A solution to the path planning problem via algebraic geometry and reinforcement learning

In this paper, the path planning problem for an unicycle-like mobile robot is considered. By using some results borrowed from algebraic geometry, a technique is given to determine a dynamical system that is affine in the input and whose trajectories tend to a chosen algebraic set independently of the control input. Since this does not guarantee that the corresponding paths of motion are collision free, an optimal control problem is formulated to enforce this behavior, and its approximate solution is determined via integral reinforcement learning. Finally, it is shown how such results can be used to derive a feedback control law for unicycle-like mobile robots.     

Cascade design for formation control of nonholonomic systems in chained form

This paper presents a constructive method to design a cooperative state and output feedback to steer a group of nonholonomic mobile robots in chained form to form a desired geometric formation shape. The control methodology divides the resulting tracking error dynamics into a cascaded of linear and time-varying subsystems. A basic consensus algorithm is first applied to the linear subsystem which makes the states synchronize exponentially to zero. Once this first linear subsystem has converged, the second cascade can be treated as a linear time-varying subsystem perturbed by a vanishing term from its cascade. A dynamic state and output feedback is constructed to achieve synchronization of the rest of the states. The proof of stability is given using a result from cascade systems. Since time delay appears in many interconnection networks and particularly in cooperative control, its effect on the stability of the closed-loop system is analyzed using Razumikhim theorem. It is shown that the established cooperative controller work well even in the presence of time delay. Numerical simulations are performed on models of car-like mobile robots to show the effectiveness of the proposed cooperative state and output-feedback controllers.     

Leader-following consensus control of multiple nonholomomic mobile robots: An iterative learning adaptive control scheme

In this paper, the distributed iterative learning control for nonholonomic mobile robots with a time-varying reference is investigated, in which the mobile robots are with parametric uncertainties and are not fully actuated. Besides, the control gains of mobile robots are unknown. The leader is with a time-varying reference trajectory, and there is no need to assume that the time-varying reference is linearly parameterized by a set of known functions. A distributed control scheme is designed for each mobile robot based on a set of local compensatory filters designed by its neighborhood information. Stability analysis is established through a set of composite energy function. The uniform convergence of the consensus errors can be guaranteed. An example is given to show that our designed control law is effective.     

Impulsive control for passivity and exponential synchronization of coupled neural networks with multiple weights

This paper investigates the passivity and synchronization problems for two classes of multiple weighted coupled neural networks (MWCNNs) with or without time delays. Firstly, by utilizing an impulsive control strategy and some inequality techniques, several passivity criteria for MWCNNs with diverse dimensions of output and input are established. Then, based on the Lyapunov functional, some sufficient conditions to ensure the synchronization of MWCNNs via impulsive control are derived. In addition, combined with the comparison principle and the impulsive delay differential inequality, the global exponential synchronization of MWCNNs with time-varying delays is considered under impulsive control. Finally, two numerical examples illustrate the effectiveness of the obtained results.     

Robust cooperative control for a group of mobile robots with quantized information exchange

In this paper we investigate the cooperative tracking control problem with quantized time delay information exchange for a group of wheeled mobile robots networked through a connected graph modeling the underlying communication topology. A cooperative controller is proposed using a combination of backstepping technique, graph theory and neural network radial basis functions. We show, using the small gain theorem, that the states of each mobile robot in the group converge to and remain inside a tube centered around its assigned trajectory to form a desired geometric pattern whose centroid is assumed to move along a predefined trajectory. Experimental results on a group of three mobile robots forming a triangular shape are presented to demonstrate the good performance of the proposed cooperative controller.     

Frequency synchronization adaptive control for power grids under topological uncertainty

In this paper, an adaptive control strategy is proposed to address the synchronization issue for weakly damped generators under topological uncertainty. A singular perturbation analysis is then adopted for strongly damped generators and a compensation control scheme is subsequently given to maintain synchronization under topological changes. Theoretical proof is laid out for the validity of the proposed control scheme. Besides, a power sharing strategy is supplemented for strongly damped generators based on the designed controller. Finally, simulation studies are carried out to verify the effectiveness of the control strategies. Results show that synchronization can be swiftly restored even when the power grid suffers a fatal topological change. The power sharing property can be achieved under the given restriction with the proposed controller.     

