Aiming at unknown disturbances/uncertainties, partial effectiveness loss fault (PELF) and stuck failure (SF) of the actuator, a composite robust fault-tolerant control strategy based on incremental backstepping (IBS) is proposed for a reusable launch vehicle (RLV) during re-entry. By converting PELF to disturbances/uncertainties, this paper presents an incremental form of disturbance observer based on an improved inverse hyperbolic sine tracking differentiator (IHSTD) to compensate these interference terms originally ignored in the IBS design process. Furthermore, a failure symbol matrix is set to control the on-off states of the reaction control system of the RLV to make up for the missing torque of the actuator SF, which can strengthen the fault-tolerance capability of the control system. The simulation results show that the tracking effect of the proposed method on the attitude-angle commands is better than traditional backstepping with disturbance observer, and the presented control allocation strategy is capable of timely resolving the actuator SF problem to ensure stability of flight.

In this paper, an improved predictor-corrector algorithm with hybrid lateral logic is proposed to enhance the maneuverability during re-entry, which lets the reusable launch vehicle (RLV) possess the ability of avoiding a no-fly zone. First, the longitudinal guidance is converted to the quasi-equilibrium guidance algorithm once current states satisfy the joint point condition. During each guidance period in the gliding phase, a quadratic parametric model is devised to adjust the magnitude of the bank angle instead of utilizing the linear one. Then, an artificial potential field based lateral guidance law is designed for no-fly zone avoidance by transforming the problem into finding the reference heading angle. But the bank angle reverses while the RLV is approaching the target, which may aggravate the instability problem and increase the energy consumption. Aiming at above problem, the lateral guidance is combined with conventional heading angle deadband corridor, which works when the RLV leaves the influence area of the no-fly zone. Finally, numerical simulations show that the proposed lateral guidance logic not only is effective for no-fly zone, but also performs well in reducing the times of reversals. The Monte Carlo simulation results further demonstrate the robustness of the above guidance algorithm considering the random initial dispersions and errors.

In this paper, the maneuver flight control scheme is proposed for the hypersonic glide vehicle (HGV). The system uncertainty, unknown external disturbances and input saturation are explicitly considered in the controller design. Firstly, the maneuver control architecture of lateral turning for the HGV is developed, and then a robust attitude controller is constructed to execute the maneuver command accurately. To estimate the system uncertainty and unknown external disturbances, this paper presents a modified nonlinear disturbance observer (MNDO) which can guarantee that the estimate error signals are uniformly ultimately bounded. Secondly, an auxiliary design system is constructed to reduce the adverse effect of input saturation. Based on the developed MNDO and the auxiliary system, a robust attitude controller is designed for the HGV using the backstepping method. The tracking error is proved to be uniformly ultimately bounded by the Lyapunov method and its bound is adjustable. Finally, simulation results show the effectiveness of the proposed robust maneuver flight controller.

The control of the hypersonic glide vehicle (HGV) during re-entry is confronted with the input saturation and unknown dynamical uncertainty problem. A nonlinear anti-windup (AW) compensation control method is designed to deal with the nonlinear control problem caused by the saturation of the control surfaces of the HGV. The scheme transforms the problem of saturation control into the optimization problem through nonlinear matrix inequality (NMIL) constraints, which is solved by particle swarm optimization (PSO). The saturation situation can be relieved within a short time and the satisfactory control performance is attained by the method. Then, a novel sigmoid function tracking differentiator based disturbance observer (STDDO) is proposed to estimate parameter uncertainties and external disturbances for the problem of dynamical uncertainties. This method does not need the priori information about the bounds of disturbances and has global fast convergence property. Finally, the simulation results show the effectiveness and robustness of the proposed control scheme.

The maneuver control of hypersonic vehicles (HSVs) during re-entry is a challenging work due to the object features of serious nonlinearity, strong uncertainty and fast time variation. In this paper, we design the maneuver control architecture of lateral turning for the HSV first, and then a new self-organizing recurrent functional link network (SORFLN) is proposed to estimate the dynamical uncertainties/disturbances in flight. The SORFLN-based nonlinear controller is presented to compensate for the effect of uncertainties. The training algorithm to grow the SORFLN and adapt the parameters is derived from Lyapunov theory. The pruning strategy to keep the SORFLN size as small as possible is put forward based on the output features of the nodes. Finally, the simulation results show that the presented method can achieve satisfactory control performance and the uncertainty/disturbance rejection is successfully accomplished with small size of the network.

A nonlinear anti-windup(AW) control compensator based on improved cooperative optimization algorithm(ICOA) is proposed to deal with the control problem caused by the saturation of the control surfaces of the hypersonic vehicle(HSV) during re-entry. Firstly, saturated link is added in the system controller, and the model of AW compensator is designed according to the HSV system equations. Then, the nonlinear L2 gain structure is introduced with the purpose of optimizing the performance of system, which transforms the problem of saturation control into the optimization problem through nonlinear matrix inequality (NMIL) constraints. The optimization problem is solved by an ICOA. Finally, the simulation results show the effectiveness of the proposed method. The saturation situation can be relieved within a short time and the satisfactory control performance is attained by the presented method.

