Asynchronous sliding mode dissipative control for discrete-time Markov jump systems with application to automotive electronic throttle body control system

Zhang, Xiang; Zhang, Guangchen; Yin, Yanyan; He, Shuping

doi:10.1016/j.compeleceng.2021.107496

Cited by 8 publications

(7 citation statements)

References 17 publications

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“…That is to say, the precise system mode

{r}_t

are not available for the controller design. Therefore, it is natural to consider MJSs with partial mode information 22,28‐30 . Similar to Reference 29, a HMMD

\left({r}_t,{\hat{r}}_t\right)

is utilized to characterize the nonsynchronous phenomenon between the controller and the system

{\mu}_{ih}=\Pr \left\{{\hat{r}}_t=h\kern.17em |\kern.17em {r}_t=i\right\},\kern0.5em

where

i \in 𝒩

h\in \mathcal{M}

\mathcal{M}\triangleq \left\{1,2,\dots, M\right\}

{\mu}_{ih}\in \left[0,\kern0.3em 1\right]

is the mode detection probability with

{\sum}_{h=1}^M\kern.17em {\mu}_{ih}=1

for any

i \in 𝒩

.…”

Section: Resultsmentioning

confidence: 99%

“…Therefore, it is natural to consider MJSs with partial mode information. 22,[28][29][30] Similar to Reference 29, a HMMD (r t , rt ) is utilized to characterize the nonsynchronous phenomenon between the controller and the system…”

Section: Design Of Hybrid Asynchronous Sliding Mode Controlmentioning

confidence: 99%

“…By taking condition (30) and 𝜋 ii = − ∑ N j=1,j≠i 𝜋 ij into consideration and resorting to the Schur complement, ( 29) is guaranteed by (20). In addition, the equation constraints P i ZB i = 𝜙 i I and Z T P i Z = X i are equivalent to (19), which will facilitate the solution algorithm later in Section 4.…”

Section: Reachability Analysismentioning

confidence: 99%

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Hybrid asynchronous sliding mode control for hidden Markovian jump systems under optimized design

Zhou

Song

Yang

2022

Intl J Robust & Nonlinear

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This article is concerned with the hybrid design of transition rates and asynchronous sliding mode control (SMC) law for continuous‐time Markovian jump systems with matched disturbances. First, a sufficient condition is established to ensure the stochastic ultimate boundedness (SUB) of the unforced systems, which are driven only by using the designed stabilizing transition rates. Furthermore, by considering the system modes are unavailable for the controller, a hidden Markov mode detector is introduced to emit the detection modes. Based on the mode detection probabilities, a hybrid design approach is proposed by co‐designing of transition rates and asynchronous SMC law, which ensures the SUB and disturbance attenuation performance of the resulted closed‐loop systems. The obtained sufficient conditions are solved via two iterative optimization algorithms, which combine cone complementarity linearization and genetic algorithm. Finally, a numerical example with three comparison cases is provided to illustrate the proposed results.

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“…That is to say, the precise system mode

{r}_t

are not available for the controller design. Therefore, it is natural to consider MJSs with partial mode information 22,28‐30 . Similar to Reference 29, a HMMD

\left({r}_t,{\hat{r}}_t\right)

is utilized to characterize the nonsynchronous phenomenon between the controller and the system

{\mu}_{ih}=\Pr \left\{{\hat{r}}_t=h\kern.17em |\kern.17em {r}_t=i\right\},\kern0.5em

where

i \in 𝒩

h\in \mathcal{M}

\mathcal{M}\triangleq \left\{1,2,\dots, M\right\}

{\mu}_{ih}\in \left[0,\kern0.3em 1\right]

is the mode detection probability with

{\sum}_{h=1}^M\kern.17em {\mu}_{ih}=1

for any

i \in 𝒩

.…”

Section: Resultsmentioning

confidence: 99%

Section: Design Of Hybrid Asynchronous Sliding Mode Controlmentioning

confidence: 99%

See 1 more Smart Citation

Hybrid asynchronous sliding mode control for hidden Markovian jump systems under optimized design

Zhou

Song

Yang

2022

Intl J Robust & Nonlinear

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show abstract

“…It randomly searches the global scope to find the optimal solution. The bounds of e(k) and x(k) are depicted by (18) and (19). The smaller the bounds, the better the estimate and control performance.…”

Section: Gasmentioning

confidence: 99%

Event‐triggered disturbance rejection control for Markov jump systems: A GA‐optimized approach

Zhang,

Cheng,

Chen

et al. 2024

Asian Journal of Control

Self Cite

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This paper investigates the event‐triggered disturbance rejection control problem for discrete‐time Markov jump systems by means of genetic algorithms. Firstly, an extended state observer is developed to estimate the system states and disturbances and construct the event‐triggered disturbance rejection controller. With resort to Lyapunov theory, the uniform ultimate boundedness of both estimated errors and states is guaranteed. The disturbance rejection performance is also analyzed. The genetic algorithm is adopted to avoid conservatism in solving the given nonlinear conditions and achieve a meaningful optimization arising from realizing better system performance. The designed approach not only realizes a trade‐off between the bounds of estimated errors and states but also rejects the disturbance. Finally, an example is given to illustrate the effectiveness of the proposed approach.

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“…The topics of this type of research range from the first-order SMC 3 , 4 , high-order SMC 5 , and discrete-time SMC 6 to terminal SMC 7 as well as event-triggered SMC 8 . With several advantages in order to delivery robust and stable performance to a wide class of systems, the SMC technique has been implemented as an automatic controller for numerous applications in the fields of robotics 9 , industrial automation 10 , 11 , power electronics 12 , automotive 13 , autonomous ground vehicles 14 , and aerospace [15][16][17] .…”

Section: Introductionmentioning

confidence: 99%

On the Sliding Mode Control Gain-Tuning: Novel Method and Experimental Verification

Xuan-Mung

Nguyen

Pham

et al. 2022

Preprint

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The sliding mode control is well-known as a useful control technique that can be applied in several real-world applications. However, a straightforward and efficient process of tuning the gains of a sliding mode controller remains a challenging but interesting topic. In this paper, a mathematical method for the sliding mode controller gain tuning is investigated. Firstly, we obtain relations between the gains and the natural and damping ratio of the closed-loop system. Secondly, the time constant of the system's actuators and the system response performance criteria, including settling time and delay time, are taken into consideration to determine the gains. In addition, appropriate gain ranges, which ensure that the system performance is met and the actuators work properly, are derived. Finally, the proposed method is applied to the gain tuning process of a sliding mode altitude controller for an actual quadcopter unmanned aerial vehicle. Simulation and experimental results demonstrate the applicability and effectiveness of this method.

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Asynchronous sliding mode dissipative control for discrete-time Markov jump systems with application to automotive electronic throttle body control system

Cited by 8 publications

References 17 publications

Hybrid asynchronous sliding mode control for hidden Markovian jump systems under optimized design

Hybrid asynchronous sliding mode control for hidden Markovian jump systems under optimized design

Event‐triggered disturbance rejection control for Markov jump systems: A GA‐optimized approach

On the Sliding Mode Control Gain-Tuning: Novel Method and Experimental Verification

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