基于模拟退火算法的机器人路径规划与研究

机器人技术作为20世纪自动控制领域的一项伟大成就已经取得了长足的发展,移动机器人也越来越多地应用到了各个行业中。移动机器人具有高度自规划、自组织和自适应能力,适合工作于复杂的非结构化环境中。本文以自主移动机器人为背景,着重对其关键的路径规划技术进行研究和探讨。     

Continuous fixed-time synchronization control for uncertain industrial master-slave robotics system with improved transparency

Industrial telerobotics system (ITS) enables robots to implement remote, dangerous, and complicated manufacturing tasks by incorporating human intelligence. Higher requirements are put forward for the working speed and performance of ITS. However, for ITS, only asymptotic convergence can be realized by existing control strategies, which have poor robust performance. In view of these theoretical and practical problems, this article addresses fixed-time synchronization control issue for a class of ITS with unknown parametric/nonparametric uncertainties and external disturbances. Satisfactory force and position performance can be achieved with the designed novel control algorithms. Firstly, based on the impedance control frame, two reference models are constructed for the master and slave robots by considering force and position signals transmission between master and slave, respectively. Then, a new adaptive sliding mode disturbance observer (ASMDO) is developed to realize the estimation of external disturbances and system uncertainties in higher speed and higher precision under relaxed assumption. Moreover, a novel continuous fixed-time control (CFTC) scheme is developed to guarantee good position and force synchronization performances, simultaneously. Finally, the effectiveness of the suggested control method is validated with simulations and experimental results.     

A new on-line observer-based controller for leader-follower formation of multiple nonholonomic mobile robots

In this paper, a novel on-line observer-based trajectory tracking strategy for leader-follower formation of multiple nonholonomic mobile robots is developed. In the proposed strategy, a leader robot follows a certain trajectory whereas a number of followers track the leader as specified by a formation protocol. Unlike other techniques in the literature, a predefined trajectory is not required, and it can be changed on-line. Moreover, this strategy aims to have a fast transient response without showing undesired overshoots. To achieve this feature, a new observer is introduced. Based on the output of that observer, a control strategy with two components is derived. The first control component is responsible for tracking the desired trajectory, whereas the second control component is used to regulate the robot to its desired steady state position. The stability of the closed loop control system is investigated. Applications of the proposed observer-based controller to different case studies are presented to illustrate the effectiveness, robustness and applicability of the developed technique. To show the superiority of proposed controller, its performance in a trajectory tracking application is compared to that of a Lyapunov-based controller.     

Static group synchronization of second-order multi-agent systems via pinning control

This paper investigates the expected static group synchronization problem of the second-order multi-agent systems via pinning control. For directed communication topology with spanning tree, based on Gershgorin disk theorem and the matrix property, a static pinning control protocol with fixed gains is first introduced and some sufficient and necessary static group synchronization criteria are also established. It is worth mentioning that a rigorous proof is also given that only one pinning node is needed to guarantee static group synchronization, which could be inferred that our protocol might be more economical and effective in large scale of multi-agent systems. Then, for weakly connected directed communication topology with nodes of zero in-degree, an adaptive pinning control applied to the node with zero in-degree is also proposed to achieve static group synchronization. Finally, the efficiency of the proposed protocols is verified by two simulation examples.     

Command filtered adaptive neural network synchronization control of fractional-order chaotic systems subject to unknown dead zones

Command filters are essential for alleviating the inherent computational complexity (ICC) of the standard backstepping control method. This paper addresses the synchronization control scheme for an uncertain fractional-order chaotic system (FOCS) subject to unknown dead zone input (DZI) based on a fractional-order command filter (FCF). A virtual control function (VCF) and its fractional-order derivative are approximated by the output of the FCF. In order to handle filtering errors and obtain good control performance, an error compensation mechanism (ECM) is developed. A radial basis function neural network (RBFNN) is introduced to relax the requirement of the uncertain function must be linear in the standard backstepping control method. The construction of a VCF in each step satisfies the Lyapunov function to ensure the stability of the corresponding subsystem. By using the bounded information to cope with the unknown DZI, the stability of the synchronization error system is guaranteed. Finally, simulation results verify the effectiveness of our methods.     

Consensus tracking control for nonlinear multiagent systems with asymmetric state constraints and input delays

In this paper, the consensus tracking problem is studied for a group of nonlinear heterogeneous multiagent systems with asymmetric state constraints and input delays. Different from the existing works, both input delays and asymmetric state constraints are assumed to be nonuniform and time-varying. By introducing a nonlinear mapping to handle the problem caused by state constraints, not only the feasibility condition is removed, but also the restriction on the constraint boundary functions is relaxed. The time-varying input delays are compensated by developing an auxiliary system. Furthermore, by utilizing the dynamic surface control method, neural network technology and the designed finite-time observer, the distributed adaptive control scheme is developed, which can achieve the synchronization between the followers’ output and the leader without the violation of full-state constraints. Finally, a numerical simulation is provided to verify the effectiveness of the proposed control protocol.     