In this paper a novel sliding mode method is proposed to reduce the chattering phenomenon. Instead of the switching surface in traditional SMC method, the unidirectional auxiliary surfaces are utilized to design SMC controller in this paper. With different unidirectional auxiliary surfaces, the chattering phenomenon and robustness of the SMC controller can be adjusted according to requirements. Based on this idea, we might find a new way to build a balance between the robustness and chattering reduction in SMC methods. And simulation results are given to illustrate the benefits and properties of the proposed algorithm.

The control of the hypersonic glide vehicle (HGV) during reentry is confronted with the unknown dynamical disturbance and parameter uncertainty problem. In this paper, we use the HGV mathematical model with an assumption that the earth is spherical first, and then a new self-organizing functional link network (SOFLN) is presented to approximate the dynamical disturbances/uncertainties. Finally, the SOFLN-based controller is designed to offset the effect of disturbances/uncertainties. The Lyapunov function is utilized to design the growing strategy of the SOFLN, and the pruning strategy is put forward according to output features of the FLN nodes. The online training algorithm of SOFLN weights is derived from Lyapunov theory. The simulation results show that the SOFLN-based controller can find the appropriate network topology to approximate the disturbances/uncertainties during reentry and compensate for their effects to achieve good interference rejection capability and satisfactory control performance.

It is difficult for the traditional pan-tilt-zoom (PTZ) system driven by electromagnetic motor to meet the growing demand for video surveillance system. The key bottleneck problem is high positioning accuracy, high dynamic performance and miniaturization of the PTZ system. This paper presents a PTZ system driven by two degree-of-freedom obelisk-shaped ultrasonic motor with single stator, and makes research on its intelligent control algorithm. First, analyses of the structure, driving mechanism and electromechanical coupling system characteristic of the PTZ system are conducted using both the method of simulation and experiment. Then for the sake of solving the complex nonlinear factors, parameter variation and external disturbance, this paper combines the fuzzy logic algorithm and the sliding mode control strategy to improve the control performance. The results of simulation show that this algorithm proposed in this paper has faster response, higher precision and also has a good robustness to prevent the effect of interference.

In this paper, a novel sliding mode method is proposed to suppress the chattering phenomenon with unstable surfaces. Unlike the conventional sliding mode control methods, these unstable surfaces are utilized to design an available sliding mode structure. The main idea of this method is to design a sliding mode controller following a new reaching condition with unstable auxiliary surfaces. Based on this idea, we might find a new way to design a large number of different sliding mode controllers to solve the chattering problem of sliding mode method. The simulation results are given to illustrate the benefits and properties of the proposed method.

A new direction is proposed to reduce the chattering phenomenon in SMC methods. Unlike the previous chattering-free SMC methods, the discontinuous switching function in this direction is considered as a necessary part to guarantee the continuity of control u. The main idea of this direction is to build a continuous control u with two discontinuous components. Based on this idea, we might find a new way to eliminate the contradictions between the robustness and chattering reduction. A chattering-free SMC method is proposed as an example under this direction. And simulation results are given to illustrate the benefits and properties of the proposed direction.

In order to improve the adaptive ability and robustness of the system, the wavelet neural network (WNN) single-scaling frame function with robust controller is used to design the controller. The WNN has self-learning and adaptive ability to approximate nonlinear functions. Combined with the trajectory linearization control (TLC) method, the adaptive robust control strategy and the NSV attitude control system are designed. Then simulations are taken to demonstrate the effectiveness.

A stable adaptive auxiliary system is designed according to the input constraints problem for the near space vehicle (NSV) in reentry phase, which can realize the compensation for control saturation. The NSV flies with the large angle of attack during reentry, and the compound control mode of aero-surfaces and reaction control system is adopted. Then, the reentry attitude control system of the NSV is designed using the second-order terminal sliding mode control law combined with the saturation compensation. Finally, the sliding mode disturbance observer is employed to estimate the aerodynamic parameter uncertainty and external disturbance. Meanwhile, its compensation adaptive law is deduced. The simulation results show the effectiveness and robustness of this scheme.

Near-space hypersonic vehicles (NHVs) are viewed as reliable, affordable and global reach vehicles. Their controller design is a challenging task due to strong uncertainties and disturbances in the flight dynamics of NHVs. In this paper, a new methodology is presented to build control-oriented models of two kinds of disturbances. For a winged-cone NHV, the paper models the moment disturbance induced by the thrust misalignment of the engine. Next, a new group of 12-state equations is obtained based on the kinetic and dynamic laws for the NHV with variable wind field, as the wind turbulence frequently occur in the upper near space. Then, the quantisation and simulation results about the models are provided to show the variation characteristics of the disturbances. Finally, the attitude control results are given to assess the adaptive control effect of the NHV with these two models. Therefore, in the presence of the thrust misalignment and wind disturbances, the control-oriented models presented can become the simulation tools which help us to evaluate adaptive control laws designed for NHVs.

