Adaptive fuzzy backstepping control for a two continuous stirred tank reactors process based on dynamic surface control approach

Xin, Li-Ping; Yu, Bo; Zhao, Lin; Yu, Jinpeng

doi:10.1016/j.amc.2020.125138

Cited by 26 publications

(18 citation statements)

References 42 publications

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“…Before giving the Theorem 2, the following assumption which is commonly used in DSM (such as in the section 3.2 in [22], the author assumed that the derivative of virtual control input is bounded as a positive constant) should be assumed to be valid throughout this paper: 2 1 1 2 2 3 3 4 4 2 2 3 3 4 4 2 2 2 1 1 1 2 1 2 2 2 2 3 2 3 3 3 2 3 3 3 3 4 3 4 4 1 4 4 1 4 4 1 2 1 2 2 2 4 3 3 4 5 2 2 2 2 3 3 1 1 2 2 1 1 2 3 4 111 2 2 3 3 1min 1 2 2 min 1, 2, 0 , 0 2…”

Section: Arm Dynamic Surface Controller Based On Hgomentioning

confidence: 99%

“…The new states are defined as If the states 3 p and 4 p are known, the system ( 12) is a matched uncertain system. Let the matched uncertainty , 0 1 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 (22) Substituting ( 13) and ( 13) into ( 22) yields…”

Section: High-gain Observermentioning

confidence: 99%

“…For conventional BCM, the computations needed for back-stepping is very tedious and complicated, this is so called the problem of "differential explosion". To solve this problem, the dynamic surface method (DSM) was proposed [22][23]. The DSM not only can suppress the mismatched uncertainties by the step-bystep recursive process like BCM, but also adopt a low-pass filter to avoid the explosiveness of backstepping.…”

Section: Introductionmentioning

confidence: 99%

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Spiking-Free HGO-Based Dynamic Surface Control for Flexible Joint Manipulator with Unmeasurable States

Kong¹,

Wang²,

Yan³

2020

Preprint

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For the flexible joint manipulator control system (FJMCS) with unmeasurable states, a novel partial states feedback control (PSFC) is proposed. Firstly, the unmeasurable states and the uncertainties are observed by a high-gain observer (HGO) simultaneously. Then, a dynamic surface controller is proposed based on the output of the HGO. The newly proposed controller has several advantages over existing methods. First, the proposed controller not only uses the estimate states to avoid using unmeasurable states, but also uses the estimation of uncertainties to enhance the robustness of FJMCS. Second, a novel spike suppression function (SSF) is developed to avoid the estimation spike problem in the existing HGO-based controllers. The closed-loop system stability is proved by the Lyapunov theory. Simulation results demonstrate the effectiveness of the proposed controller.

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Section: Arm Dynamic Surface Controller Based On Hgomentioning

confidence: 99%

Section: High-gain Observermentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Spiking-Free HGO-Based Dynamic Surface Control for Flexible Joint Manipulator with Unmeasurable States

Kong¹,

Wang²,

Yan³

2020

Preprint

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“…However, undesirable features (i.e., strong couplings between variables, disturbances, complicated dynamic characteristics, and time delays) always bring challenges to researchers [5]. In recent years, in addition to the traditional PID controller [6], a lot of advanced control strategies, such as MPC [7][8][9][10][11][12], adaptive control [11,13,14], neural network control [15], robust control [16,17], optimal control [18], supervisory control [3], and expert control [19], have been put forward. MPC is one of the most popular approaches in the field of GCP.…”

Section: Introductionmentioning

confidence: 99%

Process Control of Ball Mill Based on MPC-DO

Chen

Yang

Zhong

et al. 2021

Mathematical Problems in Engineering

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The grinding process of the ball mill is an essential operation in metallurgical concentration plants. Generally, the model of the process is established as a multivariable system characterized with strong coupling and time delay. In previous research, a two-input-two-output model was applied to describe the system, in which some key indicators of the process were ignored. To this end, a three-input-three-output system is proposed to improve the model accuracy. Moreover, some practical and effective control strategies have been studied. The common control methods, including model predictive control (MPC), disturbance observer (DO), and so on, show poor performance when strong external and internal disturbances exist. In this paper, a composite control strategy based on MPC-DO is put forward to realize the control of the three-input-three-output ball mill system. The disturbances of the system consist of external disturbances including fluctuation of ore hardness and internal disturbances including model mismatches and strong couplings. The proposed MPC-DO controller includes a feedback control component based on MPC and a feed-forward compensation component based on DO. The simulation results indicate that the composite control scheme based on MPC-DO has good performance of tracking and anti-interference in process control of the ball mill.

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“…Utilizing Nussbaum disturbance observer, an adaptive tracking dynamic surface backstepping control was designed for high-order strict-feedback nonlinear systems (Aghababa and Moradi, 2020). Adaptive fuzzy controllers along with the backstepping design (Shaocheng et al, 2009; Xin et al, 2020) were developed to control the process of two continuous stirred tank reactors. An adaptive backstepping nonsingular fast terminal sliding mode control (Van et al, 2018) was proposed for the tracking control of robotic manipulators.…”

Section: Introductionmentioning

confidence: 99%

A state augmented adaptive backstepping control of wheeled mobile robots

Ahmadi

Taghadosi

2020

Transactions of the Institute of Measurement and Control

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The present paper aims to design an integrated kinematic/dynamic-based tracking controller for wheeled mobile robots (WMRs) considering motors’ dynamics. By defining a reference WMR, the role of kinematic controller is to not only minimize the posture error which indicates the difference between the reference and actual WMRs, but also to generate a desired path for the actual WMR. The kinematic tracking control problem of WMRs is so challenging if motors’ dynamics, parametric and nonparametric uncertainties and external disturbances are considered. Thus, proposing a dynamic control law alongside a kinematic control is unavoidable. In this study, we propose a new dynamic controller, namely, a state augmented adaptive backstepping such that the desired path is asymptotically tracked. Several numerical results accompanied by 3D simulations of trajectory tracking control of a WMR in ‘Simscape Multibody’ environment and comparisons with two well-designed controllers in the literature are reported to show the high performance of proposed control structure.

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Adaptive fuzzy backstepping control for a two continuous stirred tank reactors process based on dynamic surface control approach

Cited by 26 publications

References 42 publications

Spiking-Free HGO-Based Dynamic Surface Control for Flexible Joint Manipulator with Unmeasurable States

Spiking-Free HGO-Based Dynamic Surface Control for Flexible Joint Manipulator with Unmeasurable States

Process Control of Ball Mill Based on MPC-DO

A state augmented adaptive backstepping control of wheeled mobile robots

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