Decentralized Sliding Mode Control for Multi‐Input Complex Interconnected Systems Subject to non‐smooth Nonlinearities

Adaptive fuzzy control for full states constrained systems with nonstrict-feedback form and unknown nonlinear dead zone

In this paper, we consider a terminal sliding mode control method for anti-synchronization of chaotic systems containing dead-zone nonlinearity. Based on the Lyapunov stability theorem, a terminal sliding mode controller is designed so that the states tracking error can reach the terminal sliding mode surface and converge to zero in a finite time. Finally, a Duffing-Holmes chaotic system is used to demonstrate the effectiveness of the proposed control law.

To achieve the requirements of lightweight, low energy consumption, and low inertia of an underwater vehicle manipulator system, a cable-driven manipulator is installed on the underwater vehicle to form a cable-driven flexible-joint-based underwater vehicle manipulator system (CDFJ–UVMS). The CDFJ–UVMS is a complex nonlinear system subject to model uncertainties, complex marine environment disturbances, and actuator dead-zone nonlinearity. To design track controllers, the CDFJ–UVMS dynamics is divided into two parts: known and unknown. Subsequently, a radial basis function neural network is adopted to approximate the unknown nonlinearity. A neural network performance observer is constructed, whose estimation error is then used to design a novel neural disturbance observer (NDO) to estimate the total disturbance. Finally, an adaptive neural network control method is proposed for the CDFJ–UVMS based on the NDO, neural network compensator, and neural performance observer. The stability of the closed-loop system is analyzed using the Lyapunov method. The proposed control algorithm is applied to a CDFJ–UVMS with two cable-driven joints and compared with other control methods to show the effectiveness of the proposed control algorithm.

Recursive identification for Hammerstein–Wiener systems with dead-zone input nonlinearity

This paper studies an adaptive tracking control for a class of multi-input multi-output (MIMO) non-affine nonlinear systems, with input dead-zone nonlinearity and external disturbances. By using the mean-value theorem, the system model is transformed into an affine form so as the difficulty in controlling non-affine systems is overcome. In the proposed control design, neural networks (NNs) are used to approximate the unknown nonlinearities based on their universal approximation properties. To compensate for approximation errors and external disturbances, an adaptive robust control term is introduced. In comparison with existing approaches, the structure of the designed controller is considerably simpler, and can handle a wider range of nonlinear systems. The stability of the closed-loop system is investigated by using Lyapunov theory. The simulation results illustrate the proposed method.

Interval type-2 fuzzy adaptive tracking control design for PMDC motor with the sector dead-zones

This article presents an original motion control strategy for robot manipulators based on the coupling of the inverse dynamics method with the so-called second-order sliding mode control approach. Using this method, in principle, all the coupling non-linearities in the dynamical model of the manipulator are compensated, transforming the multi-input non-linear system into a linear and decoupled one. Actually, since the inverse dynamics relies on an identified model, some residual uncertain terms remain and perturb the linear and decoupled system. This motivates the use of a robust control design approach to complete the control scheme. In this article the sliding mode control methodology is adopted. Sliding mode control has many appreciable features, such as design simplicity and robustness versus a wide class of uncertainties and disturbances. Yet conventional sliding mode control seems inappropriate to be applied in robotics since it can generate the so-called chattering effect, which can be destructive for the controlled robot. In this article, this problem is suitably circumvented by designing a second-order sliding mode controller capable of generating a continuous control law making the proposed sliding mode controller actually applicable to industrial robots. To build the inverse dynamics part of the proposed controller, a suitable dynamical model of the system has been formulated, and its parameters have been accurately identified relying on a practical MIMO identification procedure recently devised. The proposed inverse dynamics-based second-order sliding mode controller has been experimentally tested on a COMAU SMART3-S2 industrial manipulator, demonstrating the tracking properties and the good performances of the controlled system.

The attitude tracking control problem of flexible spacecraft subjected to parameter uncertainties, time-dependent external disturbances, actuator input nonlinearity, and input actuator misalignment is investigated in this paper. Explicitly, the proposed strategy addresses the input actuator misalignment and dead-zone issues that increase the controller design difficulties. Initially, a new second-order sliding mode observer (SoSMO) using an extended state approach is developed by adding a correction function to improve observer performance to estimate unwanted system perturbations. Then, a distinct SoSMO-based integral-type sliding mode control (ISMC) structure is designed in a unified manner to guarantee the asymptotic stability of the closed-loop system. Comparative numerical simulations under input actuator misalignment, the dead-zone nonlinearity, external disturbance, and inertia uncertainty are performed to illustrate the effectiveness of the proposed controller.

