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To solve the control problem of time-varying state-scale nonlinear systems whose initial state is not affected by settling time, fixed-time convergence algorithms are proposed for first-order systems and higher-order systems in this paper. First, a scalar model is used to illustrate how the time-varying feedback parameter can guarantee that the system achieves asymptotic stability while achieving finite-time convergence, and it is proved that the settling time obtained in this paper is only related to the prescribed boundary. This allows us to design the settling time with an appropriate parameter based on the prescribed boundary. To exhibit the effectiveness and extensibility of the proposed algorithm for first-order scalar systems, the results are subsequently extended to general higher-order systems based on the backstepping method. By introducing numerical simulation results, this paper verifies that the proposed algorithm will make the system achieve asymptotic stability and its output can converge to a given boundary, regardless of the system's initial states. [ABSTRACT FROM AUTHOR]

This paper designs event-triggered delay compensation and disturbance attenuation control algorithms for multi-agent systems. First, through predictor-based model reduction method, an unknown large input delay can be compensated and delay-free dynamics is obtained. Based on the transformed systems, predictive descriptor observers are proposed to obtain estimated system states and sensor faults. Then, an event-triggered fault-tolerant algorithm is designed to save energy resources for communication among the agents while attenuating the disturbances. Moreover, it is validated that the systems do not exhibit Zeno behaviour using the designed event-triggering sequence. Numerical simulations are conducted to demonstrate the effectiveness of designed algorithms. [ABSTRACT FROM AUTHOR]

Finding feasible solutions to motion planning and control problem of robotic systems in different environments with various applications is an active area of research. This article presents a new solution to the motion planning and control problem of a three-dimensional articulated mobile manipulator comprising a car-like mobile platform and a three-dimensional n-link articulated arm using the Lyapunov-based control scheme. The motion of the system is described as twofold: first, the car-like mobile platform moves from an initial position to its pseudo-target, and second, when the mobile platform is within some predefined distance from the pseudo-target, the end-effector of the robot arm is attracted to its designated target. Therefore, presenting a new 2-Step Algorithm in this paper for dual movement of the articulated mobile manipulator in 3D. In addition, a workspace cluttered with fixed spherical and rod obstacles of random sizes and positions is considered in this research. For the mobile manipulator to avoid an obstacle, the Minimum Distance Technique is adapted where a point on the robot that is closest to an obstacle will avoid the obstacle. The convergence of the two bodies and the stability of the mechanical system are guaranteed by the Lyapunov's direct method. The continuous nonlinear control laws proposed from the control scheme also take into account all mechanical singularities and velocity limitations associated with the system. Theoretical proofs and computer simulations validate the new continuous, acceleration-based, nonlinear, time-invariant control laws. [ABSTRACT FROM AUTHOR]

This paper proposes a new hybrid robust control method for control of an autonomous underwater vehicle. Fractional sliding mode control (FSMC) is robust against external disturbances. The main drawback of the FSMC method is creating a chattering phenomenon. Therefore, a compound control method is applied, which benefits in both robustness of the FSMC method and chattering elimination by the new control algorithm. A random noise is applied in order to verify the robustness of the proposed control method. The stability of FSMC and proposed compound control method has been verified by Lyapunov theory. The effectiveness of the proposed control method is compared with FSMC, which numerical simulation results confirm the best performance of the proposed control method. [ABSTRACT FROM AUTHOR]

The initial value problems (IVPs) of Caputo fractional-order differential equations are very important in control systems modelling and simulation. A series of numerical algorithms are proposed in the paper in solving systematically various kinds of Caputo equations. For linear Caputo equations, the divergent problems of the existing Taylor auxiliary function are pointed out, and two effective algorithms are presented to transform the nonzero IVPs into zero ones, where the closed-form solutions are available. Furthermore, algorithms for nonlinear Caputo equation are also presented, aiming at finding numerical solutions to all kinds of Caputo equations. Error analysis for the proposed algorithms is provided, and numerical examples are presented to illustrate the accuracy and effectiveness of the algorithms. [ABSTRACT FROM AUTHOR]

In this paper, we present an algorithm for identifying two-dimensional (2D) causal, recursive and separable-in-denominator (CRSD) state-space models in the Roesser form with deterministic–stochastic inputs. The algorithm implements the N4SID, PO-MOESP and CCA methods, which are well known in the literature on 1D system identification, but here we do so for the 2D CRSD Roesser model. The algorithm solves the 2D system identification problem by maintaining the constraint structure imposed by the problem (i.e. Toeplitz and Hankel) and computes the horizontal and vertical system orders, system parameter matrices and covariance matrices of a 2D CRSD Roesser model. From a computational point of view, the algorithm has been presented in a unified framework, where the user can select which of the three methods to use. Furthermore, the identification task is divided into three main parts: (1) computing the deterministic horizontal model parameters, (2) computing the deterministic vertical model parameters and (3) computing the stochastic components. Specific attention has been paid to the computation of a stabilised Kalman gain matrix and a positive real solution when required. The efficiency and robustness of the unified algorithm have been demonstrated via a thorough simulation example. [ABSTRACT FROM AUTHOR]

