Distributed adaptive containment control of uncertain QUAV multiagents with time-varying payloads and multiple variable constraints

This paper considers the containment control problem for uncertain QUAV (Quadrotor Unmanned Aerial Vehicle) multiagents with time-varying payloads under a fixed topology graph, and a distributed adaptive containment control protocol with multiple variable constraints is proposed. Generally, the control framework is classified into two layers. In the first layer, the desired trajectories are determined for followers by the communication topology and initial values of leaders. For the second layer, the ith QUAV follower is required to track the desired trajectory by employing the information of itself and neighbors. Under the second layer, the system of the ith agent is decoupled into two subsystems: the translational subsystem and the rotational subsystem. For the translational subsystem, the distributed adaptive containment controller is designed via dynamic surface control method to track the desired position trajectory. With such method, the information requirement of ith agent for its neighbors can be reduced significantly. For the rotational subsystem, the adaptive tracking controller is constructed to track the desired attitudes derived from translational subsystem through commonly used attitudes extraction algorithms. In the end, the resulting closed-loop system is proved to be stable in the sense of uniformly ultimate boundness, and the effectiveness of the proposed approach is illustrated by numerical simulations.     

Formation-containment control of networked Euler–Lagrange systems: An event-triggered framework

To improve the concurrency of leaders’ formation and followers’ containment, a difficult problem of designing the formation controller and the containment controller simultaneously should be addressed for networked systems. Motivated by this, this paper presents an even-triggered control framework for networked Euler–Lagrange systems to achieve formation-containment control even in the presence of uncertain parameters. An event-triggered formation controller is firstly designed for leaders to achieve the desired configuration. An event-triggered containment control law is then developed to guarantee that all the followers can converge to the convex hull formed by leaders. The key feature of the containment control law is that it does not necessitate any relative velocity information with respect to neighbor followers. Each controller’s gains are adaptively tuned using only local information. The parametric uncertainties are accommodated by using the adaptive updating law. Zeno behaviors of the triggering time sequences are also excluded. As a result, the communication burden of formation-containment system can be reduced. Numerical simulation is finally presented to verify the effectiveness of the proposed event-triggered formation-containment control framework.     

Surrounding control of nonlinear multi-agent systems with non-identical agents

In this paper, the surrounding control problem of a group of non-identical agents is considered, where a team of followers achieves an equidistant distributed formation to surround a team of moving leaders. An adaptive design method is presented for multi-agent systems where the dynamics of agents are supposed to be nonlinear with unknown parameters. First, an estimator for the center of the leaders is introduced. Then, two distributed adaptive controllers based on the estimated center are proposed for each follower. The stability and parameter convergence of the proposed protocols are shown by using algebraic graph theory and Lyapunov theory. Finally, a numerical example is provided to validate the theoretical results.     

输入受限的非完整移动机器人的自适应模糊控制

提出了一种非完整移动机器人饱和自适应模糊轨迹跟踪控制方法,该方法基于反演技术分别设计了系统的运动学控制器和动力学控制器。运动学控制器通过引入分流控制技术解决了初始速度跳变引起的控制量突变问题,动力学控制器利用饱和函数和受限控制参数实现了其有界力矩控制。自适应模糊控制器将模糊逻辑系统与自适应方法相结合,有效消除了常规方法难以解决的系统未知不确定性对系统的影响。通过Lyapunov直接法证明了该系统是收敛且渐进稳定的。仿真结果验证了所设计控制器的良好控制性能和强鲁棒性。     

Adaptive integral feedback controller for pitch and yaw channels of an AUV with actuator saturations

Input saturations and uncertain dynamics are among the practical challenges in control of autonomous vehicles. Adaptive control is known as a proper method to deal with the uncertain dynamics of these systems. Therefore, incorporating the ability to confront with input saturation in adaptive controllers can be valuable. In this paper, an adaptive autopilot is presented for the pitch and yaw channels of an autonomous underwater vehicle (AUV) in the presence of input saturations. This will be performed by combination of a model reference adaptive control (MRAC) with integral state feedback with a modern anti-windup (AW) compensator. MRAC with integral state feedback is commonly used in autonomous vehicles. However, some proper modifications need to be taken into account in order to cope with the saturation problem. To this end, a Riccati-based anti-windup (AW) compensator is employed. The presented technique is applied to the non-linear six degrees of freedom (DOF) model of an AUV and the obtained results are compared with that of its baseline method. Several simulation scenarios are executed in the pitch and yaw channels to evaluate the controller performance. Moreover, effectiveness of proposed adaptive controller is comprehensively investigated by implementing Monte Carlo simulations. The obtained results verify the performance of proposed method.     

