Discrete-Time Adaptive Controller Based on Estimated Pseudopartial Derivative and Reaching Sliding Condition

2016 ◽  
Vol 138 (10) ◽  
Author(s):  
Chidentree Treesatayapun
Keyword(s):  
Discrete Time ◽  
Sliding Mode ◽  
Direct Method ◽  
Experimental System ◽  
Adaptive Controller ◽  
Current Control ◽  
Lyapunov Direct Method ◽  
Model Free ◽  
Control Scheme ◽  
Time Systems

An adaptive controller based on sliding mode condition is developed with estimated pseudopartial derivative (PPD) of data-driven scheme. The controlled plant is considered as a class of unknown discrete-time systems with only output feedback, which allows the proposed controller to be applicable for practical plants operated by computerization systems. The convergence of estimated PPD is analyzed by Lyapunov direct method under reasonable assumptions. The control law is derived by the estimated PPD and reaching condition of sliding surface as a model-free of controlled plant. The performance of the proposed control scheme is validated by theoretical analysis and experimental system with direct current (DC) motor current control.

Discrete-Time Sliding Mode Controller With Time-Varying Band for Unfixed Sampling-Time Systems

2018 ◽  
Vol 140 (11) ◽  
Author(s):  
Chidentree Treesatayapun
Keyword(s):  
Discrete Time ◽  
Sliding Mode ◽  
Fuzzy Rule ◽  
Current Control ◽  
Sampling Time ◽  
Control Law ◽  
Time Varying ◽  
Control Effort ◽  
Time Systems ◽  
The Mathematical Model

An adaptive discrete-time controller is developed for a class of practical plants when the mathematical model is unknown and the sampling time is nonconstant or unfixed. The data-driven model is established by the set of plant's input–output data under the pseudo-partial derivative (PPD) which represents the change of output with respect to the change of control effort. The multi-input fuzzy rule emulated network (MiFREN) is utilized to estimate PPD with an online-learning phase to tune all adjustable parameters of MiFREN with the convergence analysis. The proposed control law is developed by the discrete-time sliding mode control (DSMC), and the time-varying band is established according to the unfixed sampling time and unknown boundaries of disturbances and uncertainties. The prototype of direct current-motor current control with uncontrolled-sampling time is constructed to validate the performance of the proposed controller.

Robust predictive sliding mode control for input rate-constrained discrete-time system

2018 ◽  
Vol 36 (3) ◽  
pp. 901-919 ◽  
Author(s):  
Rong Li ◽  
Qingxian Wu
Keyword(s):  
Sliding Mode Control ◽  
Discrete Time ◽  
Sliding Mode ◽  
Input Rate ◽  
Discrete Time System ◽  
Control Approach ◽  
Mode Control ◽  
Discrete Time Systems ◽  
Control Scheme ◽  
Time Systems

Abstract This paper investigates a class of uncertain linear discrete-time systems subject to input rate saturation. A predictive sliding mode control approach is proposed which guarantees the control inputs remain bounded in the input rate saturation. Furthermore, the disturbance observer is developed to compensate for the system uncertainty and disturbance. Finally, the simulations demonstrate the effectiveness of the proposed predictive sliding mode control scheme.

scholarly journals Reaching Law Based Sliding Mode Control of Sampled Time Systems

Energies ◽  
2021 ◽  
Vol 14 (7) ◽  
pp. 1882
Author(s):  
Piotr Leśniewski ◽  
Andrzej Bartoszewicz
Keyword(s):  
Sliding Mode Control ◽  
Discrete Time ◽  
Sliding Mode ◽  
Rate Of Change ◽  
Reaching Law ◽  
Mode Control ◽  
Sliding Motion ◽  
Control Precision ◽  
Continuous Time Systems ◽  
Time Systems

In this paper, discrete time reaching law-based sliding mode control of continuous time systems is considered. In sliding mode control methods, usually the assumption of bounded absolute values of disturbances is used. However in many cases, the rate of change of the disturbance is also bounded. In the presented approach, this knowledge is used to improve the control precision and reduce the undesirable chattering. Another advantage of the proposed method is that the disturbance does not have to satisfy the matching conditions. In the paper two new reaching laws are analyzed, one of them ensures the switching quasi-sliding motion and the other the non-switching motion. For both of them, the robustness is assessed by calculating the quasi-sliding mode band width, as well as the greatest possible state error values. Specifically, the state errors are not considered only at the sampling instants, as is usual for discrete time systems, but the bounds on the continuous values “between” the sampling instants are also derived. Then, the proposed approaches are compared and analyzed with respect to energy expenditure of the control signal.

scholarly journals Adaptive PD Sliding Mode Control For 4 DOF SCARA Variant

2021 ◽  
Author(s):  
Manjeet Tummalapalli
Keyword(s):  
Sliding Mode Control ◽  
Trajectory Tracking ◽  
High Speed ◽  
Sliding Mode ◽  
Adaptive Controller ◽  
Degree Of Freedom ◽  
Tracking Performance ◽  
Advantages And Disadvantages ◽  
Model Free ◽  
Adaptive Law

This project proposes a new SCARA variant with 4 degree of freedom. The proposed variant is achieved by swapping joint 2 and joint 3 of the standard SCARA robots. An adaptive controller is defined based on the advantages and disadvantages of PD, and SMC controllers.The purpose of the project is to understand the dynamics of the variant and to track the performance for trajectories. Simulations for tracking performance are carried under linear and circular trajectories. The variant is studied over the three controllers; PD, PD-SMC and A-PD-SMC. The variant under the adaptive controller is most efficient in terms of tracking performance and the control inputs to the system. The system is simulated under high speed and with the influence of friction at the joints. The control gains are held constant for both the trajectories and hence the controller is able to perform good under changing trajectories. Due to the use of the adaptive law, the system is at the ease of implementation and since no priori knowledge if the system is needed, it is model free. Therefore, the proposed adaptive PD-SMC has proven to provide good, robust trajectory tracking.

Model-free adaptive PID control for nonlinear discrete-time systems

2020 ◽  
Vol 42 (10) ◽  
pp. 1797-1807 ◽  
Author(s):  
Shuhua Zhang ◽  
Ronghu Chi
Keyword(s):  
Discrete Time ◽  
Mathematical Analysis ◽  
Pid Control ◽  
Contraction Mapping Principle ◽  
Unknown Parameters ◽  
Model Free ◽  
Discrete Time Systems ◽  
Gradient Parameter ◽  
Adaptive Pid Control ◽  
Time Systems

This work explores a model-free adaptive PID (MFA-PID) control for nonlinear discrete-time systems with rigorous mathematical analysis under a data-driven framework. An improved compact form dynamic linearization (iCFDL) is proposed to transfer the original nonlinear system into an affined linear data model including a nonlinear residual term. Both a time-difference estimator and a gradient parameter estimator are designed to estimate the nonlinear residual uncertainties and the unknown parameters in the iCFDL model. Subsequently, a novel improved CFDL based MFA-PID (iCFDL-MFA-PID) control is proposed by incorporating these two estimators. The results are extended by the use of improved partial format dynamic linearization (iPFDL) and full format dynamic linearization (iFFDL). The theoretical results are shown using contraction mapping principle-based mathematical analysis, as well as simulations.

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