Optimal Sliding Mode Control Research Articles

Design of Optimal Sliding Mode Control of Elbow Wearable Exoskeleton System Based on Whale Optimization Algorithm

The high nonlinearity and time-varying coefficients characterize the elbow exoskeleton system for rehabilitation. To deal with these difficult control challenges, nonlinear and reliable controllers are needed. This paper shows the use of Sliding Mode Control (SMC) to track the trajectory of an Elbow Exoskeleton System (EES) with presence of parameter uncertainty. The Whale Optimization Algorithm (WOA) algorithm is used to tuning the design parameters of suggested controllers for performance improvement. Computer simulation based on MATLAB software has been implemented to conduct a comparison study between optimal and non-optimal SMC. The simulation findings shows that the optimal SMC outperforms the non-optimal version of controller in terms of performance.

Optimal sliding mode control of electromagnetic worm-like locomotion systems for in-pipe robots

Optimal sliding mode control of electromagnetic worm-like locomotion systems for in-pipe robots

Genetic algorithm optimized robust nonlinear observer for a wind turbine system based on permanent magnet synchronous generator

This paper presents an optimal control scheme for a Permanent Magnet Synchronous Generator (PMSG) coupled to a wind turbine operating without a position sensor. This sensorless scheme includes two observers: The first observer uses the flux to estimate the speed. However, an increase in the temperature or a degradation of the permanent magnet characteristics will result in a demagnetization of the machine causing a drop in the flux. The second observer is therefore used to estimate these changes in the flux from the speed and guaranties the stability of the system. This structure leads to a better exchange of information between the two observers, eliminates the problem of encoder and compensates for the demagnetization problem. To improve the precision of the speed estimator, the gain of the non-linear observer is optimized using Genetic Algorithm (GA) and the speed is obtained from a modified Phase Locked Loop (PLL) method using an optimized Sliding Mode Controller (SMC). Furthermore, to enhance the convergence speed of this observer scheme and improve the performance of the system a Fast Super Twisting Sliding Mode Control (FSTSMC) is introduced to reinforce the SMC strategy. A series of simulations are presented to show the effectiveness and robustness of proposed observer scheme.

A Novel Fast Optimized Sliding Mode Controller for Automatic Voltage Regulator System

A Novel Fast Optimized Sliding Mode Controller for Automatic Voltage Regulator System

IAE Minimization in Sliding Mode Control With Input and Velocity Constraints

In this work an optimal sliding mode controller for second order, nonlinear systems is proposed. First, the sliding surface is selected to obtain finite time convergence to the desired state. Moreover, to ensure robustness with respect to unknown external disturbances and model uncertainties, the surface is time-varying and at the start of the control process it intersects the point, whose coordinates are defined by the initial state. Thus, the existence of the sliding mode is ensured for the whole control process. Next, admissible values of the hyperplane parameters, that ensure satisfaction of velocity and/or control signal constraints are determined. Lastly, optimal values of these parameters, in terms of integral absolute error (IAE) are calculated. The main motivation of this paper was to obtain the good dynamical performance of the system and robustness by eliminating the reaching phase, overcoming the external, unknown disturbances and obtaining a finite-time convergence of the representative point to the desired state. The other main issue was to include some key limitations such as control signal and velocity constraints in order to facilitate the practical application of this strategy.

Consensus of Discrete-Time Nonlinear Multiagent Systems Using Sliding Mode Control Based on Optimal Control

This article investigates the optimal sliding mode control approach for consensus of nonlinear discrete-time high-order multi-agent systems (MASs). First, the nonlinearity and communication delay in the MAS is solved by designing a distributed discrete-time integral sliding mode control law, together with a proof of reachability of the sliding mode surface, as well as a proof that the chattering of the system is attenuated. In addition, the optimal controller is designed based on the model obtained after the distributed sliding mode control law is applied to the system. The merits of the proposed distributed sliding mode controller with the fusion of optimal control are that it can reduce the chattering of the MASs and their existence of quasi-sliding modes, as well as tolerate the negative impact caused by communication delay among agents. The MASs can achieve consensus quickly with the combined action of the sliding mode controller and the optimal controller. Finally, two examples are given to verify the effectiveness of the control method proposed in this paper.

