Robust Adaptive Control Law Research Articles

Robust Adaptive Control for Dynamic Positioning of Ships

In this paper, a robust adaptive control scheme with the global asymptotic stability with respect to positioning errors is proposed for dynamic positioning (DP) of ships in the presence of time-varying unknown bounded environmental disturbances. The unknown environmental disturbances are expressed as the outputs of a linear exosystem with unknown parameters and all eigenvalues of system matrix lying on the imaginary axis. On the basis of this exosystem, the disturbances are further represented as the outputs of a linear model of canonical form with unknown disturbances being inputs by a multivariate linear regression model whose regressor is the state vector of the linear model and whose regression parameters depend on unknown parameters of the linear exosystem. This representation allows us to construct an observer to estimate the unavailable state vector (regressor) in the linear model and hence convert the disturbance compensation control for the DP of ships to an adaptive control problem. Then, a robust adaptive control law for the DP of ships is designed incorporating the constructed observer and the projection algorithm into the vectorial backstepping method. The global asymptotic stability with respect to positioning errors of the DP closed-loop control system is proved applying Lyapunov stability theory and Barbalat's lemma. Finally, simulation results on a supply ship Northern Clipper in two different disturbance cases and simulation comparisons with an existing DP adaptive robust control scheme demonstrate more effectiveness and less conservativeness of our proposed control scheme.

High-performance adaptive robust control with balanced torque allocation for the over-actuated cutter-head driving system in tunnel boring machine

The tunnel boring machine(TBM) is a kind of large-scale underground equipment for the tunnel and subway excavations. The cutter-head driving system is one of the key components in hard rock TBM, which is driven by multiple motors to provide enough torque during the excavation. Synchronizing motions of the multiple driving motors and balancing the driving torques are two essential control issues to be addressed of cutter-head driving system. However, the existing synchronization control approaches usually focus on the pure motion synchronization of the multiple driving motors only. These methods will lead to the phenomena of uneven driving torques even when their motions are quite well synchronized, and may result in the shaft broken accident. Instead in this paper, an adaptive robust control law integrated with torque allocation technique scheme is proposed that achieves not only better motion synchronization of the driving motors but also simultaneous regulation of driving torques. Namely, the adaptive robust control (ARC) is introduced to deal with the negative effects from uncertainties and variable load acting on the cutter-head. And a torque allocation algorithm is proposed to distribute the driving torque of each motor evenly. Comparative simulations are carried out to verify the excellent performance of the proposed scheme.

Robust adaptive vibration control for an uncertain flexible Timoshenko robotic manipulator with input and output constraints

ABSTRACTThe problems of the constraints and the vibration suppression are investigated for the flexible Timoshenko robotic manipulator in this paper. Robust adaptive boundary control laws with the disturbance observes are designed to guarantee the convergence of the feedback flexible Timoshenko robotic manipulator system with the uncertain parameters and the states are proven to be uniform bounded. In addition, the proposed boundary controls are verified to be effectiveness by the numeral experiments.

Performance-Oriented Coordinated Adaptive Robust Control for Four-Wheel Independently Driven Skid Steer Mobile Robot

Four-wheel independently driven skid-steered mobile robots are widely used in the fields of industrial automation and outdoor exploration. In most of existing controllers of skid-steered mobile robots, the wheel velocities are controlled independently to track the desired velocities from the high-level kinematic controller. However, this kind of control method may lead to chattering phenomenon of skid-steered mobile robots in practice, when the desired velocity commands of four wheels are not matched under different ground conditions. In this paper, the coordinated control problem is investigated for the four-wheel independently driven skid steer mobile robots, so as to solve the chattering phenomenon and also achieve good control performance under different ground conditions. Since the mobile robots are over-actuated and lack of suspension systems, a coordinated adaptive robust control scheme integrated with torque allocation technique is proposed. First, an adaptive robust control law is developed to attenuate the negative effects of load variations and uncertainties. Second, instead of directly giving the desired velocity commands, a torque control and allocation algorithm is developed to regulate the driving torque of each wheel motor. A coordinated control law with considering the wheel slip compensation is also proposed. Comparative experiments are carried out, and the results show the proposed scheme can avoid the chattering problem and achieve the excellent performance under different ground conditions.

