Adaptive Robust Control Technique Research Articles

Event-Triggered Adaptive Robust Control for a Class of Uncertain Nonlinear Systems With Application to Mechatronic System

Adaptive robust control technique is investigated to devise trajectory tracking event-triggered controller for a class of uncertain nonlinear systems. Different from the most existing results, this paper divides the entire control input into two parts, including model compensation input term and the robust term, which are separately dealt with by means of special triggered mechanisms. The advantage of separation is that the system reduces the magnitude of chattering amplitude within triggered inputs. To balance the information updating frequency and the magnitude of chattering amplitude, this paper proposes the dynamic threshold triggered mechanism and provides a new Lyapunov function to guarantee the global boundedness of all the closed-loop signals as well as the convergence of the tracking error to an arbitrary small set around zero. This paper also considers desired compensation adaptive robust event-triggered control strategy, thereby further saving bandwidth resources and smoothing the triggered inputs. The Zeno behavior is excluded for two triggering schemes. Finally, simulation and Hardware-in-the-loop (HIL) experiment are used to verify the effectiveness of the proposed strategies.

Robust Adaptive Control of a Riser-Vessel System in Three-Dimensional Space

In this study, an adaptive robust control technique for an uncertain riser-vessel system in a three-dimensional space is developed. A projection mapping technique and a hyperbolic tangent function are exploited to construct novel adaptive robust controllers based on adaptive laws dynamically updated online to restrain the vibration, tackle parametric uncertainties, compensate for the unknown upper bound of disturbances, and ensure robustness of the coupled system. Lyapunov’s method is adopted to analyze and demonstrate the bounded stability of the closed-loop system. Simulation results are provided to validate the feasibility and effectiveness of the proposed approach.

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.

Three-dimensional neural network tracking control of a moving target by underactuated autonomous underwater vehicles

This paper investigates three-dimensional target tracking control problem of underactuated autonomous underwater vehicles (AUVs) by using coordinates transformation and multi-layer neural networks. The passive-boundedness assumption of sway and heave velocities of underactuated AUVs is used to design a controller in the actuated directions. For this purpose, a new Euler–Lagrange formulation is proposed based on range and bearing tracking errors with respect to a moving target in the body-fixed frame. Then, a tracking controller is proposed to make range and bearing tracking errors converge to zero. Multi-layer neural networks (MLNNs) are utilized to approximate unknown nonlinear-in-parameter dynamics of the system, and adaptive robust control techniques are adopted to compensate for MLNN approximation errors and time-varying environmental disturbances which are induced by waves, wind and ocean currents. The stability of the proposed control system is analysed based on Lyapunov’s approach which shows that target tracking errors are semi-globally uniformly ultimately bounded and exponentially tend to a small neighbourhood around the zero. At the end, simulation examples are given to demonstrate the competency of the proposed target tracking controller.

Adaptive robust attitude control and active vibration suppression of flexible spacecraft

This paper presents the large angle attitude manoeuvre control design of a single-axis flexible spacecraft system that consists of a central rigid body and a cantilever beam with bonded piezoelectric sensor/actuator pairs as a flexible appendage. The proposed control strategy combines the attitude controller designed by the adaptive robust control technique with the active vibration controller designed by the positive position feedback control method. The desired angular position of the spacecraft is planned and an adaptive robust attitude control approach based on a projection type adaptation law is proposed to track the planned path and to achieve precise attitude manoeuvre control. Meanwhile, the positive position feedback control method is applied to actively increase the damping of the flexible appendage and to suppress the residual vibration induced by manoeuvre. Improved transient and steady state performance during and after large angle attitude manoeuvre can be both achieved by integration of the technical merits of all these control methods. Analytical and numerical results illustrate the effectiveness of this approach.