Fuzzy adaptive selfish herd optimization based optimal sliding mode controller for frequency stability enhancement of a microgrid

In recent power system, the quality of power is highly influenced by the imbalance between generation and load demand. Automatic Generation Control (AGC) is an imperative control strategy to minimize the frequency or power deviation by regulating the generation. In this work, a centralized Sliding Mode Control (SMC) is employed as AGC to achieve reliable performance of a Microgrid (MG). Due to existence of some poor inertia sources in MG, a knowledgeable and reliable controller is very indispensable. Wind turbine, photovoltaic unit, fuel cell, aqua-electrolyser, fly-wheel, ultra capacitor, battery energy storage units reside in MG with nonlinearities such as Generation Rate Constraint (GRC), communication delay and anomalous load. Further, a Small Hydro Power Plant (SHPP) is integrated with MG to enhance the performance response. The performance of the controller is enhanced by Selfish Herd Optimization (SHO) and a novel fuzzy adaptive SHO (FASHO). The decisive parameters of SHO are decided by fuzzy logic control by which the efficacy of algorithm is improved. The proposed FASHO based SMC controller is substantiated over SHO/FASHO based PID, FOPID and FOPID-(1 + PI) controllers. The proposed FASHO-SMC controller and integration of SHPP are wrapped up as superior approaches to enhance the performance of MG.

Learning-based online optimal sliding-mode control for space circumnavigation missions with input constraints and mismatched uncertainties

A learning-based online optimal sliding-mode control strategy is developed for space circumnavigation missions subject to input constraints, and the mismatched uncertainties caused by measurement uncertainties are also considered in this infinite-horizon optimal control problem. The logarithmic hyperbolic cosine function is used to design the optimal value function to overcome the weakness that the derivative of the adaptive weight of neural network (NN) changes too fast when the value of the sliding-mode function is too large, and another suitable nonquadratic function is used to incorporate input constraints into the optimal control framework. To approximate the Hamiton-Jacobi-Bellman equation corresponding to the novel optimal value function, an actor-critic (AC) architecture is introduced with NNs, and a finite-time disturbance observer (FTDO) is employed to estimate the mismatched uncertainties in the plant. The simulation results verify the effectiveness of the proposed approach.

OPTIMAL SLIDING MODE CONTROLLER DESIGN BASED ON WHALE OPTIMIZATION ALGORITHM FOR LOWER LIMB REHABILITATION ROBOT

The Sliding Mode Controllers (SMCs) are considered among the most common stabilizer and controllers used with robotic systems due to their robust nonlinear scheme designed to control nonlinear systems. SMCs are insensitive to external disturbance and system parameters variations. Although the SMC is an adaptive and model-based controller, some of its values need to be determined precisely. In this paper, an Optimal Sliding Mode Controller (OSMC) is suggested based on Whale Optimization Algorithm (WOA) to control a two-link lower limb rehabilitation robot. This controller has two parts, the equivalent part, and the supervisory controller part. The stability assurance of the controlled rehabilitation robot is analyzed based on Lyapunov stability. The WO algorithm is used to determine optimal parameters for the suggested SMC. Simulation results of two tested trajectories (linear step signal and nonlinear sine signal) demonstrate the effectiveness of the suggested OSMC with fast response, very small overshoot, and minimum steady-state error.

Composite Control of a Hovering Helicopter Based on Optimized Sliding Mode Control

Composite Control of a Hovering Helicopter Based on Optimized Sliding Mode Control

Frequency stability analysis with fuzzy adaptive selfish herd optimization based optimal sliding mode controller for microgrids

Abstract This article articulates the frequency control in an isolated microgrid (MG) under a centralized secondary controller. The penetration of distributed generators (DGs) which are weather dependant, and some of them are inertia less cause the instability in the MG. Besides this, unusual/abrupt load change, communication delay, and parameter change uncertainties make the MG more unstable. So, to restore the stability of the MG a sliding mode controller (SMC) is employed. The design of the SMC is carried by selfish herd optimization (SHO) algorithm. To validate the performance of SHO-SMC controller, it is compared with the results obtained by GOA-FOPID-(1+PI), SHO-PID, SHO- FOPID, and SHO-FOPID-(1+PI) controllers. Further, to establish an ameliorated dynamic response of the MG, SHO is modified by applying fuzzy logic named as fuzzy adaptive SHO (FA-SHO). In addition to this, in a two area MG, the potential of SHO/FA-SHO SMC controllers over SHO-SMC, and SHO/FA-SHO FOPID-(1+PI) controllers has been examined. Finally, with some crucial intermittent uncertainties like abrupt load change, time delay, and parameter variation, the robustness of the proposed controller is established.

