Adaptive Robust Control and Active Vibration Suppression of Dumbbell-Shaped Spacecraft

A new adaptive robust fuzzy control (ARFC) algorithm is presented for a class of nonlinear systems with unstructured uncertainties which are coming from modelling errors and external disturbances. In the algorithm, without any prior knowledge of the bounding functions of the uncertainties, Takagi-Sugeno type fuzzy logic systems are employed to approximate uncertain functions. A systematic procedure is developed for the synthesis of adaptive robust fuzzy control whose adaptive mechanism has minimal learning parameterizations by use of dissipative theoretical approach and small gain approach. Application example illustrating the method described is included for ship roll system, which is shown that the designed system guarantees the performance of the global asymptotic stability.

This paper focuses on the synthesis of nonlinear adaptive robust controller with saturated actuator authority for a linear motor drive system, which is subject to parametric uncertainties, unmodeled nonlinearities and input disturbances as well. Global stability is achieved by breaking down the overall uncertainties to state-linearly-dependent uncertainties (such as viscous friction) and bounded nonlinearities (such as coulomb friction, cogging force and etc.) and treating them with different strategies. Furthermore, a guaranteed transient performance and final tracking accuracy can be obtained by incorporating the well-developed adaptive robust controller and effective parameter identifier. Asymptotic output tracking is also achievable in the presence of parametric uncertainties only. Meanwhile, the choice of design parameters is easier to make with the controller designed based on the original states which have physical meanings than the existing control structure with saturation designed in a transformed coordinate

In the paper, based on a combination of the robust control approach and an adaptive control technique, a design procedure of a new robust adaptive controller is proposed for power system load-frequency control with system parametric uncertainties. The system parametric uncertainties are obtained by changing parameters by 30% to 50% simultaneously from their typical values. In the design of the proposed controller, only the bounds of system parameters are required. The motivation of combining the robust control with an adaptive control is to use the robust control approach to deal with the small parametric uncertainties and to use the adaptive control for large parametric uncertainties so that stability of the overall system and good performance can both be achieved for all admissible uncertainties. The simulation results demonstrate that for the example system the proposed load-frequency controller can achieve good performance even in the presence of the generation rate constraint (GRC).

In this paper, a quadrotor with two manipulators constrained on a straight path is modeled and a robust adaptive controller is proposed for it. Adding two manipulators to quadrotor increases its capabilities and applications in industry. Here, these two manipulators are used to place the robot on a constraint path so that the quadrotor can perform monitoring operations more accurately, because the under-actuated quadrotor becomes over-actuated by these constrained manipulators and one can use this feature to accurately control the position of the robot. Reduced form of motion equations are derived for the constrained quadrotor and based on this a robust adaptive controller is proposed. The nonlinear terms in the dynamic model are approximated by basic functions with constant weights and adaptive laws are designed by projection operator. Stability analysis is performed based on the Lyapunov theory. Evaluation of the presented controller is done by some numerical simulations. The simulation results showed that the robot tracks the reference path with bounded error in spite of dynamic uncertainties and wind force and satisfies the considered constraints.

This paper focuses on a frequency-weighted hybrid adaptive control with application tosimultaneous precision positioning and vibration suppression of smart composite structures.Following the introduction of the structure and materials system of an active compositepanel (ACP) with a surface-mounted and two embedded piezoelectric ceramic patches, thesensor selection for the purpose of precision positioning or vibration control is discussed,and the function assignment of a laser displacement sensor as well as the embeddedpiezoelectric sensor is determined for the ACP. The frequency-weighted hybrid adaptivecontrol approach is then developed. The approach consists of an adaptive feedforwardposition controller for precision positioning, an adaptive feedforward vibrationcontroller for vibration suppression as well as an adaptive feedback controller for bothprecision positioning and vibration suppression. The frequency-weighted filtersintroduced in the approach realize the signal fusion of the two sensors. Finally,experiments are also performed for harmonic disturbances at the first two naturalfrequencies of the ACP and a random disturbance for both cases of with/without theadaptive feedforward vibration controller, demonstrating that the frequency-weightedhybrid adaptive control approach can provide satisfactory precision positioningand vibration suppression in both cases, and that better position accuracy canbe achieved if the adaptive feedforward vibration controller is also employed.