Event-triggered decentralized adaptive fault-tolerant control of uncertain interconnected nonlinear systems with actuator failures

This paper investigates the event-triggered decentralized adaptive tracking problem of a class of uncertain interconnected nonlinear systems with unexpected actuator failures. It is assumed that local control signals are transmitted to local actuators with time-varying faults whenever predefined conditions for triggering events are satisfied. Compared with the existing control-input-based event-triggering strategy for adaptive control of uncertain nonlinear systems, the aim of this paper is to propose a tracking-error-based event-triggering strategy in the decentralized adaptive fault-tolerant tracking framework. The proposed approach can relax drastic changes in control inputs caused by actuator faults in the existing triggering strategy. The stability of the proposed event-triggering control system is analyzed in the Lyapunov sense. Finally, simulation comparisons of the proposed and existing approaches are provided to show the effectiveness of the proposed theoretical result in the presence of actuator faults.     

On decentralized adaptive full-order sliding mode control of multiple UAVs

In this study, a novel decentralized adaptive full-order sliding mode control framework is proposed for the robust synchronized formation motion of multiple unmanned aerial vehicles (UAVs) subject to system uncertainty. First, a full-order sliding mode surface in a decentralized manner is designed to incorporate both the individual position tracking error and the synchronized formation error while the UAV group is engaged in building a certain desired geometric pattern in three dimensional space. Second, a decentralized virtual plant controller is constructed which allows the embedded low-pass filter to attain the chattering free property of the sliding mode controller. In addition, robust adaptive technique is integrated in the decentralized chattering free sliding control design in order to handle unknown bounded uncertainties, without requirements for assuming a priori knowledge of bounds on the system uncertainties as stated in conventional chattering free control methods. Subsequently, system robustness as well as stability of the decentralized full-order sliding mode control of multiple UAVs is synthesized. Numerical simulation results illustrate the effectiveness of the proposed control framework to achieve robust 3D formation flight of the multi-UAV system.     

一类施加单向控制量的不确定非线性系统的重复学习控制

针对存在有界的、周期变化的非线性不确定动态的二阶系统,提出一种使系统渐近地跟踪目标轨迹的控制律。考虑仅能施加单向控制量的系统,所提出的控制律利用饱和函数和基于在线学习的估计器相结合来学习和估计未知非线性动态特性,并对未知动态进行补偿以保证系统跟踪误差渐近收敛于零。同时引入自适应陷波滤波器（Adaptive notch filter,ANF）来在线估计未知非线性动态特性的频率。不同于以前的方法,提出的基于ANF的饱和改进型重复控制律只需要未知动态特性是有界的（未知动态特性的结构、参数、频率是不需要预先知道的）。最后将此控制律应用到只能提供竖直向上电磁力的EMS型磁悬浮系统中,设计出适合磁悬浮系统的控制策略。仿真结果证明了所提出的控制策略的有效性。     

Adaptive fuzzy prescribed performance control for MIMO nonlinear systems with unknown control direction and unknown dead-zone inputs

In this study, an adaptive fuzzy prescribed performance control approach is developed for a class of uncertain multi-input and multi-output (MIMO) nonlinear systems with unknown control direction and unknown dead-zone inputs. The properties of symmetric matrix are exploited to design adaptive fuzzy prescribed performance controller, and a Nussbaum-type function is incorporated in the controller to estimate the unknown control direction. This method has two prominent advantages: it does not require the priori knowledge of control direction and only three parameters need to be updated on-line for this MIMO systems. It is proved that all the signals in the resulting closed-loop system are bounded and that the tracking errors converge to a small residual set with the prescribed performance bounds. The effectiveness of the proposed approach is validated by simulation results.     

Robust cooperation of connected vehicle systems with eigenvalue-bounded interaction topologies in the presence of uncertain dynamics

This study presents a distributed H-infinity control method for uncertain platoons with dimensionally and structurally unknown interaction topologies provided that the associated topological eigenvalues are bounded by a predesigned range.With an inverse model to compensate for nonlinear powertrain dynamics, vehicles in a platoon are modeled by third-order uncertain systems with bounded disturbances. On the basis of the eigenvalue decomposition of topological matrices, we convert the platoon system to a norm-bounded uncertain part and a diagonally structured certain part by applying linear transformation. We then use a common Lyapunov method to design a distributed H-infinity controller. Numerically, two linear matrix inequalities corresponding to the minimum and maximum eigenvalues should be solved. The resulting controller can tolerate interaction topologies with eigenvalues located in a certain range. The proposed method can also ensure robustness performance and disturbance attenuation ability for the closed-loop platoon system. Hardware-in-the-loop tests are performed to validate the effectiveness of our method.     

