Decoupled Sliding Mode Control Research Articles

Design of a Decoupled Sliding Mode Control for Four-Leg Distribution Static Compensator

In the conventional sliding mode control, the four-leg distribution static compensator (DSTATCOM) currents are controlled based on a current error in each phase. However, the four currents in a four-wire system can not be independently controlled variables and hence one of the four controllers is redundant in conventional schemes. Further, the current dynamics of a DSTATCOM converter are coupled through converter pole voltages in the natural reference frame. This leads to cross-coupling in the sliding variable equations with respect to four manipulated input variables. Considering the above points, in this paper, the current due to Thevenin’s equivalent load neutral-point voltage is considered as a fourth independent controlled variable and the corresponding system dynamic equations are presented. To get a decoupled feature, a new sliding surface function is structured. The performance of a DSTATCOM with the proposed control scheme under various operating conditions is validated through a detailed simulation study and experimental results, obtained from a laboratory prototype of four-leg DSTATCOM.

Analysis of single input dual output buck converter with reduced cross regulation using decoupled sliding mode control strategy

AbstractIn the present scenario, single input dual output (SIDO) converters are remarkably required for wide range of applications, as it is capable of handling two outputs with a single source. The general advantages of SIDO converters are reduced number of components in the topology; power rating can be increased or decreased depending on the application and it ease of control. However, it faces with a common problem of cross regulation occurring due to the change of load in anyone of the load terminals. This paper proposes a control technique for a SIDO buck converter (SIDO‐BC) to have a mitigated cross regulation scenario during load change. Decoupled sliding mode controller (D‐SMC) is developed for the SIDO‐BC by considering the boundary limits of the inductor current. The D‐SMC‐based SIDO‐BC provides better output regulation with mitigated cross regulation when compared to the conventional techniques. The topological small signal model derivation of the SIDO‐BC is firmly derived, and the controller is designed and developed in such way to provide a stabilized regulated output. The entire system is implemented in simulation and in experimental hardware to validate the performance.

Optimal design of an adaptive robust controller using a multi-objective artificial bee colony algorithm for an inverted pendulum system

In this study, a multi-objective artificial bee colony (MOABC) optimization algorithm was utilized to improve the performance of an adaptive robust control technique. This approach is implemented using an inverted pendulum system. More precisely, the proposed controller is a combination of a decoupled sliding-mode controller (DSMC) and adaptation laws based on the gradient descent approach. To achieve optimum control operation, the MOABC, as a novel meta-heuristic method simulated from the smart foraging activity of honeybee groups, was employed to optimize the coefficients of the suggested controller. In this regard, the objective functions are determined as the integral time of the absolute value of the pole angle and cart position errors. Finally, the time responses of the system states and control effort are presented to prove the effectiveness and feasibility of the proposed strategy compared with other contemporary studies referenced in this paper.

State-varying optimal decoupled sliding mode control for the Lorenz chaotic nonlinear problem based on HEPSO and MLS

ABSTRACT In order to gain the optimal performance of a controller, the proper selection of its parameters is of great importance. Moreover, any changes in the values of the parameters of the system cause that the respected controller works in a non-optimal status. Hence, to prevail over these obstacles, a state-varying optimal Decoupled Sliding Mode Control (DSMC) method is proposed in this research. First, the High Exploration Particle Swarm Optimization (HEPSO) approach is employed to find the optimal parameters of the DSMC. Then, the Moving Least Squares (MLS) approximation method is used to adjust the optimal gains of the controller according to the new parameters of the system. Lastly, the proposed state-varying optimal DSMC is utilized to address the Lorenz chaotic problem. The efficacy of the proposed controller is illustrated via comparing its performance with other notable studies.

