Sliding Mode Parameter Research Articles

Observer-based model following sliding mode tracking control of discrete-time linear networked systems with two-channel event-triggered schemes and quantizations

This paper addresses the problem of H∞ observer-based model following sliding mode tracking control for a class of linear discrete-time networked systems subject to event-triggered transmission schemes and quantizations occurring in both input and output channels. First, a dynamic event-triggered scheme and a static event-triggered scheme on sensor and controller sides are proposed, respectively, to reduce the number of unnecessary data transmission. Then, an observer is designed to estimate the system state. Considering the effects of quantization, networked conditions, external disturbance and event-triggered transmission schemes, the state error system and sliding mode dynamics are modeled as a new networked time-delay system. Based on this model and Lyapunov–Krasovskii functional method, sufficient conditions are derived to guarantee the resulting closed-loop system to be asymptotically stable with prescribed H∞ performance. And then, a co-design method is present to obtain the observer gain, triggering parameter and sliding mode parameter, simultaneously. Furthermore, a sliding mode controller for reaching motion is developed to ensure the reachability of the sliding surface. Finally, simulation examples are present to verify the effective of the proposed design method.

Piecewise Adaptive Sliding Mode Control for Aeroengine Networked Control Systems with Resource Constraints

Within the future application of wireless network for the aeroengine control problem, resource constraints (caused by the limitation of hardware) and network traffic restriction must be considered as one of the difficulties to be solved; thus, the network connection and transmission efficiency can be ensured. With focus on the problem of active packed dropout, a MEF‐TOD (Maximum Error First‐Try Once Discard) scheduling based network parameter and sliding mode joint design method has been proposed. First, a scheduling protocol strained control system and network parameter joint model have been established based on MEF‐TOD scheduling strategy, taking sampling period and data packet capacity as unknown network parameters. Subsequently, considering the influence of scheduling strategy, a sliding surface containing a compensation term has been designed, and then a sliding mode parameter and unknown network parameter heuristic joint design method has been developed. Finally, an attenuation factor based piecewise adaptive sliding mode strategy has been designed considering the influence of sampling period on system performance. Simulation results indicate that the joint design method can obtain the network parameter group which has the minimum performance function upper bound, thus achieving relatively high network utilization. The proposed piecewise adaptive sliding mode controller has good dynamic performance and is robust to the packet dropout problem caused by network scheduling and can effectively suppress chattering.

Fault-Tolerant Control of Time-Delay Markov Jump Systems With <inline-formula> <tex-math notation="LaTeX"> $It\hat{o}$</tex-math> </inline-formula> Stochastic Process and Output Disturbance Based on Sliding Mode Observer

This paper focuses on the fault-tolerant control problem of Markov jump systems (MJS) with $It\hat{o}$ stochastic process and output disturbances. Such a problem widely exists in practical systems such as mobile manipulator systems. Since MJS can suitably describe mobile manipulator systems, in this paper, a new approach based on the MJS model is proposed. First, a proportional-derivative sliding mode observer (SMO) and an observer-based controller are designed and synthesized. Two new theorems are derived to ensure the close-loop stochastic stability and the reachability of the sliding mode surface. Compared with the existing works, the system model is more general, which could describe a larger variety of plants or processes. The controller design procedure is simplified by solving the sliding mode parameters and the controller gain simultaneously with only one linear matrix inequality problem. In addition, the augmented fault vector can be reconstructed by employing a descriptor SMO. Simulations are provided to demonstrate the validity of the derived theorems and the effectiveness of the proposed algorithm.

H∞ observer-based event-triggered sliding mode control for a class of discrete-time nonlinear networked systems with quantizations

This paper investigates the problem of H∞ observer-based event-triggered sliding mode control (SMC) for a class of uncertain discrete-time Lipschitz nonlinear networked systems with quantizations occurring in both input and output channels. The event-triggered strategy is used to save the limited network bandwidth. Then, based on the zero-order-hold (ZOH) measurement, a state observer is designed to reconstruct the system state, which facilitates the design of the discrete-time sliding surface. Considering the effects of quantizations, networked-induced constraints and event-triggered scheme, the nonlinear state error dynamics and sliding mode dynamics are converted into a unified linear parameter varying (LPV) time-delay system with the aid of a reformulated Lipschitz property. By using the Lyapunov-Krasovskii functional and free weighting matrix, a new sufficient condition is derived to guarantee the robust asymptotic stability of the resulting closed-loop system with prescribed H∞ performance. And then the observer gain, event-triggering parameter and sliding mode parameter are co-designed. Furthermore, a novel SMC law is synthesized to force the trajectories of the observer system onto a pre-specified sliding mode region in a finite time. Finally, a single-link flexible joint robot example is utilized to demonstrate the effectiveness of the proposed method.