Trajectory tracking of under-actuated ships based on optimal sliding mode control with state observer

An optimal sliding mode control (SMC) with state observer is presented for trajectory tracking of under-actuated ships with the model uncertainties, environmental disturbances, input constraints and optimization. Firstly two backstepping virtual control laws are designed by the kinematic model to convert trajectory tracking into heading control and surge velocity control. Then, according to the Norrbin model and the correlation coefficient between surge velocity and propeller revolution, a heading model and a surge velocity model are established respectively. Meanwhile, two extended state observers are built based on the hyperbolic tangent function with clear bounded meaning, which estimate model uncertainties and disturbances. The nonlinear SMC is used to control heading and surge velocity, which embeds the control laws, namely rudder angle and propeller revolution, in a cost function. This cost function is solved with input limits to address the input optimization, amplitude and increment constraints. Finally, the stability analysis is provided, and the simulations show that the ship can track trajectory successfully in case of the disturbances and constraints. These results demonstrate the feasibility and effectiveness of this method.

Designing an optimal control strategy for a mobile manipulator and its application by considering the effect of uncertainties and wheel slipping

AbstractThis article seeks to develop the dynamic model of a mobile robot for controlling purposes while the effects of uncertainties and longitudinal and lateral slip are assumed. The rise in the number of state variables and considering the effects of nonlinear parameters due to slip modeling can complicate the control procedure of wheeled mobile manipulators. In addition, the existence of uncertainties as well as holonomic and nonholonomic constraints would increase this complexity even more. On the one side, as wheels are considered to slip, unwanted movements due to slippage affect the movement of the manipulator and the manipulator may not be able to track the desired path. On the other side, the movement of weighted links of the manipulator constantly changes the normal forces of the wheels. As traction forces are dependent on these normal forces, the path tracked by the platform would be affected. Given these conditions, employing a robust control methodology and developing an optimal algorithm to reduce the effects of uncertainties and wheels slip seems mandatory. To this aim, a sliding mode control (SMC) strategy is formulated in this study. Furthermore, the suggested algorithm is optimized using a state‐dependent Riccati equation to reduce the consumed torque and increase the accuracy of the system. Simulations are conducted, and the presented algorithm is also checked with the experimental setup of a Scout robot. Simulation results show that the optimal sliding mode control (OSMC) successfully decreases sudden jumps due to slippage in the system. In addition, the consumed power of wheels and arm for SMC decreases from 9.15 and 1.02 N·m to, respectively, 1.46 and 0.54 N·m for OSMC.

Optimal sliding mode control for cutting tasks of quick-return mechanisms

A solution of the constant cutting velocity problem of quick-return mechanisms is the main concern of this paper. An optimal sliding mode control in the task space is used to achieve uniform and accurate cuts throughout the workpiece. The switching hyperplane is designed to minimize the position error of the slider-dynamics in an infinite horizon.A Jacobian compensator is used to exploit the mechanical advantage and ensure controllability. The velocity profile is constructed in terms of the mechanism and workpiece geometric properties. Stability of the closed-loop dynamics is verified with the Lyapunov stability theory. Experiments are carried out in a quick-return mechanism prototype to validate the proposal.

Differential Evolutionary Optimized Sliding Mode Control for PMSM Drives

Increasing environmental concerns and fluctuating oil prices have paved way to adopt an alternative to combustion engines. At this instance, electric vehicles could be the most viable solution. Permanent magnet synchronous motors (PMSMs) have high power density, relatively smaller size and high torque-inertia ratio. However, it has series of challenging problems due to model mismatch, load disturbance, and nonlinear in nature. These challenges demand a robust controller. Sliding Mode Controller (SMC) is one such controller that eliminates internal parameter variations and external disturbances. This motivates the design of SMC for speed control of PMSM. The parameters of the SMC are optimized using Differential Evolutionary algorithm and performance of PMSM servo system is validated. © 2001 Elsevier Science. All rights reserved

Performance analysis of MR damper based semi-active suspension system using optimally tuned controllers

This study assesses the dynamic performance of the semi-active quarter car vehicle under random road conditions through a new approach. The monotube MR damper is modelled using non-parametric method based on the dynamic characteristics obtained from the experiments. This model is used as the variable damper in a semi-active suspension. In order to control the vibration caused under random road excitation, an optimal sliding mode controller (SMC) is utilised. Particle swarm optimisation (PSO) is coupled to identify the parameters of the SMC. Three optimal criteria are used for determining the best sliding mode controller parameters which are later used in estimating the ride comfort and road handling of a semi-active suspension system. A comparison between the SMC, Skyhook, Ground hook and PID controller suggests that the optimal parameters with SMC have better controllability than the PID controller. SMC has also provided better controllability than the PID controller at higher road roughness.

