A New Neural Network Based Sliding Mode Adaptive Controller for Tracking Control of Robot Manipulator

In this paper a New RBF Neural Network based Sliding Mode Adaptive Controller (NNNSMAC) for Robot Manipulator trajectory tracking in the presence of uncertainties and disturbances is introduced. The research offers a learning with minimal parameter (LMP) technique for robotic manipulator trajectory tracking. The technique decreases the online adaptive parameters number in the RBF Neural Network to only one, lowering computational costs and boosting real-time performance. The RBFNN analyses the system's hidden non-linearities, and its weight value parameters are updated online using adaptive laws to control the nonlinear system's output to track a specific trajectory. The RBF model is used to create a Lyapunov function-based adaptive control law. The effectiveness of the designed NNNSMAC is demonstrated by simulation results of trajectory tracking control of a 2 dof Robotic Manipulator. The chattering effect has been significantly reduced.

Forced Sliding Mode Control for Chaotic Systems Synchronization

Synchronization of chaotic systems is considered to be a common engineering problem. However, the proposed laws of synchronization control do not always provide robustness towards the parametric perturbations. The purpose of this article is to show the use of synergy-cybernetic approach for the construction of robust law for Arneodo chaotic systems synchronization. As the main method of design of robust control, the method of design of control with forced sliding mode of the synergetic control theory is considered. To illustrate the effectiveness of the proposed law it's compared in this article with the classical sliding mode control. The distinctive features of suggested robust control law are the more good compensation of parametric perturbations (better performance indexes --- the root-mean-square error, average absolute value of error) without designing perturbation observers, the ability to exclude the chattering effect, less energy-consuming and a simpler analysis of the stability of a closed-loop system. Offered approach will allow a new consideration for the design of robust control laws for chaotic systems, taking into account the ideas of directed self-organization and robust control. It can be used for synchronization other chaotic systems.Mathematics Subject Classification (2020) 93B35 · 93B52 · 93C30 · 93D21 · 34H10

Prescribed performance-based adaptive sliding mode control for the autopilot design of missile with lateral jets

A novel prescribed performance-based adaptive sliding mode control is investigated for the autopilot design of missile with lateral reaction jets. An integral sliding mode surface is designed for a class of nonlinear systems such that the prescribed output-tracking behavior is incorporated into the sliding mode dynamics. An adaptive algorithm is developed using the concept of equivalent control to attenuate the chattering effect. Then, the method is applied to the autopilot design where the sliding mode control law is allocated to two sets of actuators according to their respective characteristics. The proposed integral sliding surface guarantees that the missile output can track the given reference command with the prescribed performance indices from the very beginning of the time. Moreover, the adaptation laws allow the reduction of the jets consumption. Several simulations conducted at different set-points show the efficacy of the proposed methods.

Improved Pole-placement Control with Feed-forward Dead Zone Compensation for Position Tracking of Electro-Pneumatic Actuator System Improved Pole-placement Control with Feed-forward Dead Zone Compensation for Position Tracking of Electro-Pneumatic Actuato

Dead-zone in the valve degraded the performances of the Electro-Pneumatic Actuator (EPA) system. It makes the system difficult to control, become unstable and leads to chattering effect nearest desired position. In order to cater this issue, the EPA system transfer function and the dead-zone model is identified by MATLAB SI toolbox and the Particle Swarm Optimization (PSO) algorithm respectively. Then a parametric control is designed based on pole-placement approach and combine with feed-forward inverse dead-zone compensation. To reduce chattering effect, a smooth parameter is added to the controller output. The advantages of using these techniques are the chattering effect and the dead-zone of the EPA system is reduced. Moreover, the feed-forward system improves the transient performance. The results are compared with the pole-placement control (1) without compensator and (2) with conventional dead-zone compensator. Based on the experimental results, the proposed controller reduced the chattering effect due to the controller output of conventional dead-zone compensation, 90% of the pole-placement controller steady-state error and 30% and 40% of the pole-placement controller with conventional dead-zone compensation settling time and rise time.

A discrete-time terminal sliding mode controller design for an autonomous underwater vehicle

Autonomous underwater vehicle (AUV) are underwater robotic devices intended to explore hostiles territories in underwater domain. AUVs research gaining popularity among underwater research community because of its extensive applications and challenges to overcome unpredictable ocean behavior. The aim of this paper is to design discrete time terminal sliding mode control (DTSMC) reaching law-based employed to NPS AUV II purposely to improve the dynamic response of the closed loop system. This is accomplished by introducing a nonlinear component to sliding surface design in which the system state accelerated, and chattering effect is suppressed. The nonlinear component consist of fractional power is to ensure steeper slope of the sliding surface in the vicinity of the equilibrium point which lead to quicker convergence speed. Thus, the chattering effect in the control action suppressed as the convergence of the system state accelerated. The stability of the control system is proven by using Sarpturk analysis and the performance of the DTSMC is demonstrated through simulation study. The performance of DTSMC is benchmarked with DSMC and PID controller

