On a motion control problem for an object in a conflict environment

The evasion problem of a mobile object from detection by a stationary observer in a passive mode is solved. For the case of power dependence of the level of the radiated signal on the motion velocity, a control law for velocity and the trajectory of the object that provide a minimum to the integral level of the signal coming to the observer input for the time of object motion are found in an explicit form.     

On statistical risk functional in a control problem for an object moving in a conflict environment

A statistical criterion is suggested for a variational problem on constructing an optimal trajectory of evasion of a movable object from detection by a stationary observer. Coordinates of the observer are assumed to be not known exactly but are distributed in the space in accordance with some a priori known probability distribution. The risk functional for the variational problem is taken to be expectation of an integral loss functional (depending on a random parameter) in the deterministic problem, which is calculated in this work.     

Vectorization path planning for autonomous mobile agent in unknown environment

This paper presents a novel real-time path planning algorithm, called InsertBug, for an autonomous mobile agent in completely unknown environment. By using the algorithm, all the planned paths are described and stored by vectors. The algorithm combines range sensor data with safety radius to determine the blocking obstacles and calculate the shortest path by choosing the intermediate points. When there is obstacle blocking the current path, the intermediate points will be calculated, and the planned path will be regenerated by inserting the intermediate points. The local optimum avoidance strategy is also considered in this algorithm by specifying a fixed direction. The agent will return to the optimal direction after running out of the local optimum. Different simulation parameters are taken to show the advantages of this algorithm. Moreover, the performance of this algorithm has also been evaluated by comparing with another usual method via simulations. The results show that the safety performance and time requirements of this algorithm are significant superior to the algorithm contrasted with.     

WSNs中移动物体监测的覆盖控制技术研究

针对物体监测时可能存在节点能耗不均和漏检问题,提出一种基于模糊移动轨迹的移动物体监测控制策略.监测点根据邻居节点信息和移动物体轨迹分析机制与节点回退机制,通过有效的优先级划分策略,在节点资源受限的情况下,保证了较高的节点利用率和监测点的覆盖度.仿真结果表明:该策略与PEAS算法相比,有效改善了节点能耗不均的问题,减小无线传感器网络(WSNs)的监测失真度.     

Evasion on plane from a single mobile observer in the conflict environment

Consideration was given to the problem of evasion of a mobile object from the moving observer in a conflict environment. A law of control of the mobile object speed was established. The optimal motion trajectory was constructed, and the time dependence of the accumulated signal was compared for other laws of control.     

Dynamic path planning for a mobile automaton with limited information on the environment

The problem of path planning is studied for the case of a mobile robot moving in an environment filled with obstacles whose shape and positions are not known. Under the accepted model, the automaton knows its own and the target coordinates, and has a "sensory" feedback which provides it with local information on its immediate surroundings. Ibis information is shown to be sufficient to guarantee reaching a global objective (the target), while generating reasonable (if not optimal) paths. A lower bound on the length of paths generated by any algorithm operating with uncertainty is formulated, and two nonheuristic path planning algorithms are described. In the algorithms, motion planning is done continuously (dynamically), based on the automaton's current position and on its feedback. The effect of additional sources of information (e.g., from a vision sensor) on the outlined approach is discussed.     

On the existence of optimal strategies in the control problem for a stochastic discrete time system with respect to the probability criterion

We study a control problem for a stochastic system with discrete time. The optimality criterion is the probability of the event that the terminal state function does not exceed a given limit. To solve the problem, we use dynamic programming. The loss function is assumed to be lower semicontinuous with respect to the terminal state vector, and the transition function from the current state to the next is assumed to be continuous with respect to all its arguments. We establish that the dynamic programming algorithm lets one in this case find optimal positional control strategies that turn out to be measurable. As an example we consider a two-step problem of security portfolio construction. We establish that in this special case the future loss function on the second step turns out to be continuous everywhere except one point.     