Two time-scale observer-based robust motion controller design and realization of a linear actuator

In this paper, an observer-based sliding mode controller is proposed for a high-accuracy motion plant to suppress the disturbances and improve the tracking performance. In particular, a two time-scale separation technology, which can recover the disturbance state in a faster time scale, is utilized to compensate the disturbances and improve the system robustness. The parameter identification is carried out to obtain the model coefficients with a high fitting rate. Such an identified model can allow the engineers to tune the controller’s gains highly enough when the system suffers from the measurement noises. Instead of the traditional low-pass filter, a differentiator is introduced for the velocity signal prediction and its discrete-time version is provided to attenuate the noises effect. To verify the effectiveness of the proposed approach, an adaptive robust control law is compared with the proposed one in terms of dynamic positioning error, robustness and rapid signal tracking, and the superiority and advantages can be illustrated by the experimental results.

Robust Control for Nonlinear Systems with Nonlinear Characteristics

본 연에서는 미지의 데드존을 갖는 시 연속 비선형 동적 시스템에 대해서 견실한 적응제어 법칙을 제안하였다. 액츄에터의 비선형특성은 제어 시스템에서 흔하게 존재하게 된다. 이러한 여러 비선형 특성은 데드존, 백래쉬, 히스테리시스, 또는 피이스와이스 선형에 대해서 부드럽지 않은(넌 스무스)한 특성을 가지게 된다. 이러한 비선형특성을 갖는 제어 시스템에 대해서 많은 연구가들이 제안한 제어법칙들은 대부분 역 데드존을 활용해서 제어법칙들을 제안하였다. 본 연구에서 제안하는 견실한 적응제어 법칙은 역 데드존을 사용하지 않고 제안하였으며, 데드존에 대해서 직관과 수학적인 관점에서의 모델을 활용하였다. 제안된 법칙에 대해서 리아프노프 정리를 활용하여 대역적 안정도에 대해서 증명을 통해서 제시 하였다. 제안된 제어기에 대해서 수치적 예를 통한 결과로부터 제안된 알고리즘의 타당성을 검증 하였다.

Switching control system based on robust model reference adaptive control

For conventional adaptive control, time-varying parametric uncertainty and unmodeled dynamics are ticklish problems, which will lead to undesirable performance or even instability and nonrobust behavior, respectively. In this study, a class of discrete-time switched systems with unmodeled dynamics is taken into consideration. Moreover, nonlinear systems are here supposed to be approximated with the class of switched systems considered in this paper, and thereby switching control design is investigated for both switched systems and nonlinear systems to assure stability and performance. For robustness against unmodeled dynamics and uncertainty, robust model reference adaptive control (RMRAC) law is developed as the basis of controller design for each individual subsystem in the switched systems or nonlinear systems. Meanwhile, two different switching laws are presented for switched systems and nonlinear systems, respectively. Thereby, the authors incorporate the corresponding switching law into the RMRAC law to construct two schemes of switching control respectively for the two kinds of controlled systems. Both closed-loop analyses and simulation examples are provided to illustrate the validity of the two proposed switching control schemes. Furthermore, as to the proposed scheme for nonlinear systems, its potential for practical application is demonstrated through simulations of longitudinal control for F-16 aircraft.