Time efficient sliding mode controller based on Bang–Bang logic for satellite attitude control

In order to improve the convergence rate of standard sliding mode controller, time efficient controllers based on Bang–Bang logic for satellite attitude stabilization and tracking control are developed in this paper. The time efficient open-loop control algorithm Bang–Bang control is combined with closed-loop sliding mode control to improve system robustness. A two-stage structure sliding mode with a fixed angular velocity stage and a fixed deceleration stage is proposed in this paper. The sliding mode parameter is real-time updating hence the modified sliding mode could have Bang–Bang character. The system inertia matrix uncertainty and disturbance torque is discussed and the controller proposed in this paper is robust to the perturbation. The control torque constraint is also discussed and the constraint on control parameters is given. The performance of the controller is demonstrated by numerical simulation.

A Variable Structure System Control and its Application in Underwater Vehicles

The paper proposes a new Variable Structure System (VSS) control algorithm and its application in underwater robotics. The main features of the proposed approach consist on the usage of coupled switching surfaces, and on the usage of an adaptive adjustment method for their parameters in order to accelerate the transient processes. The adaptive algorithm of linear and nonlinear switching surfaces coefficients, is based on the stabilization of the sliding mode parameter close to the reference value. In this paper, it is shown how the proposed approach improves the system transient processes and the energy efficiency in comparison with conventional VSS, neutralizing also some drawbacks. The proposed adaptive VSS algorithm is applied to control a Remotely Operated Vehicle (ROV), and simulation results confirm the advantages to apply it.

Robust Tracking Control of Networked Control Systems With Communication Constraints and External Disturbance

This paper addresses the problem of robust tracking control of networked control systems with communication constraints (network-induced delay, packet dropouts, and packet disorder) and external disturbance. A novel networked predictive control algorithm based on k -order adaptive discrete-time sliding-mode control ( k -ADSMC) is proposed. The ADSMC, which can self-adapting adjust sliding-mode parameters and ensure faster convergence, is designed based on the error and error difference of tracking output. Furthermore, k -ADSMC is designed, which uses the estimated disturbance as weight factors and synthesizes the sliding- mode values of all k times, in order to improve the robust of tracking control. Finally, the stability of the system is proved, and a dc motor servo system is utilized to verify the effectiveness of the proposed method.

A Fixed-Frequency Sliding Mode Controller for a Boost-Inverter-Based Battery-Supercapacitor Hybrid Energy Storage System

The boost-inverter-based battery-supercapacitor hybrid energy storage systems (HESSs) are a popular choice for the battery lifetime extension and system power enhancement. Various sliding mode (SM) controllers have been used to control the boost inverter topology in the literature. However, the traditional SM controllers for the boost inverter topology operate with a high and variable switching frequency which increases the power losses and system components design complexity. This can be alleviated by a pulse width modulation (PWM)-based fixed-frequency SM controller proposed in this paper. The SM controller is implemented using variable amplitude PWM carrier signals generated using the output capacitor voltage and inductor current measurements, thus eliminating the requirement of the output capacitor currents measurement. The battery-connected inductor reference currents for the SM controller are generated by a supercapacitor energy controller which is responsible for the HESS power allocation. First, the theoretical aspects of the SM controller, the operation and parameter selection of the supercapacitor energy controller, and the supercapacitor sizing for the HESS are discussed in the paper. Then, the proposed control system is experimentally verified, and it is shown that the HESS is able to satisfy the HESS output power requirements, while allocating the ripple current and the fast power fluctuations to the supercapacitor while maintaining operation of the supercapacitor within predefined voltage limits. The main advantage of the proposed SM controller, as compared with the traditional double-loop control method, is in eliminating possible DC current injection into the grid when the equivalent series resistance values of the boost inductors become unequal due to the tolerances and temperature variations.