FEED-FORWARD/FEEDBACK CONTROL FOR ACTIVE VIBRATION SUPPRESSION OF FLEXIBLE SPACECRAFT DURING ATTITUDE MANEUVER

In this article, a robust adaptive self-structuring fuzzy control (RASFC) scheme for the uncertain or ill-defined nonlinear, nonaffine systems is proposed. The RASFC scheme is composed of a robust adaptive controller and a self-structuring fuzzy controller. In the self-structuring fuzzy controller design, a novel self-structuring fuzzy system (SFS) is used to approximate the unknown plant nonlinearity, and the SFS can automatically grow and prune fuzzy rules to realise a compact fuzzy rule base. The robust adaptive controller is designed to achieve an L 2 tracking performance to stabilise the closed-loop system. This L 2 tracking performance can provide a clear expression of tracking error in terms of the sum of lumped uncertainty and external disturbance, which has not been shown in previous works. Finally, five examples are presented to show that the proposed RASFC scheme can achieve favourable tracking performance, yet heavy computational burden is relieved.

A pneumatic parallel platform driven by an air cylinder and three circumambient pneumatic muscles was considered. Firstly, a mathematical model of the pneumatic servo system was developed for the MIMO nonlinear model-based controller designed. The pneumatic muscles were controlled by three proportional position valves, and the air cylinder was controlled by a proportional pressure valve. As the forward kinematics of this structure had no analytical solution, the control strategy should be designed in joint space. A cross-coupling integral adaptive robust controller (CCIARC) which combined cross-coupling control strategy and traditional adaptive robust control (ARC) theory was developed by back-stepping method to accomplish trajectory tracking control of the parallel platform. The cross-coupling part of the controller stabilized the length error in joint space as well as the synchronization error, and the adaptive robust control part attenuated the adverse effects of modelling error and disturbance. The force character of the pneumatic muscles was difficult to model precisely, so the on-line recursive least square estimation (RLSE) method was employed to modify the model compensation. The projector mapping method was used to condition the RLSE algorithm to bound the parameters estimated. An integral feedback part was added to the traditional robust function to reduce the negative influence of the slow time-varying characteristic of pneumatic muscles and enhance the ability of trajectory tracking. The stability of the controller designed was proved through Laypunov’s theory. Various contrast controllers were designed to testify the newly designed components of the CCIARC. Extensive experiments were conducted to illustrate the performance of the controller.

A torque controller based on adaptive robust control is proposed for trajectory tracking of nonholonomic wheeled mobile robot with kinematic and dynamic uncertainties. In this controller, the parametric uncertainties are estimated by the adaptive control, and the non-parametric uncertainties are compensated by the adaptive robust control. The operation efficiency of the system is improved by distinguishing the differences between parametric and non-parametric uncertainties. Furthermore, the transient performance of adaptive control is optimized by the adaptive robust control and the measurements of uncertainties bounds are avoided, this strengthened the applicability of the controller. The uniformly ultimately bounded of closed-loop control system is proved by the Lyapunov theory. Simulations show that the adversely impacts of complex system uncertainties can be eliminated effectively and the high-precision trajectory tracking is guaranteed.

This paper focuses on an adaptive robust dynamic surface control (ARDSC) with composite adaptation laws (CAL) for a class of uncertain nonlinear systems in semi‐strict feedback form. A simple and effective controller has been obtained by introducing dynamic surface control (DSC) technique and designing novel adaptation laws. First, the ‘explosion of terms’ problem caused by backstepping method in the traditional adaptive robust control (ARC) is avoided. Meanwhile, through a new proof philosophy the asymptotical output tracking that the ARC possesses is theoretically preserved. Second, when persistent excitation (PE) condition satisfies, true parameter estimates could be acquired via designing CALs which integrate the information of estimation errors. Finally, simulation results are presented to illustrate the effectiveness of the proposed method. Copyright © 2010 John Wiley & Sons, Ltd.