Fuzzy Dijkstra algorithm for shortest path problem under uncertain environment

A common algorithm to solve the shortest path problem (SPP) is the Dijkstra algorithm. In this paper, a generalized Dijkstra algorithm is proposed to handle SPP in an uncertain environment. Two key issues need to be addressed in SPP with fuzzy parameters. One is how to determine the addition of two edges. The other is how to compare the distance between two different paths with their edge lengths represented by fuzzy numbers. To solve these problems, the graded mean integration representation of fuzzy numbers is adopted to improve the classical Dijkstra algorithm. A numerical example of a transportation network is used to illustrate the efficiency of the proposed method.     

Dual criterion stochastic optimal control problem for robustness improvement

The solution of the dual criterion linear quadratic stochastic optimal control problem is obtained by following a Wiener type of solution procedure. A stabilizing solution is guaranteed by parameterizing the controller using the Desoer fractional representation approach. The dual criterion includes sensitivity and complementary sensitivity weighting terms which provide a means of varying the robustness characteristics of the multivariable system.     

Method for lexicographic suboptimal control of the evader in a conflict problem

An approach is considered that allows generating a suboptimal strategy for the evader in a nonlinear feedback position control problem that can be implemented in real time. The evader does not know exactly what actions the pursuer will take up, and the evader’s strategy is selected from the known functionality of both players and worse possible actions of the pursuer. __________ Translated from Kibernetika i Sistemnyi Analiz, No. 3, pp. 156–167, May–June 2006.     

Visual search for an object in a 3D environment using a mobile robot

Consider the problem of visually finding an object in a mostly unknown space with a mobile robot. It is clear that all possible views and images cannot be examined in a practical system. Visual attention is a complex phenomenon; we view it as a mechanism that optimizes the search processes inherent in vision (Tsotsos, 2001; Tsotsos et al., 2008) [1], [2]. Here, we describe a particular example of a practical robotic vision system that employs some of these attentive processes. We cast this as an optimization problem, i.e., optimizing the probability of finding the target given a fixed cost limit in terms of total number of robotic actions required to find the visual target. Due to the inherent intractability of this problem, we present an approximate solution and investigate its performance and properties. We conclude that our approach is sufficient to solve this problem and has additional desirable empirical characteristics.     

An efficient suboptimal algorithm for player-ally control in a conflict problem

An approach is considered that allows one to generate a suboptimal strategy for the player-ally in a nonlinear problem of positional feedback control, which can be implemented in the real-time control of plants. Here, the player-ally has no exact information about the future action of the opponent, and the strategy of this player is chosen from the condition of opponent’s “worst” actions and the physical capabilities of both players     

Bounded controllers for global path tracking control of unicycle-type mobile robots

This paper presents a design of bounded controllers with a predetermined bound for global path tracking control of unicycle-type mobile robots at the torque level. A new one-step ahead backstepping method is first introduced. The heading angle and linear velocity of the robots are then considered as immediate controls to force the position of the robots to globally and asymptotically track its reference path. These immediate controls are designed based on the one-step ahead backstepping method to yield bounded control laws. Next, the one-step ahead backstepping method is applied again to design bounded control torques of the robots with a pre-specified bound. The proposed control design ensures global asymptotical and local exponential convergence of the position and orientation tracking errors to zero, and bounded torques driving the robots. Experimental results on a Khepera mobile robot verify the proposed control controller.     

Dyna-Q-based vector direction for path planning problem of autonomous mobile robots in unknown environments

Reinforcement learning (RL) is a popular method for solving the path planning problem of autonomous mobile robots in unknown environments. However, the primary difficulty faced by learning robots using the RL method is that they learn too slowly in obstacle-dense environments. To more efficiently solve the path planning problem of autonomous mobile robots in such environments, this paper presents a novel approach in which the robot’s learning process is divided into two phases. The first one is to accelerate the learning process for obtaining an optimal policy by developing the well-known Dyna-Q algorithm that trains the robot in learning actions for avoiding obstacles when following the vector direction. In this phase, the robot’s position is represented as a uniform grid. At each time step, the robot performs an action to move to one of its eight adjacent cells, so the path obtained from the optimal policy may be longer than the true shortest path. The second one is to train the robot in learning a collision-free smooth path for decreasing the number of the heading changes of the robot. The simulation results show that the proposed approach is efficient for the path planning problem of autonomous mobile robots in unknown environments with dense obstacles.     