Sliding Mode Control of Cable‐Driven Redundancy Parallel Robot with 6 DOF Based on Cable‐Length Sensor Feedback

The sliding mode control of the cable‐driven redundancy parallel robot with six degrees of freedom is studied based on the cable‐length sensor feedback. Under the control scheme of task space coordinates, the cable length obtained by the cable‐length sensor is used to solve the forward kinematics of the cable‐driven redundancy parallel robot in real‐time, which is treated as the feedback for the control system. First, the method of forward kinematics of the cable‐driven redundancy parallel robot is proposed based on the tetrahedron method and Levenberg‐Marquardt method. Then, an iterative initial value estimation method for the Levenberg‐Marquardt method is proposed. Second, the sliding mode control method based on the exponential approach law is used to control the effector of the robot, and the influence of the sliding mode parameters on control performance is simulated. Finally, a six‐degree‐of‐freedom position tracking experiment is carried out on the principle prototype of the cable‐driven redundancy parallel robot. The experimental results show that the robot can accurately track the desired position in six directions, which indicates that the control method based on the cable‐length sensor feedback for the cable‐driven redundancy parallel robot is effective and feasible.

Decentralized and Parallel Constructionsfor Optimally Rigid Graphs in

In this paper, we address the decentralized and parallel construction of rigid graphs in the plane that optimize an edge-weighted objective function under cardinality constraints. Two auction-based algorithms to solve this problem in a decentralized fashion are first proposed. Centered around the notion of leader election, the first approach finds an optimal solution through a greedy bidding, while the second approach provides a sub-optimal solution which reduces complexity according to a sliding mode parameter. Then, by exploiting certain local structural properties of graph rigidity, a parallelization to build a portion of the optimal solution in constant time is derived. A theoretical characterization of algorithm performance is provided together with complexity analysis. Finally, simulation results are presented to corroborate the theoretical findings.

An adaptive VSS control for remotely operated vehicles

SummaryThe paper is devoted to a new adaptive variable‐structure system (VSS) control algorithm and its applications in underwater robotics. The proposed approach is based on the usage of sliding mode parameter (SMP) in order to have adaptation in VSS. It is demonstrated that the extreme values of SMPs are directly associated with high efficiency of transient processes in VSS. The essence of the presented adaptation algorithm consists on the adjustment of switching surface parameters such that the SMPs move from the assigned desirable value to the extreme values, with the overall effect to accelerate transients. The effectiveness of the derived approach is proven by applying it for controlling a real remotely operated vehicle. Copyright © 2015 John Wiley & Sons, Ltd.

Identification of Nonlinear Dynamic Systems Using Type-2 Fuzzy Neural Networks—A Novel Learning Algorithm and a Comparative Study

In order to achieve faster and more robust convergence (especially under noisy working environments), a sliding mode theory-based learning algorithm has been proposed to tune both the premise and consequent parts of type-2 fuzzy neural networks in this paper. Differently from recent studies, where sliding mode control theory-based rules are proposed for only the consequent part of the network, the developed algorithm applies fully sliding mode parameter update rules for both the premise and consequent parts of the type-2 fuzzy neural networks. In addition, the responsible parameter for sharing the contributions of the lower and upper parts of the type-2 fuzzy membership functions is also tuned. Moreover, the learning rate of the network is updated during the online training. The stability of the proposed learning algorithm has been proved by using an appropriate Lyapunov function. Several comparisons have been realized and shown that the proposed algorithm has faster convergence speed than the existing methods such as gradient-based and swarm intelligence-based methods. Moreover, the proposed learning algorithm has a closed form, and it is easier to implement than the other existing methods.

Second-order terminal sliding mode control for networks synchronization

This paper proposes a second-order terminal sliding mode controller for outer synchronization of a class of complex networks with disturbances. This control scheme adopts a hierarchical control structure to reduce the numbers of controllers. The multivariable error systems were decomposed into two subsystems, a controllable nonlinear subsystem and a linear subsystem. The proposed terminal sliding mode controller was only designed for the nonlinear subsystem. The linear subsystem is set to appropriate sliding mode parameters to implement synchronization. This approach possesses the features of less controllers, faster convergence and higher tracking precision. The performance of the control strategy is evaluated through the control of the complex networks consisting of \(N\) identical Rossler systems. Simulation results demonstrate the effectiveness of the proposed control method.