Optimum fuzzy combination of robust decoupled sliding mode and adaptive feedback linearization controllers for uncertain under-actuated nonlinear systems

In this paper, an optimum fuzzy combination of decoupled sliding mode control (DSMC) and adaptive feedback linearization (FBL) is presented for under-actuated nonlinear systems with uncertainties. At first, DSMC and FBL are separately designed and the feedback linearization parameters are adapted by using the gradient descent approach; then, a fuzzy weighted summation of the two controllers is introduced. The multi-objective non-dominated sorting genetic algorithm II (NSGAII) is employed to properly choose the control gains. The objective functions for the optimization process are defined as the integrals of time multiplied by absolute errors, which have been minimized, simultaneously. In addition, the ball and beam system, as a well-known and popular benchmark, is investigated to test and challenge the proposed strategy. Simulation results illustrate that this approach would provide better performance in terms of settling time and control input compared with other methods reported in the literature.

Robust hierarchical sliding mode control with state-dependent switching gain for stabilization of rotary inverted pendulum

The rotary inverted pendulum (RIP) system is one of the fundamental, nonlinear, unstable and interesting benchmark systems in the field of control theory. In this paper, two nonlinear control strategies, namely hierarchical sliding mode control (HSMC) and decoupled sliding mode control (DSMC), are discussed to address the stabilization problem of the RIP system. We introduced HSMC with state-dependent switching gain for stabilization of the RIP system. Numerical simulations are performed to analyze the performance of the hierarchical sliding mode controllers with the decoupled sliding mode controller and the controller obtained from the pole placement technique. We proposed HSMC with state-dependent switching gain as it shows better performance as compared to HSMC with constant switching gain, DSMC, and the state feedback controller based on pole placement technique. The stability analysis of proposed HSMC is also discussed by using Lyapunov stability theory.

Optimal self-tuning decoupled sliding mode control for a class of nonlinear systems

A decoupled sliding mode controller (DSMC) is well-known as a simple way to achieve asymptotic stability of the nonlinear under-actuated systems. This method has many advanced features such as good performance and robustness against parameter variations. However, because of changing the system states, the controller with the constant parameters would not be optimum in any state of the system, and designing DSMC requires an adaptation for the controller parameters. Hence, in this paper, a robust self-tuning decoupled sliding mode controller (RSDSMC) is presented and optimised with five conflicting objective functions and twelve design variables using a multi-objective genetic algorithm. The proposed controller is applied to a highly nonlinear inverted pendulum and cart system via the computer simulation. The final results depict the appropriate performance of this new controller and demonstrate its superiority in comparison with those reported in literature.

Optimal self-tuning decoupled sliding mode control for a class of nonlinear systems

A decoupled sliding mode controller (DSMC) is well-known as a simple way to achieve asymptotic stability of the nonlinear under-actuated systems. This method has many advanced features such as good performance and robustness against parameter variations. However, because of changing the system states, the controller with the constant parameters would not be optimum in any state of the system, and designing DSMC requires an adaptation for the controller parameters. Hence, in this paper, a robust self-tuning decoupled sliding mode controller (RSDSMC) is presented and optimised with five conflicting objective functions and twelve design variables using a multi-objective genetic algorithm. The proposed controller is applied to a highly nonlinear inverted pendulum and cart system via the computer simulation. The final results depict the appropriate performance of this new controller and demonstrate its superiority in comparison with those reported in literature.

Decoupled Sliding Mode Control for a Novel 3-DOF Parallel Manipulator with Actuation Redundancy

This paper presents a decoupled nonsingular terminal sliding mode controller (DNTSMC) for a novel 3-DOF parallel manipulator with actuation redundancy. According to kinematic analysis, the inverse dynamic model for a novel 3-DOF redundantly actuated parallel manipulator is formulated in the task space using Lagrangian formalism and decoupled into three entirely independent subsystems under generalized coordinates to significantly reduce system complexity. Based on the dynamic model, a decoupled sliding mode control strategy is proposed for the parallel manipulator; the idea behind this strategy is to design a nonsingular terminal sliding mode controller for each subsystem, which can drive states of three subsystems to the original equilibrium points simultaneously by two intermediate variables. Additionally, a RBF neural network is used to compensate the cross-coupling force and gravity to enhance the control precision. Simulation and experimental results show that the proposed DNTSMC can achieve better control performances compared with the conventional sliding mode controller (SMC) and the DNTSMC without compensator.