A nonlinear intelligent reentry control method with B-spline functional link network disturbance observer (BFLNDO) is presented for hypersonic vehicles (HSVs). The nonlinear generalized predictive control (NGPC) algorithm is employed to design the nominal control law of the attitude system of the HSV. The output prediction defined on finite horizon is carried out via Taylor series expansion. The unmodeled dynamics and unknown uncertainties/disturbances during reentry are estimated by a new BFLNDO. The stability analyses of the BFLNDO and close-loop control system are provided also. Finally, the simulation results show satisfactory performance of the controller for the tracking of reentry attitude angles, and the intelligent uncertainty/disturbance rejection are successfully accomplished.

The controller design for an air-breathing hypersonic vehicle (AHV) is very challenging, mainly because of large uncertainties and disturbances existing in flight dynamics. For a specific AHV, this paper presents a new methodology to construct mathematical models of the main disturbances which are seldom involved by other AHV literatures. First, it considers the moment disturbance induced by the thrust misalignment of the engine. Second, a new group of 12 states nonlinear equations is derived for the AHV subjected to variable wind field. Finally, the simulation results of these disturbance models are given to express their features. Thus, the presented models can become the simulation tools employed to assess control laws of AHVs with thrust misalignment and wind disturbances.

A proportional-derivative (PD) correction partially-feedback-functional-link-network (PFFLN) control method is presented for air-breathing hypersonic vehicles (AHVs) with dynamical uncertainties. The control law consists of a nonlinear generalized predictive controller (NGPC), a PD-correction PFFLN control adjustment, and an adaptive robust control (RC) item. The latter two are used for approximating uncertainties in the slow-loop attitude system, and the PFFLN is applied to the fast-loop one. The network weights and robust gains are online tuned based on Lyapunov stability theorem and the learning process does not need offline training. Finally, simulation results show a satisfactory attitude control effect for the AHV subjected to dynamical uncertainties and disturbances.

As the flight envelop of near-space vehicle(NSV) is extremely large,the system may have strong nonlinearity and fast time-variability,especially when the velocity is hypersonic.Meanwhile,because of the airframe/engine integrated design,the aerodynamic and the propulsion have strong coupling.Both are big challenges for the controller design.Considering the flight task of NSV,the aerodynamic model and the engine system are analyzed first.Then the integrated aerodynamic/engine control model for hypersonic longitudinal motion of NSV is also studied and transformed into an affine nonlinear system using the input-output feedback linearization method.After that,for a class of uncertain nonlinear systems,a GPC(generalized predictive control) strategy based on sliding-mode surface is derived and an adaptive law is proposed to eliminate the systems' uncertainty using the universal approximation of T-S fuzzy system,then the control character of this method is analyzed via Lyapunov method.Finally,this strategy is used as an integrated flight/propulsion control law for the longitudinal motion of NSV,and the result of simulation experiment shows the effectiveness of fuzzy adaptive GPC.

The controller design for a near-space hypersonic vehicle (NHV) is challenging due to its plant uncertainties and sensitivity to atmospheric disturbances such as gusts and turbulence. This paper first derives 12 states equations of NHVs subjected to variable wind field, and presents a novel recurrent neural network (RNN) control method for restraining atmospheric disturbances. The method devises a new B-spline recurrent functional link network (BRFLN) and combines it with the nonlinear generalized predictive control (NGPC) algorithm. Moreover, the proportional-derivative (PD) correction BRFLN is proposed to approximate atmospheric disturbances in flight. The weights of BRFLN are online tuned by the adaptive law based on Lyapunov stability theorem. Finally, simulation results show a satisfactory performance for the attitude tracking of the NHV in the mesosphere, and also illustrate the controller’s robustness to wind turbulence.

This paper proposes a new recurrent neural network (NN) adaptive control method for air-breathing hypersonic vehicles (AHVs) in the presence of dynamical parameter uncertainties and disturbances. The control law mainly consists of the optimal generalized predictive control (OGPC) algorithm, and an adaptive adjustment of B-spline recurrent functional link network (BRFLN). The BRFLN, a new NN presented here, is applied to approximating dynamical uncertainties and disturbances. Moreover, a guaranteed global convergence algorithm, the stochastic particle swarm optimizer (SPSO) is employed to learn the self-connection weights of the BRFLN, which can improve the adaptability of the BRFLN. It is proved that the closed-loop system error is uniformly ultimately bounded. Finally, simulation results show that the controller designed attains a satisfactory performance for the AHV attitude tracking. © 2011 World Academic Press, UK. All rights reserved.