The design of a new hybrid controller for fractional-order uncertain chaotic systems with unknown time-varying delays

PurposeThe purpose of this paper is to propose an adaptive robust controller for coupled attitude and orbit control of rigid spacecraft based on dual quaternion in the presence of external disturbances and model uncertainties.Design/methodology/approachFirst, based on dual quaternion, a theoretical model of the relative motion for rigid spacecraft is introduced. Then, an adaptive robust controller which can realize coordinated control of attitude and orbit is designed in the existence of external disturbances and model uncertainties.FindingsThis paper takes advantage of the Lyapunov function which can guarantee the asymptotic stabilization of the whole system in the existence of parameters uncertainties. Simulation results show that the proposed controller is feasible and effective.Originality/valueThis paper proposes a coupled attitude and orbit adaptive robust controller based on dual quaternion. Simulation results demonstrate that the proposed controller can achieve higher control performance in the presence of parameters uncertainties.

Liquid sloshing in moving or stationary containers and flexible uncertainty caused by the slosh are considered to be the most probable causing unexpected coupling effects on the dynamics of many systems such as aerospace, ground vehicles, and high speed industries arms. The coupling of dynamic liquid slosh in a container system with the uncertainty caused by the sensors or dampers is rare documented and this coupling can be considered as a highly nonlinear system. In this paper, an investigation is presented to demonstrate a new approach for enabling the reduction of the liquid slosh and uncertainty by implementing adaptive robust wavelet control technique. Starting by creating the mathematical dynamic model for the nonlinear slosh coupled by uncertainty, adaptive robust control based wavelet transform is applied for calculating optimal motion that minimize residual slosh and uncertainty. Subsequently the adaptive robust control based wavelet network approximation and the appropriate parameter algorithms for the container system with slosh and uncertainty are derived to achieve the feedback linearization, adaptive control, and H∞ tracking performance. The simulation results show that the effects of slosh errors and external uncertainty can be successfully attenuated within a desired attenuation level.

Hydraulic system is widely used in industry where large actuation forces are needed such as electro-hydraulic positioning system, active suspension control, and so on. One of the main problem in hydraulic system is the nontriviality, for instance, the deadbands in valve operation, frictions of links, saturations, pressure dynamics, etc. both system unknown nonlinearities and external disturbances should be considered in controller design. For underwater hydraulic manipulator, because of the environment of sea and the large nonlinearities of the hydraulic manipulator system, both system unknown nonlinearities and external disturbances should be considered in controller design. A lot of control methods have been proposed to solve the problem properly, such as sliding mode control, adaptive control, fuzzy adaptive control, adaptive robust control, ect. However, due to limited knowledge about hydraulic manipulator system, it is hard to precisely estimate the nonlinearities for a possible higher performance. In this paper, a neural network adaptive robust control method is proposed to help control an underwater hydraulic manipulator. In order to achieve better performance using adaptive robust control strategy, unknown nonlinearities in the system are approximated by the outputs of radial basis function neural network (RBFNNs). A projection law has been used to bound the NN weights when they are tuning on-line to avoid possible adaptive divergence, and the tracking transient performance is guaranteed by robust control law. Simulation results illustrate that manipulator has a good tracking performance.

To keep the attitude control of maneuvering reentry vehicle in reentry phase, the strict feedback attitude model of reentry vehicle with time-varying parameters is built. An adaptive robust controller is designed based on backstepping, which consists of backstepping adaptive control and robust control. The controller design method uses adaptive strategies to estimate the unknown parameters, introduces robust control to avoid the singularity in parameters estimation of gain matrix phase. Theoretical analysis shows that all signals of the closed-loop system are proved intimately uniform bounded. Simulation results of six-degree-of-freedom demonstrate that the proposed control method has strong robust performance.