Sliding Mode Control Based on Genetic Algorithm for WSCC Systems Include of SVC

In this study, in order to control the voltage of theWestern System Coordinating Council (WSCC) system, asliding mode control has been used. First, the active andreactive power values, voltage and angle values of the loadbuseshave been calculated. The load-buses which their voltagelevels are lower than 1 pu has been identified. After that, byconsidering one of these load-buses, the system is transformedto the system with two load-buses and the sliding mode controlmodel has been obtained. The sliding mode parameters havebeen obtained by using genetic algorithm (GA) optimizationtechnique. From the results of simulations of this model, it isshown that the voltage of the load-buses reaches at 1 pu with avery low error.DOI: http://dx.doi.org/10.5755/j01.eee.19.4.1580

Design of a stable sliding-mode controller for a class of second-order underactuated systems

In the above paper [1], additional conditions are required for the sliding-mode parameters to avoid the singularity, and some of simulation results do not match up to the theoretical one. In the following remark, the conditions for the controller in [1] to avoid singularity are given.

Global Fast Terminal Sliding Mode Control for Wind Energy Conversion System

As for traditional sliding mode control (SMC) with linear sliding surface and the tracking error can’t convergent to zero in finite time, fast terminal sliding mode control (FTSMC) designed with introduction nonlinear function into sliding hyper-plane, which makes tracking error converge to zero in finite time. A global fast terminal sliding mode control (GFTSMC) was designed with SMC and FTSMC, the sliding surface of GFTSMC was designed and the control law was deduced, also the convergence time was computed and stability proved by Lyapunov theory. With simulation, the optimal sliding mode parameters was selected and applied this control strategy for wind energy conversion system (WECS), the simulation result shows this control system can realize optimal power tracking control for wind energy conversion system.

Sliding mode parameter identification of systems with measurement noise

Identification problem in a nonlinear system with constant coefficients is addressed via traditional and high-order sliding mode parameter observer based on the least-squares continuous-time technique. Measurement noise effects on the parameter estimation algorithm are analyzed. The effectiveness of the proposed method is verified via the parameter estimation in a second-order system with noisy measurement.

Sliding modes time varying matrix identification for stochastic system

Time varying parameters identification of stochastic systems is addressed via sliding mode parameter observers. Sliding mode observer is governed by control that compensates a so-called Ito's term, which reflects a stochastic nature of a system. The matrix estimation algorithm based on equivalent control is proposed. A numerical example illustrates the effectiveness of the proposed approach.

Visual Servoing-Based Autonomous 2-D Manipulation of Microparticles Using a Nanoprobe

In this paper, autonomous 2-D manipulation and pattern formation of microparticles under an optical microscope by pushing and pulling them with a sharp nanoprobe is presented. For calibration of the camera and to achieve a larger bandwidth on position control, an iterative sliding mode parameter observer is designed that satisfies the Lyapunov stability criterion. A procedure that allows particles to stick near the tip of the nanoprobe while pushing/pulling and to release them when placed to the target position is used for manipulation. For pattern formation, a trajectory planning algorithm based on a metric that defines the blockage of trajectories by particles and target positions is used to order manipulation of particles such that the particle that blocks the most number of trajectories is pulled/pushed to the target position that blocks the least number of trajectories. This ordering of manipulation performs better than the conventional distance-based approaches due to the fact that it minimizes the number of blockages to the linear trajectories. Efficiency of the approach is demonstrated on simulation and experimental results by positioning 4.5-mum diameter polystyrene particles on a flat glass substrate autonomously. The average accuracy of the pushing/pulling operations is less than 0.64 mum.

Modeling and controlling of parallel manipulator joint driven by pneumatic muscles

A parallel manipulator joint driven by three pneumatic muscles and its posture control strategy are presented. Based on geometric constraints and dynamics, a system model is developed through which some influences on dynamic response and open-loop gain are analyzed including the supply pressure, the initial pressure and the volume of pneumatic muscle. A sliding-mode controller with a nonlinear switching function is applied to control posture, which adopts the combination of a main method that separates control of each muscle and an auxiliary method that postures error evaluation of multiple muscles, especially adopting the segmented and intelligent adjustments of sliding-mode parameters to fit different expected postures and initial states. Experimental results show that this control strategy not only amounts to the steady-state error of O.1° without overshoot, but also achieves good trajectory tracking.