Source detection problem with discrete-time variable radiation intensities: Joint control optimization for the path and observations of a mobile observer

This paper demonstrates the specifics of the implementation of a control optimization procedure for the path and observations of a mobile observer detecting a system of sources with discretetime variable radiation intensities. We define the sequence of the calculation of the probabilistic characteristics of the radiation intensity variations in the control design algorithm. An illustrative example is given.     

On the problem of break-through between two sensors for a craft moving in the conflict environment

Planning of the path of a craft moving between two sensors was considered with the aim of minimizing the total signal arriving to the sensors in the passive mode.     

One-parameter optimal correction problem for the trajectory of an aerial vehicle with respect to the probability criterion

The correction problem of an aerial vehicle trajectory is considered. The mathematical model of the correction process is represented by a scalar stochastic control system with a probability terminal performance index. The system’s state variable is the predicted miss of a single parameter of the aerial vehicle. It is assumed that the complete information about the state variable is available. The aim of the correction is to maximize the probability that the terminal miss does not exceed the prescribed level. The execution errors of the designed correction impulse are distributed uniformly. Using dynamic programming, a procedure for the optimization of corrections of the aerial vehicle trajectory with respect to the probability performance index is developed, and this procedure is used to solve the one-parameter optimal correction problem for the aerial vehicle for the case of N time steps. The resulting optimal control is compared to the known optimal controls with respect to other performance indices.     

Pirax: framework for application piracy control in mobile cloud environment

Mobile cloud computing is an emerging technology that is gaining popularity as a means to extend the capabilities of resource-constrained mobile devices such as a smartphone. Mobile cloud computing requires specialized application development models that support computation offloading from a mobile device to the cloud. The computation offloading is performed by means of offloading application process, application component, entire application, or clone of the smartphone. The offloading of an entire application or clone of the smartphone to cloud may raise application piracy issues, which, unfortunately, have not been addressed in the existing literature. This paper presents a piracy control framework for mobile cloud environment, named Pirax, which prevents mobile applications from executing on unauthenticated devices and cloud resources. Pirax is formally verified using High Level Petri Nets, Satisfiability Modulo Theories Library and Z3 solver. Pirax is implemented on Android platform and analyzed from security and performance perspectives. The performance analysis results show that Pirax is lightweight and easy to integrate into existing mobile cloud application development models.     

基于降精度求解准则的快速最优控制问题求解算法

动态优化策略广泛应用于很多领域,包括基于微分方程模型的最优控制问题求解等等. 这类问题在离散后,得到大规模、复杂的非线性优化问题.现在的优化方法采用传统收敛准则,往往收敛速度缓慢甚至最终收敛失败,无法及时得到可靠的数值解.本文针对联立法离散后的问题,采用一种基于降精度求解准则(reduced precision solution criterion,RPSC)的序列2次规划方法(sequcntial quadratic programming,SQP)进行求解.RPSC定义了一系列指标,用于判断继续迭代是否能够有效改善解值,是否可以终止求解进程.仿真实验结果表明,该收敛准则与传统收敛准则相比,能够及时终止求解过程,同时返回较好的数值解.此外,收敛阈值可以根据用户的实际需要设定,在得到满足要求的估计值时及时终止求解进程.     

An optimality criterion in a control problem for a Sobolev-type linear equation

The necessary and sufficient conditions for solving an optimal control problem with a quadratic cost function for a system, whose state is described by a linear confluent equation in Hilbert spaces are obtained. We apply these results for investigating an optimal control problem for the Dzektser equation of the evolution of the free surface of a filtering fluid.