Adaptive Robust Coordinated Control for Over-actuated Cutter-head Driving Systems of Hard Rock Tunnel Boring Machines

Abstract: The cutter-head system of tunnel boring machines (TBM) is one of the key components for rock cutting and excavation. In this paper, the coordinated control problem is investigated for the over-actuated cutter-head driving system of TBM. A generalized nonlinear time-varying dynamic model is developed for the hard rock TBM cutter-head driving system. An adaptive robust control law integrated with control allocation technique is proposed, which controls the cutter-head to desired velocities while driving torques are well coordinated. Specially, the adaptive robust control (ARC) is used to deal with the negative effects of various uncertainties and variable loads acting on the cutter-head, and a coordinated control scheme with appropriate control allocation is developed to distribute the driving torque of each motor evenly. Comparative simulations are carried out to verify the excellent performance of the proposed scheme. The results suggest that, with the proposed control scheme, the motion performance is guaranteed and the driving torques are also well coordinated, validating the effectiveness and the performance improvement of the proposed control strategy.

Impact time control guidance with field-of-view constraint accounting for uncertain system lag

The problem of impact time control guidance with seeker’s field-of-view constraint in the presence of uncertain system lag is addressed. A novel two-step control approach based impact time control guidance law with seeker’s field-of-view constraint is proposed. Specifically, in the first step, a state constrained robust adaptive control law, using the dynamic surface control method combining with the control integral barrier Lyapunov function technique, is synthesized to achieve the required robust tracking performance with respect to the desired trajectory of lead angle in the presence of uncertain system lag and other uncertainties. In the second step, the desired trajectory of lead angle is generated online to guarantee target interception at the designated impact time under the assumption of ideal autopilot dynamics while not violating the seeker’ field-of-view constraint. The proposed guidance law ensures the seeker’s field-of-view constraint does not be violated in the presence of uncertain system lag and other uncertainties. Numerical simulations are provided to illustrate the effectiveness of the proposed guidance law.

Smooth shift control of an automatic transmission for heavy-duty vehicles

In this paper, a robust shift control strategy of a heavy duty vehicle powertrain system is investigated for enhancing shift quality. To analyse the shift transient phenomena, the dynamic models for various powertrain components, such as engine, torque converter, transmission and drivetrain, are developed. Three different robust adaptive control laws are derived for the different process control that reduces the output torque during the gear shifts. In deriving the control laws, both the engine and automatic transmission dynamics have been included. In order to overcome the challenge of the relevant variables characterizing the performance of the powertrain is not measurable because of sensor cost and reliability considerations. The integrated controller proposed uses only angular velocity signals, such as engine speed, turbine speed and output speed, which are inexpensive to measure and easy to implement. Finally, the designed control strategy is tested on a heavy-duty vehicle equipped with automatic transmission. Results from the experimental studies show that the proposed control strategy can effectively reduce shift shock and smooth the gear shift.

Adaptive sliding mode control for re-entry attitude of near space hypersonic vehicle based on backstepping design

Combining sliding mode control method with radial basis function neural network (RBFNN), this paper proposes a robust adaptive control scheme based on backstepping design for re-entry attitude tracking control of near space hypersonic vehicle (NSHV) in the presence of parameter variations and external disturbances. In the attitude angle loop, a robust adaptive virtual control law is designed by using the adaptive method to estimate the unknown upper bound of the compound uncertainties. In the angular velocity loop, an adaptive sliding mode control law is designed to suppress the effect of parameter variations and external disturbances. The main benefit of the sliding mode control is robustness to parameter variations and external disturbances. To further improve the control performance, RBFNNs are introduced to approximate the compound uncertainties in the attitude angle loop and angular velocity loop, respectively. Based on Lyapunov stability theory, the tracking errors are shown to be asymptotically stable. Simulation results show that the proposed control system attains a satisfied control performance and is robust against parameter variations and external disturbances.

Robust adaptive tracking control of MIMO nonlinear systems in the presence of actuator hysteresis

Adaptive tracking control of a class of MIMO nonlinear system preceded by unknown hysteresis is investigated. Based on dynamic surface control, an adaptive robust control law is developed and compensators are designed to mitigate the influences of both the unknown bounded external uncertainties and the unknown Prandtl–Islinskii hysteresis. By adopting the low-pass filters, the explosion of complexity caused by tedious computation of the time derivatives of the virtual control laws is overcome. With the proposed control scheme, the closed-loop system is proved to be semi-globally ultimately bounded by the Lyapunov stability theory, and the output of the controlled system can track the desired trajectories with an arbitrarily small error. Finally, numerical simulations are given to verify the effectiveness of the proposed approach.