Decoupled Sliding Mode Control for an Induction Motor

This paper represents a decoupled control strategy using sliding surface based on sliding mode controller for speed control of induction motor .The decoupled method provides a simple way to achieve asymptotic stability for induction motor .A strategy of sliding mode control is used, the decoupling method in this study uses two sliding mode controller for flux and speed . Then it compared by using PI controller which control flux and speed of the motor. Both controllers are simulated using SIMULINK .Simulation results are presented the effectiveness and good performance of the decoupling sliding mode control by considering the effects of the variations of the load torque. General Terms Robust control, induction motor

Online optimal decoupled sliding mode control based on moving least squares and particle swarm optimization

Regulation and tracking of system states to the desired points or trajectories are two common tasks in the field of control engineering. For optimum performance of a controller, the appropriate selection of its parameters is of utmost importance. Furthermore, when the initial conditions of the system change, the controller with the previous parameters would be not optimum in the new conditions. To overcome these obstacles, in this paper, an online optimal Decoupled Sliding Mode Control (DSMC) approach is introduced. Firstly, to determine the optimum parameters of DSMC, an improved Particle Swarm Optimization (PSO) algorithm is applied. Next, to adapt the optimal controller to any initial condition, the Moving Least Squares (MLS) approximation is utilized. Finally, the proposed online optimal DSMC is successfully applied to a ball and beam system. The comparative studies are provided to verify the effectiveness of the proposed control scheme.

Adaptive dynamic fuzzy neural network-based decoupled sliding-mode controller with hybrid sliding surfaces

The main motivation for this study is to remove the constraint of known non-linear dynamics in the control law, and eliminate the chattering in the switching. Thus, the dynamic fuzzy neural network (DFNN) is applied to better approximate the unknown non-linear dynamics in a decoupled sliding mode control (DSMC) problem for a class of fourth-order non-linear systems. To avoid the drawback of control chattering occurring in the sliding mode, a fractional order PI compensator is used to compensate for disturbance forces while suppressing chattering effect. Using this approach, the response of the system will converge faster than that of previous reports. Finally, simulations adopting this framework are presented for cart-pendulum system and TORA system. Simulation results show the effectiveness of the newly proposed adaptive DFNN-based decoupled sliding mode control method.

Decoupled Sliding Mode Control for a Multivariable Nonlinear System

This paper presents a decoupled control strategy using timevarying sliding surface-based Sliding Mode Controller (SMC) for a multivariable nonlinear system as an Ammonia Reactor system. The decoupled method provides a simple way to achieve asymptotic stability by dividing the system into three subsystems. Simulation results are presented for SMC comparing with a traditional PID controller. Then , the system is subjected to temperature disturbance to demonstrate the effectiveness and robustness of the controller. General Terms Decoupled Sliding Mode Control.

Pareto optimal design of the decoupled sliding mode controller for an inverted pendulum system and its stability simulation via Java programming

In this paper, firstly, a decoupled sliding mode controller (DSMC) is designed for stabilization of an inverted pendulum system. Secondly, a multi-objective particle swarm optimization (MOPSO) algorithm is implemented to optimize the DSMC parameters in order to decrease the normalized angle error of the pole and normalized distance error of the cart, simultaneously. The proposed Pareto front for the DSMC problem is validated through comparisons with existing state-of-the-art multi-objective algorithms. Then, Java programming with applets is presented in order to simulate the stability and educate the internet-based control.

Genetic algorithms optimisation of decoupled Sliding Mode controllers: simulated and real results

Two decoupled Sliding Mode control configurations have been designed for the navigation and propulsion systems of CyberShip II, a scale model of an oil platform supply ship. These control structures have parameters that need to be tuned to improve their performance. These parameters have been optimised using Genetic Algorithms. The performance of these controllers has been analysed through computer-generated simulations based on a non-linear hydrodynamic model of CyberShip II. The robustness has been evaluated through simulation in the presence of environmental disturbances. Subsequently, the optimised controllers have been tested in the real plant and the results are shown.