been seen before, is strongly supported by the numerical examples. Henceforth, the presented methodology covers the entire set of LTI MIMO state-space-oriented plants in the discrete-time domain, which is also a consequence of conducted research investigation in the past. INDEX TERMS Non-full rank, perfect control procedure, Moore-Penrose inverse, generalized inverses, skeleton factorization, pole-free delayed plants, discrete-time state-space MIMO structures

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Switching Perfect Control Algorithm

Cited by 6 publications

References 19 publications

Toward Optimal Control of a Multivariable Magnetic Levitation System

Toward Optimal Control of a Multivariable Magnetic Levitation System

A Sensor-Aided System for Physical Perfect Control Applications in the Continuous-Time Domain

A New Non-Full Rank Algorithm for the IMC-Derived d-Step MIMO Structures in the Pole-Free State Space

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