Characteristic model-based H 2/H ∞ robust adaptive control during the re-entry of hypersonic cruise vehicles

This paper aims at introducing H2 and H∞ robustness into the well-known characteristic model-based golden-section adaptive control law, and applying the robust adaptive control scheme to the attitude control of hypersonic cruise vehicles that are subject to external disturbances and aerodynamic coefficients uncertainties. When maneuvering at ultra high speeds, the attitude system of the hypersonic cruise vehicle is extremely sensitive to external disturbances and aerodynamic coefficients variations, and therefore the adaptiveness and the robustness of the attitude system are crucial during the controller design. To enhance the robustness of the existing golden-section adaptive control law, a golden-section robust adaptive control law is proposed. Compared to the existing control law where the design of the parameter λ depends on experience and is carried out offline, linear matrix inequality-based synthesis of λ is proposed such that the closed-loop system is stable with guaranteed H2 and H∞ performance. It is suitable for online computing and provides a time-varying λ(k) that is adjusted towards the optimal H2 and H∞ performance. When being applied to the attitude control of hypersonic vehicles during re-entry, the adaptive nature of the proposed control law provides the attitude system the capability to accommodate large flight conditions, and its H2 and H∞ robustness brought by λ(k) guarantees satisfying tracking performance in the presence of disturbances including both external disturbance and absolute aerodynamic coefficients errors.

Constraint robust adaptive stabilization for a class of lower triangular systems with unknown control direction

This paper studies the constrained robust adaptive stabilization problem for a class of lower triangular systems with unknown control direction. A robust adaptive feedback control law for the systems is proposed by incorporating the technique of Barrier Lyapunov Function with Nussbaum gain. Such a controlled system arises from the study of the constrained robust output regulation problem for a class of output feedback systems with the unknown control direction and a nonlinear exosystem. An application of the constrained robust adaptive stabilization design leads to the solution of the constrained robust output regulation problem in the sense that the output tracking error is constrained within the prescribed barrier limit while asymptotically approaching to zero and the closed loop signals are all bounded for all the time. A numerical example is provided to illustrate the performance of the proposed control.

Robust adaptive neural network control of a class of uncertain strict-feedback nonlinear systems with unknown dead-zone and disturbances

In this paper, a robust adaptive neural control design approach is presented for a class of perturbed strict-feedback nonlinear systems with unknown dead-zone. In the controller design, different from existing methods, all the virtual control laws need not be actually implemented at intermediate steps, and only one actual robust adaptive control law is constructed by approximating the lumped unknown function of the system with a single neural network at the last step. By this approach, the structure of the designed controller is much simpler since the causes for the problem of complexity growing in existing methods are eliminated. Stability analysis shows that the proposed scheme can guarantee the uniform ultimate boundedness of all the closed-loop system signals, and the steady-state tracking error can be made arbitrarily small by appropriately choosing control parameters. Simulation studies demonstrate the effectiveness and merits of the proposed approach.

Adaptive position tracking control system based on recurrent fuzzy wavelet neural networks for robot manipulators

In this article, we propose an adaptive recurrent fuzzy wavelet neural network control strategy to improve high-accuracy position tracking for robot manipulators. In order to deal with the unknown knowledge of the robot system problems, the adaptive recurrent fuzzy wavelet neural networks are applied in the main controller to approximate the unknown dynamics without the requirement of prior knowledge. In addition, an adaptive robust control law is also developed to eliminate uncertainties that consist of estimation errors and disturbances from the robot control system. The design of the adaptive online learning algorithms is determined using the Lyapunov stability theorem. Therefore, the proposed controller proves that it can guarantee not only the stability and robustness but also the tracking performance of the robot manipulators control system. The effectiveness and robustness of the proposed method are demonstrated by comparative simulation and experimental results.

