Optimal control of Buck converter by state feedback linearization

Shuai, Dingxin; Xie, Yunxiang; Wang, Xiaogang

doi:10.1109/wcica.2008.4593275

Cited by 32 publications

(8 citation statements)

References 8 publications

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“…Traditional techniques, such as state-feedback, optimal control, and PID control, which are based on first principles, can partly accomplish these goals. Nevertheless, they may not effectively respond to sudden process changes or malfunctions [53,58]. Tab.…”

Section: Control Theorymentioning

confidence: 99%

State‐of‐the‐Art Review on the Applications of Nonlinear and Artificial Intelligence‐Based Controllers in Petrochemical Processes

Ansari

Taqvi

2023

ChemBioEng Reviews

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Petrochemical industries are facing severe challenges in controlling nonlinear processes which are to be analyzed and monitored to develop efficient control models for improved efficiency and productivity. This review focuses on the control theory of petrochemical processes along with linear and nonlinear controllers with their limitations as well as on the application of artificial intelligence (AI)‐based controllers in multiple sectors of petrochemical industries. The findings and results from the review prove that the AI control technique is a promising one in the future for uncertain dynamic systems. The paper also covers a review of the vinyl chloride monomer (VCM) process and a recent control study on the plant. Being a nonlinear system, VCM requires advanced control techniques to control the uncertain dynamics of the process. The study shows a gap in the development of control strategies applied to VCM in terms of sustainability, efficiency, and environment‐concerned issues. Valuable insights for researchers, practitioners, and engineers engaged in process control and automation in the petrochemical industry are provided.

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Section: Control Theorymentioning

confidence: 99%

State‐of‐the‐Art Review on the Applications of Nonlinear and Artificial Intelligence‐Based Controllers in Petrochemical Processes

Ansari

Taqvi

2023

ChemBioEng Reviews

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show abstract

“…In [14], it designs a nonlinear controller based on Lyapunov function, and it proves that it has global stability, good dynamic and static characteristics, but its computational complexity and difficult to implement. Using the optimal control method in switching power converter achieves a stable operation in a wide range when the system operates in a large fluctuation range and the controller has a strong follower performance, and it also improve the system dynamic performance significantly [15][16]. The optimal control of nonlinear systems generally look for objective functional performance indicators and obtain the minimum value of the objective function along all possible trajectories of the system, so this problem is usually considered to resolve partial differential equations for the Hamilton-Jacobi-Bellman, but solving Hamilton-Jacobi-Bellman is very difficult in most cases.…”

Section: Introductionmentioning

confidence: 99%

An Optimal Control Scheme for Single-Phase Grid-Connected Photovoltaic Inverter

Zhang¹,

Yang²,

Liu³

et al. 2014

JCP

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In this paper, an optimal control scheme for single-phase grid-connected photovoltaic inverter is proposed. Besides a nonlinear mathematical model of the inverter in the DQ rotating coordinate is constructed. In addition, the designed controller has weaker dependence on the parameters of the system by selecting the appropriate performance control matrix. The simulation works show that this method can achieve zero steady-state error, has a good dynamic and static response, and it ensures that the system is robust in the case of parameters variations and fluctuations.

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“…Sliding mode control having strong robustness and stability in a wide margin has been proved in [15,16], but it cannot eliminate the steady-state error and also has oscillation problem. Optimal nonlinear control method using the power converter has been proposed in [17][18][19], and it has proved that the method can operate in a stable way in a wide fluctuating range and has strong robustness. Moreover, [17][18][19][20] also point out that the optimal control is more suitable for trajectory tracking problem, which also proves its stability and effectiveness, and [21,22] also focus on the optimal control and prove that this method has good performance.…”

Section: Introductionmentioning

confidence: 99%

“…Optimal nonlinear control method using the power converter has been proposed in [17][18][19], and it has proved that the method can operate in a stable way in a wide fluctuating range and has strong robustness. Moreover, [17][18][19][20] also point out that the optimal control is more suitable for trajectory tracking problem, which also proves its stability and effectiveness, and [21,22] also focus on the optimal control and prove that this method has good performance. Photovoltaic grid-connected inverter also can be considered in the current trajectory tracking problem, and using the optimal control can significantly improve performances of the system.…”

Section: Introductionmentioning

confidence: 99%

Discrete-Time Optimal Control of Photovoltaic Grid-Connected Inverter Based on Particle Swarm Optimization

Liu

Zhang

Yang

et al. 2014

Mathematical Problems in Engineering

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This paper is concerned with the problem of optimal control of photovoltaic grid-connected inverter. Firstly, the discrete-time nonlinear mathematical model of single-phase photovoltaic grid-connected inverter in the rotating coordinate system is constructed by the Delta operator, which simplifies the control process and facilitates direct digital realization. Then, a novel optimal control method which is significant to achieve trajectory tracking for photovoltaic grid-connected inverter is developed by constructing a control Lyapunov functional against the difficulty of solving HJB (Hamilton-Jacobi-Bellman) partial differential equations. More importantly, the performance matrix of the controller which is very meaningful to many performance indicators of the system is also optimized via the particle swarm optimization. Finally, two numerical examples are provided to illustrate the effectiveness of the proposed method.

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Optimal control of Buck converter by state feedback linearization

Cited by 32 publications

References 8 publications

State‐of‐the‐Art Review on the Applications of Nonlinear and Artificial Intelligence‐Based Controllers in Petrochemical Processes

State‐of‐the‐Art Review on the Applications of Nonlinear and Artificial Intelligence‐Based Controllers in Petrochemical Processes

An Optimal Control Scheme for Single-Phase Grid-Connected Photovoltaic Inverter

Discrete-Time Optimal Control of Photovoltaic Grid-Connected Inverter Based on Particle Swarm Optimization

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