Synchronization for chaotic systems via mixed-objective dynamic output feedback robust model predictive control

This paper focuses on mixed-objective dynamic output feedback robust model predictive control (OFRMPC) for the synchronization of two identical discrete-time chaotic systems with polytopic uncertainties, energy bounded disturbances, and input constraint. Using active control strategy, the chaos synchronization is transformed into standard dynamic OFRMPC scenarios tractable through receding horizon min–max optimization. Utilizing the notion of quadratic boundedness, the augmented closed-loop stability is further characterized. Then, the concepts of mixed performance criteria are firstly incorporated into the dynamic OFRMPC scheme to guarantee both the robust stability and the disturbance attenuation ability while preserving better dynamical behaviors. Necessary and/or sufficient conditions for desired mixed-objective dynamic OFRMPC are formulated involving linear matrix inequalities (LMIs). Finally, two numerical examples are given to demonstrate the theoretical results.     

On the moral responsibility of military robots

This article discusses mechanisms and principles for assignment of moral responsibility to intelligent robots, with special focus on military robots. We introduce the concept autonomous power as a new concept, and use it to identify the type of robots that call for moral considerations. It is furthermore argued that autonomous power, and in particular the ability to learn, is decisive for assignment of moral responsibility to robots. As technological development will lead to robots with increasing autonomous power, we should be prepared for a future when people blame robots for their actions. It is important to, already today, investigate the mechanisms that control human behavior in this respect. The results may be used when designing future military robots, to control unwanted tendencies to assign responsibility to the robots. Independent of the responsibility issue, the moral quality of robots’ behavior should be seen as one of many performance measures by which we evaluate robots. How to design ethics based control systems should be carefully investigated already now. From a consequentialist view, it would indeed be highly immoral to develop robots capable of performing acts involving life and death, without including some kind of moral framework.     

Adaptive synchronization for a class of faulty and sampling coupled networks with its circuit implement

This paper is concerned with the asymptotic synchronization problem of a class of nonlinear complex networks with faulty and sampling couplings. A new version of the adaptive control strategy is proposed to adjust control parameters to compensate for the adverse impact of network attenuation faults, nonlinearities and sampling errors. Based on the adaptive adjustment laws, an approach that is application of knowledge of electricity is introduced to physically realize the adaptive controllers. Using Lyapunov stability theory for the synchronization error system, asymptotic synchronization of the overall networks can be established for the nonlinearly sampling and faulty couplings. Finally, the proposed adaptive control schemes are tested by simulation on Chua?s circuit network.     

Dynamic path planning of mobile robot based on improved simulated annealing algorithm

Dynamic path planning for mobile robots is an urgent issue that needs to be solved because of the growing use of mobile robots in daily life and industrial operations. This work focuses on avoiding moving obstacles in dynamic situations. The computational effort required by some current algorithms makes them difficult to utilize for path planning in dynamic situations whilst the computational effort required by other methods makes them simple yet prone to local minima. In this paper, an improved simulated annealing (SA) algorithm for dynamic path planning is proposed. To reduce its computational effort, the initial path selection method and deletion operation are introduced. Simulation results show the improved SA algorithm outperforms other algorithms and provides optimal solutions in static and dynamic environments.     

Coordination of nonholonomic mobile robots for diffusive threat defense

This paper studies coordination of a team of nonholonomic mobile robots with smart actuators for defending against invasive threat to a planar convex area. The threat refers to a kind of harmful substance such as chemical pollutant appearing outside and moving towards the area. The invasion of threat can be modeled by a 2D unsteady reaction-diffusion process. To reflect the adverse effect of threat on the area, a so-called risk intensity field is introduced. The value of risk intensity is equal to the concentration of threat measured by a static mesh sensor network. Based on this risk intensity field, a coordination control scenario using Voronoi tessellation is formulated. In order to minimize the actuator performance loss and reduce the total average risk intensity simultaneously, a generalized centroidal Voronoi tessellation (CVT) algorithm including optimal motion control and risk mitigation control is designed. The proposed algorithm is gradient-based and guides mobile robots to track their optimal trajectories asymptotically. Meanwhile, two conditions of choosing control gains are derived to keep the total average risk intensity below a safety level. Several simulation examples with different cases of threat invasion are provided and the advantage of proposed algorithm over traditional control method is presented.     

Finite-time and fixed-time synchronization of discontinuous complex networks: A unified control framework design

This paper is concerned with the finite-time and fixed-time synchronization of complex networks with discontinuous nodes dynamics. Firstly, under the framework of Filippov solution, a new theorem of finite-time and fixed-time stability is established for nonlinear systems with discontinuous right-hand sides by using mainly reduction to absurdity. Furthermore, for a class of discontinuous complex networks, a general control law is firstly designed. Under the unified control framework and the same conditions, the considered networks are ensured to achieve finite-time or fixed-time synchronization by only adjusting the value of a key control parameter. Based on the similar discussion, a unified control strategy is also provided to realize respectively asymptotical, exponential and finite-time synchronization of the addressed networks. Finally, the derived theoretical results are supported by an example with numerical simulations.