A new discrete-time robust adaptive time-delay control for a class of uncertain nonlinear strict-feedback systems using sliding mode

This paper presents a new discrete-time adaptive second-order sliding mode control with time delay estimation (TDE) for a class of uncertain nonlinear time-varying strict-feedback systems. The existing researches on time delay control (TDC) are conventionally established based on a stability criterion that is subject to the infinitesimal time delay assumption. Recently, this criterion was rejected and a new criterion was proposed for the development of a controller for systems with fully known dynamics. In this study, this approach is extended to uncertain systems. Specifically, a new criterion is developed for the stability of the TDE-error within an adaptive robust controller design without the infinitesimal time delay assumption. With the proposed adaptive robust control, there is no need for determination of uncertainties upper-bounds. Simulation results illustrate the efficacy of the proposed controller.     

Adaptive fuzzy wavelet network control of second order multi-agent systems with unknown nonlinear dynamics

In this paper, consensus problem is considered for second order multi-agent systems with unknown nonlinear dynamics under undirected graphs. A novel distributed control strategy is suggested for leaderless systems based on adaptive fuzzy wavelet networks. Adaptive fuzzy wavelet networks are employed to compensate for the effect of unknown nonlinear dynamics. Moreover, the proposed method is developed for leader following systems and leader following systems with state time delays. Lyapunov functions are applied to prove uniformly ultimately bounded stability of closed loop systems and to obtain adaptive laws. Three simulation examples are presented to illustrate the effectiveness of the proposed control algorithms.     

Distributed adaptive neural networks leader-following formation control for quadrotors with directed switching topologies

The leader-following formation problem is discussed for a team of quadrotors under directed switching topologies. To obtain a more general dynamic model, we describe the quadrotor system in a non-affine pure-feedback form with mismatched unknown nonlinearities. By employing an adaptive neural networks state observer to approximate the unknown nonlinear functions and to reconstruct the immeasurable inner states, we propose a novel distributed output feedback formation control protocol with the backstepping method combining with the dynamic surface control technique. From the Lyapunov stability theorem, all signals in the closed-loop formation system are proven to be cooperatively semiglobally uniformly ultimately bounded for any given bounded initial conditions. Finally, we proved that we verify the performance of the proposed formation control approach by a simulation study.     

[电动汽车稳定性控制]异质队列的分布式鲁棒解耦控制

Based on the distributed control structure and interaction topology modeled by graph theory, a decoupled robust control strategy was presented for a heterogeneous vehicular platoon to deal with the uncertainties of node dynamics. The dynamical behavior of node composed of vehicle dynamics and a lower-level controller was assumed to be covered by a multiplicative uncertainty model. Then to decouple the platoon system, which  was skillfully decomposed into a H∞ norm bounded uncertain part and a diagonal system by applying linear transformation and eigenvalue decomposition on communication topology. The requirements of robust stability, tracking ability and vehicular platoon stability were analyzed theoretically. Comparative bench tests with a non-robust controller and different communication topologies were conducted to demonstrate its robust stability, tracking ability and vehicular platoon.     

Improved prescribed performance control for air-breathing hypersonic vehicles with unknown deadzone input nonlinearity

An improved prescribed performance controller is proposed for the longitudinal model of an air-breathing hypersonic vehicle (AHV) subject to uncertain dynamics and input nonlinearity. Different from the traditional non-affine model requiring non-affine functions to be differentiable, this paper utilizes a semi-decomposed non-affine model with non-affine functions being locally semi-bounded and possibly in-differentiable. A new error transformation combined with novel prescribed performance functions is proposed to bypass complex deductions caused by conventional error constraint approaches and circumvent high frequency chattering in control inputs. On the basis of backstepping technique, the improved prescribed performance controller with low structural and computational complexity is designed. The methodology guarantees the altitude and velocity tracking error within transient and steady state performance envelopes and presents excellent robustness against uncertain dynamics and deadzone input nonlinearity. Simulation results demonstrate the efficacy of the proposed method.     