A cascaded scheme for high-performance estimation of vehicle states

Vehicle active safety control is bonded tightly with the accurate acquirement of vehicle states. This paper presents a cascaded scheme to realize high-performance estimation of vehicle states. To achieve the estimation with good performance, an adaptive sliding mode observer is designed for determining four longitudinal tire forces independently, and the Kalman filter is used for alleviating the inherent chattering effect. On this basis, lateral tire forces are calculated via a simplified formula based on the Dugoff tire model. Lastly, utilizing the obtained tire force information, the key states of vehicle motion are estimated through the smooth variable structure filter. Numerical experiments are conducted to testify the effectiveness of the presented estimation scheme. The results of performance comparison in different case studies show that the chattering effect can be suppressed to a great extent, and the accuracy, robustness and real-time performance to modeling uncertainty and unexpected measurements can be effectively guaranteed for vehicle state estimation by means of the proposed scheme.

Attitude trajectory tracking of quadrotor UAV using super-twisting observer-based adaptive controller

The successful implementation of high-level decision algorithm on quadrotor depends on the accurate trajectory tracking performance. In this paper attitude estimation and trajectory tracking control problem of quadrotor unmanned aerial vehicle (UAV) with endogenous and exogenous disturbance are considered, where the lumped disturbance characteristic does not have a probabilistic illustration but instead the dynamics are known to have a bound. The problem is handled by developing disturbance estimator and control strategy. In order to estimate lumped disturbance precisely, a globally finite time stable extended state observer is proposed based on super-twisting algorithm. Stability analysis and observer’s parameters selection rule are discussed by using Lyapunov’s stability theory. The proposed observer strategy achieves accurate observing performance of disturbance without increasing observer’s order, and chattering effect is also reduced by applying super-twisting algorithm. Furthermore, a super-twisting sliding mode control law is proposed to guarantee the asymptotic convergence of the drone’s orientation with respect to the reference. Finally, a numerical study based on simulations is presented to analyze the performance of proposed approach.

Independent Control of Temperature and Humidity in Air Conditioners by Using Fuzzy Sliding Mode Approach

This paper proposes a sliding mode control (SMC) strategy to solve the problem of independent control of temperature and humidity in air conditioners; the complexity increases due to the need to make full use of the wind side for cooling. First, dynamics of indoor temperature and humidity are determined based on mathematical models. Second, in order to reduce the chattering effect of SMC and coordinate indoor conditions to satisfy people’s needs, the independent control of temperature and humidity is realized via a novel fuzzy sliding mode control strategy based on reaching laws. Finally, simulation results are provided to verify the effectiveness of the proposed method.

A Decentralized Low-Chattering Sliding Mode Formation Flight Controller for a Swarm of UAVs

In this paper, a nonlinear robust formation flight controller for a swarm of unmanned aerial vehicles (UAVs) is presented. It is based on the virtual leader approach and is capable of achieving and maintaining a formation with time-varying shape. By using a decentralized architecture, the local controller in each UAV uses information only from the UAV itself, its neighbors, and from the virtual leader. Also, a synchronization control objective provides a mechanism to weight between the fleet achieving the desired formation shape, that is, achieving the desired relative position between the UAVs, and each UAV achieving its desired absolute position. The use of a combination of a sliding mode controller and a low pass filter reduces the usual chattering effect, providing a smooth control signal while maintaining robustness. Simulation results show the effectiveness of the proposed decentralized controller.

Evaluation of Hunting-Based Optimizers for a Quadrotor Sliding Mode Flight Controller

The design of Multi-Input Multi-Output nonlinear control systems for a quadrotor can be a difficult task. Nature inspired optimization techniques can greatly improve the design of non-linear control systems. Two recently proposed hunting-based swarm intelligence inspired techniques are the Grey Wolf Optimizer (GWO) and the Ant Lion Optimizer (ALO). This paper proposes the use of both GWO and ALO techniques to design a Sliding Mode Control (SMC) flight system for tracking improvement of altitude and attitude in a quadrotor dynamic model. SMC is a nonlinear technique which requires that its strictly coupled parameters related to continuous and discontinuous components be correctly adjusted for proper operation. This requires minimizing the tracking error while keeping the chattering effect and control signal magnitude within suitable limits. The performance achieved with both GWO and ALO, considering realistic disturbed flight scenarios are presented and compared to the classical Particle Swarm Optimization (PSO) algorithm. Simulated results are presented showing that GWO and ALO outperformed PSO in terms of precise tracking, for ideal and disturbed conditions. It is shown that the higher stochastic nature of these hunting-based algorithms provided more confidence in local optima avoidance, suggesting feasibility of getting a more precise tracking for practical use.