A performance oriented multi-loop constrained adaptive robust tracking control of one-degree-of-freedom mechanical systems: Theory and experiments

A performance oriented multi-loop approach to the adaptive robust tracking control of one-degree-of-freedom mechanical systems with input saturation, state constraints, parametric uncertainties and input disturbances is presented. The control system contains three loops. In the outer loop, constrained optimization algorithms are developed to generate a replanned trajectory on-line at a low sampling rate so that the converging speed of the overall system response to the desired target is maximized while not causing input saturation and the violation of state constraints. In the inner loop, a constrained adaptive robust control (ARC) law is synthesized and implemented at high sampling rate to achieve the required robust tracking performances with respect to the replanned trajectory even with various types of uncertainties and input saturation. In the middle loop, a set-membership identification (SMI) algorithm is implemented to obtain a tighter estimate of the upper bound of the inertia so that more aggressive replanned trajectory could be used to further improve the overall system response speed. Interaction of the three loops is explicitly characterized by a set of inequalities that the design variables of each loop have to satisfy. It is theoretically shown that the resulting closed-loop system can track feasible desired trajectories with a guaranteed converging time and steady-state tracking accuracy without violating the state constraints. Experiments have been carried out on a linear motor driven industrial positioning system to compare the proposed multi-loop constrained ARC algorithm with some of the traditional control algorithms. Comparative experimental results obtained confirm the superior performance of the proposed algorithm over existing ones.

Online constrained optimization based adaptive robust control of a class of MIMO nonlinear systems with matched uncertainties and input/state constraints

A performance oriented two-loop control approach is proposed for a class of multiple-input–multiple-output (MIMO) systems with input saturation, state constraints, matched parametric uncertainties and input disturbances. In the inner loop, a constrained adaptive robust control (ARC) law is synthesized to achieve the required robust tracking performances with respect to on-line replanned trajectory in the presence of input saturation and various types of matched uncertainties. In the outer loop, a replanned trajectory is generated by solving a constrained optimization algorithm online to minimize the converging time of the overall system response to the desired trajectory while not violating various constraints. Interaction of the two loops is explicitly characterized by a set of inequalities that the design variables of each loop have to satisfy. It is theoretically shown that the resulting closed-loop system can track feasible desired trajectories with a guaranteed converging time and steady-state tracking accuracy without violating the state constraints. Since the system in study is most appropriate to describe the dynamics of the robotic systems, the control of a two-axis planar robotic manipulator is used as an application example. Comparative simulation results demonstrate the advantage of the proposed approach over the traditional approaches in practical applications.

Adaptive Synchronization between Fractional-Order Chaotic Real and Complex Systems with Unknown Parameters

The complex modified projective synchronization (CMPS) between fractional-order chaotic real and complex systems is investigated for the first time. The parameters of both master and slave systems are assumed to be unknown in advance; moreover, the slave system is perturbed by unknown but bounded external disturbances. The master and slave systems that achieved CMPS can be synchronized up to a complex constant matrix. On the basis of frequency distributed model of fractional integrator and Lyapunov stability theory, a robust adaptive control law is designed to realize the CMPS for two different types of fractional-order chaotic systems. Meanwhile, to deal with these unknown parameters, some fractional-order type parametric update laws are provided. An example is given to demonstrate the effectiveness and feasibility of the proposed synchronization scheme.

A Robust Adaptive Sliding Mode Control Method for Attitude Control of the Quad-Rotor

Quad-rotor is a multi-variable and strong coupling system which has nonlinear and uncertainties. According to the quad-rotor, a dynamic model of attitude which included uncertainty parameters and unknown disturbances was established. The tracking error state was used to design a slide mode surface, and a Lyapunov function which includes slide mode surface and unknown parameter was built. Further more, a robust adaptive control law was designed. At last, the designed control law was simulated, and the results justify the feasibility of the proposed control law.