采用非线性流量特性补偿的直驱式变转速泵控系统轨迹跟踪控制

变转速电机-泵直驱电液系统的发展与伺服技术的提升使得泵控系统在保留高能效特性的同时,具有更高的硬件集成度和更快的响应速度;但是在低转速泵控工况下,此类系统依旧存在泵的流量非线性、流量偏差大等控制难点,使得变转速泵控系统难以完成高精度的执行器运动轨迹跟踪。为实现泵控液压缸系统的精密运动控制,提出了一种新颖的非线性流映射方案,以此得到精确的泵输出流量;同时,利用非线性自适应鲁棒反演控制策略(Adaptive Robust Controller Backstepping,ARCB)实现液压系统在高阶动力学、参数不确定性下的精确控制。试验表明,提出的控制策略可有效解决变转速泵的流量偏差问题,实现理想的控制性能和轨迹跟踪精度。     

控制力矩受限情况下漂浮基柔性空间机械臂鲁棒自适应控制

讨论控制力矩受限情况下,参数不确定的漂浮基柔性空间机械臂系统的智能控制问题。结合系统动量守恒关系和拉格朗日-假设模态法建立系统动力学方程。为了同时实现漂浮基柔性空间机械臂系统载体姿态和关节运动轨迹的渐近跟踪以及系统弹性振动的抑制,基于奇异摄动法将系统分解为快变和慢变两个子系统。针对快变子系统设计二次最优控制方法以抑制柔性臂引起的系统弹性振动,保证系统的稳定性;针对慢变子系统提出一种鲁棒自适应混合控制方法。该方法利用连续可导递增函数来限制控制力矩的幅值大小,使控制更符合空间实际要求;利用鲁棒自适应调节器来克服系统不确定参数的影响,保证系统的控制精度。计算机仿真结果证明了所提出方法的有效性。     

Convergence performance comparisons of PID,MRAC, and PID + MRAC hybrid controller

This study proposes a hybrid controller by combining a proportional-integral-derivative (PID) control and a model reference adaptive control (MRAC), which named as PID + MRAC controller. The convergence performances of the PID control, MRAC, and hybrid PID + MRAC are also compared. Through the simulation in Matlab, the results show that the convergence speed and performance of the MRAC and the PID + MRAC controller are better than those of the PID controller. In addition, the convergence performance of the hybrid control is better than that of the MRAC control.     

Anti-disturbance dynamic surface control scheme for a class of uncertain nonlinear systems with asymmetric dead-zone nonlinearity

This study proposes anti-disturbance dynamic surface control scheme for nonlinear strict-feedback systems subjected simultaneously to unknown asymmetric dead-zone nonlinearity, unmatched external disturbance and uncertain nonlinear dynamics. Radial basis function-neural network (RBF-NN) is invoked to approximate the uncertain dynamics of the system, and the dead-zone nonlinearity is represented as a time-varying system with a bounded disturbance. The nonlinear disturbance observer (NDO) is proposed to estimate the unmatched external disturbance which further will be used to compensate the effect of the disturbance. Then, by integrating RBF-NN, NDO and dynamic surface control (DSC) approaches, the proposed anti-disturbance control scheme is designed. Stability analysis of the closed-loop system shows that all signals of the closed-loop system are semi-globally uniformly ultimately bounded and the tracking error can be made arbitrarily small by proper selection of the design parameters. In comparison with the existing methods, the proposed scheme deals with the unmatched external disturbance, uncertain dynamics and unknown asymmetric dead-zone nonlinearity, simultaneously; it avoids the "explosion of complexity" problem and develops the simple control law without singularity concern. Furthermore, some imposed assumptions to the dead-zone input and disturbances are relaxed. Simulation and comparison results verify the effectiveness of the proposed approach.     

Experimental evaluation of adaptive three-tank level control

Liquid level control through regulation of mass flow rates is an important application in various areas of the power industry. Very often a PID controller is used for these applications. This paper compares a nonconventional PID controller and three different types of adaptive controller, a direct model reference adaptive controller (MRAC), an indirect MRAC with Lyapunov estimation, and an indirect MRAC with recursive least-squares (RLS) updating estimation, for liquid level control. By implementing all four controllers on a three-tank system, the performances of each are compared. All controllers track a sinusoidal input very well and overall exhibit somewhat varying performance. The direct MRAC and the indirect MRAC with RLS estimation give the best performance. With Lyapunov estimation and RLS estimation, all the system parameter estimates converge to the reference model values. However, RLS estimation has a much faster convergence. It is concluded that adaptive liquid level control is an improvement over traditional liquid level control when precise level control in three coupled tanks is desired.