This paper proposes a novel adaptive super-twisting fractional-order nonsingular terminal sliding mode (AST-FONTSM) control scheme using time delay estimation (TDE) for the cable-driven manipulators. The designed control scheme utilizes TDE to obtain the estimation of system dynamics, and therefore no system dynamic model information will be required. Afterwards, AST and FONTSM schemes are applied to ensure good control performance in both reaching and sliding mode phases. Due to the adoption of AST scheme, good robustness and high control precision are obtained in the reaching phase, while the boundary information of the lumped uncertainties will be no longer required. Thanks to the utilization of FONTSM error dynamics, fast convergence and accurate tracking and strong robustness can be simultaneously ensured in the sliding mode phase. Corresponding comparative simulation and experimental results demonstrate the effectiveness and superiorities of our proposed method over the existing control methods.

Adaptive super-twisting fractional-order nonsingular terminal sliding mode control of cable-driven manipulators.

In this paper, a novel Runge-Kutta (RK) discretization-based model-predictive auto-tuning proportional-integral-derivative controller (RK-PID) is introduced for the control of continuous-time nonlinear systems. The parameters of the PID controller are tuned using RK model of the system through prediction error-square minimization where the predicted information of tracking error provides an enhanced tuning of the parameters. Based on the model-predictive control (MPC) approach, the proposed mechanism provides necessary PID parameter adaptations while generating additive correction terms to assist the initially inadequate PID controller. Efficiency of the proposed mechanism has been tested on two experimental real-time systems: an unstable single-input single-output (SISO) nonlinear magnetic-levitation system and a nonlinear multi-input multi-output (MIMO) liquid-level system. RK-PID has been compared to standard PID, standard nonlinear MPC (NMPC), RK-MPC and conventional sliding-mode control (SMC) methods in terms of control performance, robustness, computational complexity and design issue. The proposed mechanism exhibits acceptable tuning and control performance with very small steady-state tracking errors, and provides very short settling time for parameter convergence.

A novel auto-tuning PID control mechanism for nonlinear systems.

This article focuses on robust adaptive sliding mode control law for uncertain discrete systems with unknown time-varying delay input, where the uncertainty is assumed unknown. The main results of this paper are divided into three phases. In the first phase, we propose a new sliding surface is derived within the Linear Matrix Inequalities (LMIs). In the second phase, using the new sliding surface, the novel Robust Sliding Mode Control (RSMC) is proposed where the upper bound of uncertainty is supposed known. Finally, the novel approach of Robust Adaptive Sliding ModeControl (RASMC) has been defined for this type of systems, where the upper limit of uncertainty which is assumed unknown. In this new approach, we have estimate the upper limit of uncertainties and we have determined the control law based on a sliding surface that will converge to zero. This novel control laws are been validated in simulation on an uncertain numerical system with good results and comparative study. This efficiency is emphasized through the application of the new controls on the two physical systems which are the process trainer PT326 and hydraulic system two tanks.

Robust adaptive sliding mode control for uncertain systems with unknown time-varying delay input.

Sliding mode PI control with backstepping approach for MIMO nonlinear cross‐coupled tank systems

In order to improve the dynamic quality of traditional sliding mode control for an active suspension system, an optimal sliding mode control (OSMC) based on a genetic algorithm (GA) is proposed. First, the overall structure and control principle of the active suspension system are introduced. Second, the mathematical model of the quarter car active suspension system is established. Third, a sliding mode control (SMC) controller is designed to manipulate the active force to control the active suspension system. Fourth, GA is applied to optimize the weight coefficients of an SMC switching function and the parameters of the control law. Finally, the simulation model is built based on MATLAB/Simulink (version 2014a), and the simulations are performed and analyzed with the proposed control strategy to identify its performance. The simulation results show that the OSMC controller tuned using a GA has better control performance than the traditional SMC controller.

https://www.mdpi.com/1999-4893/11/12/205/pdf

Optimal Sliding Mode Control for an Active Suspension System Based on a Genetic Algorithm

Sliding Mode Control, with Integrator, for a Class of Mimo Nonlinear Systems

Multi-objective design of optimal higher order sliding mode control for robust tracking of 2-DoF helicopter system based on metaheuristics

This paper proposes a discrete-time sliding mode control (DT-SMC) algorithm for uncertain linear systems with time-varying delay on the state. The parameter uncertainties and the external disturban...

Robust discrete-time sliding mode control for systems with time-varying state delay and uncertainties on state and control input

In this paper, we propose a new adaptive sliding mode control for nonlinear systems which are affine with respect to control and where the free term of state representation is assumed to be unknown and modelled using Volterra series The proposed control law depends on the estimated parameters of Volterra series The Lyapunov function was defined based on the sliding surface and the errors between the Volterra model parameters and their estimated values The Lyapunov function is defined as positive and decreasing which shows the systems studied An example of simulation and a validation on a real system are performed at the end of this paper to show the effectiveness of this approach

Anouar Benamor

Papers

Robust adaptive sliding mode control for uncertain systems with unknown time-varying delay input.

Sliding Mode Control, with Integrator, for a Class of Mimo Nonlinear Systems

Multi-objective design of optimal higher order sliding mode control for robust tracking of 2-DoF helicopter system based on metaheuristics

Robust discrete-time sliding mode control for systems with time-varying state delay and uncertainties on state and control input

A new adaptive sliding mode control of nonlinear systems using Volterra series: application to hydraulic system