Optimal Sliding Mode Control of Permanent Magnet Direct Drive Linear Generator for Grid-Connected Wave Energy Conversion

the key goal of this article is on the design and optimum sliding mode control for Grid-Connected direct drive extraction method of ocean wave energy by Multi-Objective Particle Swarm Optimization (MOPSO). A Linear Permanent Magnet Generator simulates the ocean wave energy extraction system, driven by an Archimedes Wave Swing. Uncontrolled three-phase rectifiers, a three-level buck-boost converter and 3 level neutral point clamped inverter are planned grid integration of Wave Energy Conversion device. The technique monitors the three-level buck-boost converter service cycle linked to the PMLG output terminals and decides the optimum switching sequence of 3 level neutral point clamped inverter to enable the grid relation. Simulations using Matlab/Simulink were carried out to test working of the wave energy converter after the suggested optimal control method was applied under various operating settings. Various simulation test results indicate that the proposed optimum control system is tested in both normal and irregular ocean waves. And it has been shown that the control method of the MOPSO sliding mode is ideal for maximizing energy transfer efficiency. Better voltage management at the DC-link and for achieving greater controllability spectrum was accomplished by the proposed Duty-ratio optimal control system.

Optimal Sliding Mode Control of Permanent Magnet Direct Drive Linear Generator for Grid-Connected Wave Energy Conversion

the key goal of this article is on the design and optimum sliding mode control for Grid-Connected direct drive extraction method of ocean wave energy by Multi-Objective Particle Swarm Optimization (MOPSO). A Linear Permanent Magnet Generator simulates the ocean wave energy extraction system, driven by an Archimedes Wave Swing. Uncontrolled three-phase rectifiers, a three-level buck-boost converter and 3 level neutral point clamped inverter are planned grid integration of Wave Energy Conversion device. The technique monitors the three-level buck-boost converter service cycle linked to the PMLG output terminals and decides the optimum switching sequence of 3 level neutral point clamped inverter to enable the grid relation. Simulations using Matlab/Simulink were carried out to test working of the wave energy converter after the suggested optimal control method was applied under various operating settings. Various simulation test results indicate that the proposed optimum control system is tested in both normal and irregular ocean waves. And it has been shown that the control method of the MOPSO sliding mode is ideal for maximizing energy transfer efficiency. Better voltage management at the DC-link and for achieving greater controllability spectrum was accomplished by the proposed Duty-ratio optimal control system.

Impedance control based on optimal adaptive high order super twisting sliding mode for a 7-DOF lower limb exoskeleton

In this paper, a novel hybrid optimal Adaptive High-Order Super Twisting Sliding Mode (AHOSTWSM) impedance control is proposed for a lower limb exoskeleton robot with 7 active joints, which takes the interaction forces between the robot and the user into account. First, the dynamic model of the robot is extracted using Lagrange approach. Then, an adaptive super twisting sliding mode controller is designed based on Lyapanov theory. Moreover, the interaction forces are obtained in every time-step and applied to the robot as a compensating torque to guard against disturbances. The desired trajectory of the upper limb joint has been extracted so that the stability of the robot is achieved based on Zero Moment Point (ZMP) criterion at any moment. Moreover, to achieve optimal performance (maximum stability, minimum tracking error, reduced interacting forces, and optimal energy consumption), parameters of the proposed controller, the upper limb desired trajectory, and the impedance system are optimized using Harmony Search Algorithm (HSA). Finally, in order to demonstrate the effectiveness of the proposed controller, optimal sliding mode controller (SMC) is designed and performance of the AHOSTWSM is compared with SMC. The simulation results reveal the superiority of the controller in comparison with SMC.

Application of Optimized Sliding Mode Control Strategy in Ship Electric Energy Conversion Process

Application of Optimized Sliding Mode Control Strategy in Ship Electric Energy Conversion Process