Integrated adaptive robust control for multilateral teleoperation systems under arbitrary time delays

SummaryWith the increasing industrial requirements such as bigger size object, stable operation, and complex task, multilateral teleoperation systems extended from traditional bilateral teleoperation are widely developed. In this paper, the integrated control design is developed for multilateral teleoperation systems, where n master manipulators are operated by human to remotely control n slave manipulators cooperatively handling a target object. For the first time, the control objectives of multilateral teleoperation including stability, synchronization, transparency, and internal force distribution are clarified systematically. A novel communication architecture is proposed to cope with communication delays, where the estimated environmental parameters are transmitted from the slave side to the master, to replace the traditional environmental force measurement in the communication channel. A kind of nonlinear adaptive robust control technique is used to deal with nonlinearities, unknown parameters, and modeling uncertainties existing in the master, slave, and environmental dynamics, so that the excellent tracking performance is achieved in both master and slave sides. The coordinated motion/force control is designed in the slave side by the optimal internal force distribution among n slave manipulators, and the impedance control is designed in the master side to realize the target transparency behavior. In summary, the proposed control algorithm can achieve the guaranteed robust stability, the excellent synchronization and transparency performance, and the optimal internal force distribution simultaneously for multilateral teleoperation systems under arbitrary time delays and various modeling uncertainties. The simulation is carried out on a 2‐master/2‐slave teleoperation system, and the results show the effectiveness of the proposed control design. Copyright © 2015 John Wiley & Sons, Ltd.

Neural adaptive robust control of underactuated marine surface vehicles with input saturation

This paper proposes a saturated tracking controller for underactuated autonomous marine surface vehicles with limited torque. First, a second-order open-loop error dynamic model is developed in the actuated degrees of freedom to simplify the design procedure. Then, a saturated tracking controller is designed by utilizing generalized saturation functions to reduce the risk of actuator saturation. This, in turn, improves the transient performance of the control system. A multi-layer neural network and adaptive robust control techniques are also employed to preserve the controller robustness against unmodeled dynamics and environmental disturbances induced by waves and ocean currents. A Lyapunov stability analysis shows that all signals of the closed-loop system are bounded and tracking errors are semi-globally uniformly ultimately bounded. Finally, simulation results are provided for a hovercraft vehicle to illustrate the effectiveness of the proposed controller as a qualified candidate for real implementations in offshore applications.

Leader–follower formation control of underactuated autonomous marine surface vehicles with limited torque

This paper proposes a leader–follower formation tracking controller for underactuated autonomous marine surface vehicles with limited torque under environmental disturbances. A second-order formation dynamic model is developed in the actuated degrees of freedom of the followers to simplify the design procedure. Then, a formation tracking controller is designed by utilizing generalized saturation functions to reduce the risk of actuator saturation. Radial basis function neural network and adaptive robust control techniques are also adopted to preserve the controller robustness against unmodeled dynamics and environmental disturbances induced by waves and ocean currents. A Lyapunov-based stability analysis shows that all signals of the closed-loop system are bounded and tracking errors are semi-globally uniformly ultimately bounded. Finally, simulation results are provided for a group of surface vessels to illustrate the effectiveness of the proposed controller as a qualified candidate for real implementations in offshore applications.

Modular adaptive robust control of SISO nonlinear systems in a semi‐strict feedback form

AbstractIn this paper, a modular modification of the adaptive robust control (ARC) technique is presented. The modular design has all of the original ARC properties with an estimation‐based update law instead of a Lyapunov‐based update law. In this design, the controller is divided into two modules: a control module and an identification module. A key new idea is to set a priori bounds on the time derivatives of the estimates to be maintained by the update law. As a result, their effects on the system tracking accuracy can be dominated by the control law. A modification is proposed for the standard gradient and least‐square update laws to guarantee the bounds. This modification also makes the controller robust against the generalized (unparameterized) uncertainties considered in the ARC formulation while allowing asymptotic output tracking without the generalized uncertainties. Both the ARC and the modular ARC techniques are applied to a force control problem for an active suspension system. Simulations and experimental results are provided to show that the update law of the modular design is less sensitive to measurement noise which results in smaller force tracking error and smaller control gain. Copyright © 2004 John Wiley & Sons, Ltd.