This paper presents a composite control strategy integrating adaptive sliding-mode control and the linear quadratic regulator (LQR) technology for a wheeled inverted pendulum (WIP) vehicle system. The system can be partitioned into an actuated rotational subsystem and an underactuated longitudinal subsystem based on the different control input in the mathematical model. In particular, the instability analysis of zero dynamic for the underactuated longitudinal subsystem is investigated in detail using the feedback linearisation technology. Then, an adaptive sliding-mode control is designed for the trajectory tracking, where an adaptive algorithm is developed to handle with the parameter uncertainties. In addition, the LQR technique is employed to guarantee zero dynamics stability so as to achieve simultaneously the vehicle body stabilisation at the upright position. Simulation results show the good performance and strong robustness of the proposed control schemes. [ABSTRACT FROM AUTHOR]

For an uncontrollable system, adding leaders and adjusting edge weights are two methods to improve controllability. In this paper, the controllability of multi-agent systems under directed topologies is studied, especially on the leader selection problem and the weight adjustment problem. For a multi-agent system, necessary and sufficient algebraic conditions for controllability with fewest leaders are proposed. To improve controllability by adjusting edge weights, the system is supposed to be structurally controllable, which holds if and only if the communication topology contains a spanning tree. It is also proved that the number of the fewest edges needed to be assigned on new weights equals the rank deficiency of controllability matrix. In addition, a leader selection algorithm and a weight adjustment algorithm are presented. Simulation examples are provided to illustrate the theoretical results. [ABSTRACT FROM AUTHOR]

In this paper, an energy-based control methodology is proposed to satisfy the Reynolds three rules in a flock of multiple agents. First, a control law is provided that is directly derived from the passivity theorem. In the next step, the Number of Neighbours Alignment/Repulsion algorithm is introduced for a flock of agents which loses the cohesion ability and uniformly joint connectivity condition. With this method, each agent tries to follow the agents which escape its neighbourhood by considering the velocity of escape time and number of neighbours. It is mathematically proved that the motion of multiple agents converges to a rigid and uncrowded flock if the group is jointly connected just for an instant. Moreover, the conditions for collision avoidance are guaranteed during the entire process. Finally, simulation results are presented to show the effectiveness of the proposed methodology. [ABSTRACT FROM AUTHOR]

We focus on the control and the synthesis of secure timed systems which are modelled as timed automata. The security property that the system must satisfy is anon-interferenceproperty. Intuitively, non-interference ensures the absence of any causal dependency from a high-level domain to a lower level domain. Various notions of non-interference have been defined in the literature, and in this paper, we focus onstrong non-deterministic non-interference(SNNI) and two (bi)simulation-based variants thereof (cosimulation-based SNNI and bisimulation-based SNNI). These properties and their extensions have been mostly studied in the context of discrete event systems, while it is now well-known that time is an important attack vector against secure systems. At the same time, there is an obvious interest in going beyond simple verification to control problems: to be able to automatically make systems secure. We consider non-interference properties in the challenging setting of control of dense-time systems specified bytimed automataand we study the two following problems: (1) check whether it is possible to find a sub-system so that it is non-interferent; if yes, (2) compute a (largest) sub-system which is non-interferent. We exhibit decidable sub-classes for these problems, assess their theoretical complexities and provide effective algorithms based on the classical framework of timed games. [ABSTRACT FROM AUTHOR]

In this paper, a hierarchical PO-MOESP subspace identification algorithm for directed acyclic graphs (DAGs) is presented. The state of every node and the structure of the graph are assumed to be unknown. The method computes a hierarchical partition of the DAG by using projection matrices typically used in subspace identification methods applied in cascade. Then, the column space of the observability matrix of every node is sequentially estimated by projecting away the input-output data from the previous levels. A past input–output instrumental variable approach is adopted to deal with the noise. The topology of multilevel DAGs is revealed by dedicated projections applied on every level. Moreover, we provide a brief study of a more general class of DAGs that can be accurately represented by multilevel DAGs of reduced interconnection structure. Finally, three simulation examples are provided to show the effectiveness of the proposed methodology. [ABSTRACT FROM AUTHOR]