In this paper, a novel second order sliding mode control approach is extended toa class of complex interconnected systems with mismatched interconnections and unknown perturbations. The key contribution of this paper is to cancel two common restrictions clogging the application of the variable structure control to complex interconnected systems: 1) all of state variables must be accessible; 2) the control input is affected by chattering problems. First, a novel reduced-order sliding mode estimator (ROSME) is proposed to estimate the unmeasurable variables. Second, based on Moore-Penrose inverse technique and ROSME tool, a new decentralized chattering-free second order robustness sliding mode controller (CSORSMC) is developed to force the system states to stay in a sliding surface from the initial period instance and attenuate the chattering phenomenon in the control signal. Besides, a novel appropriate linear matrix inequality (LMI) requirement is proved such that the plant in sliding mode is asymptotically stable. Lastly, a mathematical model including two subsystems is simulated which confirms the usefulness and advantages of proposed technique.

This paper concerns the finite time tracking control problem for the longitudinal model of an airbreathing hypersonic vehicle (AHV) with actuator faults and external disturbances. First, the dynamics of system outputs V and h are given by calculating the differentials. Next, combining external disturbances and actuator additive faults as lumped disturbances, a nonlinear disturbance observer (NDOB) is designed to estimate them. Then, two integral sliding mode manifolds are designed based on tracking errors. Finally, combining NDOB and integral sliding mode control (SMC) techniques, a composite fault tolerant controller is constructed for the longitudinal model of an AHV. This control approach can make the velocity and altitude track the reference signals in finite time and reduce chattering phenomenon caused by SMC. Simulation results are given to show the effectiveness of the proposed control method.

This paper suggests a new hybrid control strategy, called Optimal Type II Fuzzy Sliding Mode (OT2FSM) control scheme, to realize the control of general uncertain chaotic systems. The proposed controller not only guaranties the stability and robustness against the lumped uncertainties caused by unmodeled dynamics and external disturbances, but also can significantly reduce the control chattering inherent in conventional sliding mode control. In the proposed controller, a novel heuristic algorithm namely particle swarm optimization with random inertia weight (RNW–PSO) is employed. To achieve an optimal performance, the parameters of the proposed controller as well as the input and output membership functions are optimized simultaneously by RNW–PSO. The globally asymptotic stability of the closed-loop system is mathematically proved. To evaluate the performance of the proposed controller, the results are compared with those obtained by Optimal H-infinity Adaptive PID (OHAPID) controller and an optimal Type-2 fuzzy proportional integral derivative (OT2FPID), which are the latest researches in the problem in hand. Simulation results show the effectiveness of the OT2FSM controller.

Terminal sliding mode control for coordinated motion of a space rigid manipulator with external disturbance

An effective method, adaptive fuzzy sliding-mode (SM) PI Control to design full-bridge inverter is proposed in this paper. For practical applications, sliding mode control (SMC) with chattering phenomenon is a large hindrance. The modified model of the PI controller is built by the plant extension scheme, in order to relieve the chattering. Also, the fuzzy logic is applied to find the appropriate parameter values of the PI controller, and can adapt to plant parameter variations and external load disturbances. The proposed method has been realized for the actual full-bridge inverters controlled by DSP and CPLD. Simulation and experimental results of the closed-loop system show that the proposed method yields system performance improvement, such as low total harmonic distortion (THD), fast dynamic response, reduced steady-state error, and reduced chattering.

This study proposes a finite-time tracking control system for an unmanned aerial vehicle (UAV) in the presence of dynamic payloads and external disturbances. Changes in payload result in time-varying parametric uncertainties, making traditional control strategies ineffective. A sliding mode control (SMC) scheme is designed to handle uncertainties in both translational and rotational dynamics. A finite-time SMC (FTSMC) approach is developed to handle unknown time-varying mass and external disturbances in the translational dynamics. Furthermore, differences in the payload influence the inertia characteristics of the UAV, introducing further uncertainties in the feedback control design. A finite-time sliding mode controller is also implemented for rotational dynamics to guarantee the attitude stabilization under unknown inertia parameter variations. The proposed method has the objective to attenuate the chattering effect associated with traditional SMC within a finite time frame. Theoretical stability analysis with rigorous mathematical proofs is presented to confirm the effectiveness of the control scheme. Numerical simulations are provided to validate its performance under dynamic operating conditions.

In this paper, an adaptive fast terminal sliding mode control technique combined with a global sliding mode control scheme is investigated for the tracking problem of uncertain nonlinear third-order systems. The proposed robust tracking controller is formulated based on the Lyapunov stability theory and guarantees the existence of the sliding mode around the sliding surface in a finite time. Under the uncertainty and nonlinearity effects, the reaching phase is removed and the chattering phenomenon is eliminated. This scheme guarantees robustness against nonlinear functions, parameter uncertainties and external disturbances. The derivative of the state variable is replaced by a delay term in the form of an Euler approximation of the derivative function. Furthermore, the knowledge of upper bounds of the system uncertainties is not required, which is more flexible in the real implementations. Simulation results are presented to show the effectiveness of the suggested method.