基于能效优化的仿人机器人跑步步态优化与控制

针对高能耗导致的仿人机器人难以大规模实用化的问题,提出了一种新的仿人机器人参数化跑步步态优化方法。分析了不同跑步步态参数对仿人机器人水平、垂直方向的稳定性及能耗的影响,将机器人步态优化问题转化为对步态参数的多目标寻优问题,根据连杆模型得到机器人跑步过程中水平、垂直方向的稳定裕度及能耗表达式,并构造目标函数,采用基于对位学习的遗传算法对机器人参数化跑步步态进行多目标寻优,在保证机器人俯仰、翻滚和偏摆各方向力矩平衡的前提下降低整体能量消耗;针对传统遗传算法早熟及收敛速度慢的问题,提出基于领域知识的精细化初始成员策略,采取生成种群成员对位点的方式更新种群,以加快收敛速度;为提高轨迹跟踪性能,设计了自适应控制器,并给出了稳定性证明。仿真实验表明:该方法能有效降低能耗并保证其稳定性。     

Adaptive neural control for an uncertain robotic manipulator with joint space constraints

In this paper, adaptive neural tracking control is proposed for a robotic manipulator with uncertainties in both manipulator dynamics and joint actuator dynamics. The manipulator joints are subject to inequality constraints, i.e., the joint angles are required to remain in some compact sets. Integral barrier Lyapunov functionals (iBLFs) are employed to address the joint space constraints directly without performing an additional mapping to the error space. Neural networks (NNs) are utilised to compensate for the unknown robot dynamics and external force. Adapting parameters are developed to estimate the unknown bounds on NN approximations. By the Lyapunov synthesis, the proposed control can guarantee the semi-global uniform ultimate boundedness of the closed-loop system, and the practical tracking of joint reference trajectory is achieved without the violation of predefined joint space constraints. Simulation results are given to validate the effectiveness of the proposed control scheme.     

Output feedback robust MPC for LPV system with polytopic model parametric uncertainty and bounded disturbance

The output feedback robust model predictive control (MPC), for the linear parameter varying (LPV) system with norm-bounded disturbance, is addressed, where the model parametric matrices are only known to be bounded within a polytope. The previous techniques of norm-bounding technique, quadratic boundedness (QB), dynamic output feedback, and ellipsoid (true-state bound; TSB) refreshment formula for guaranteeing recursive feasibility, are fused into the newly proposed approaches. In the notion of QB, the full Lyapunov matrix is applied for the first time in this context. The single-step dynamic output feedback robust MPC, where the infinite-horizon control moves are parameterised as a dynamic output feedback law, is the main topic of this paper, while the multi-step method is also suggested. In order to strictly guarantee the physical constraints, the outer bound of the true state replaces the true state itself, so tightness of this bound has a major effect on the control performance. In order to tighten the TSB, a procedure for refreshing the real-time ellipsoid based on that of the last sampling instant is given. This paper is conclusive for the past results and far-reaching for the future researches. Two benchmark examples are given to show the effectiveness of the novel results.     

基于自适应动态规划的矿渣微粉生产过程跟踪控制

矿渣微粉是一种新型绿色环保型建材,可以大大提高水泥混凝土的力学性能.本文以矿渣微粉生产过程为研究对象,针对该过程难以通过机理建模进行辨识和控制的特点,利用数据驱动的思想,建立矿渣微粉生产过程的递归神经网络模型.在此基础上,利用自适应动态规划,设计具有控制约束的跟踪控制器,并将其应用到矿渣微粉生产过程中.仿真分析表明,建立的数据驱动模型能够有效地辨识矿渣微粉生产过程,同时,本文提出的控制方法能够实现输入受限的微粉比表面积及磨内压差的最优跟踪控制.     

A simple robust control for global asymptotic position stabilization of underactuated surface vessels

Global asymptotic stabilization of underactuated surface vessels is generally achieved only by designing complicated controllers. This paper proposes a very simple control law that globally asymptotically stabilizes the position of underactuated surface vessel to a desired constant location and its velocities to zero. The proposed controller is independent of velocity signals and is robust to model parameters. It neither includes an observer nor an adaptive/sliding‐mode law. Controller development and stability analysis rely on a novel Lyapunov function and LaSalle's theorem. Furthermore, by extending the proposed control strategy, a saturated control law is also obtained ensuring the semiglobal asymptotic stability of position error system. Effectiveness of the proposed control schemes is demonstrated by simulation examples. Copyright © 2017 John Wiley & Sons, Ltd.     

Evidential grammars: A compositional approach for scene understanding. Application to multimodal street data

Automatic scene understanding from multimodal data is a key task in the design of fully autonomous vehicles. The theory of belief functions has proved effective for fusing information from several sensors at the superpixel level. Here, we propose a novel framework, called evidential grammars, which extends stochastic grammars by replacing probabilities by belief functions. This framework allows us to fuse local information with prior and contextual information, also modeled as belief functions. The use of belief functions in a compositional model is shown to allow for better representation of the uncertainty on the priors and for greater flexibility of the model. The relevance of our approach is demonstrated on multi-modal traffic scene data from the KITTI benchmark suite.     

基于OFDM的水声通信算法

在水声通信领域,基于正交频分复用（Orthogonal Frequency Division Multiplexing,OFDM）的通信技术是最直接和最有效的手段之一. 但是水声通信信道是多变的和复杂的,在传输的过程中可能会受到多途扩展严重、可用带宽有限和高噪声等不理想因素的影响,导致无法恢复出原始数据,所以保证数据的可靠性传输是极其重要的. 本文在原有的OFDM通信基础上加入了交织技术、chirp扩频技术、加窗以及chirp同步技术,并通过对MATLAB的仿真和实验分析,验证了该系统的可行性,最后通过对比加入噪声、多径和多普勒效应的误码率曲线图,说明了该系统的性能和抗干扰能力.     

Distributed adaptive control for vehicular platoon with unknown dead‐zone inputs and velocity/acceleration disturbances

This paper is focused on designing a distributed adaptive control scheme for a vehicular platoon with unknown bounded velocity/acceleration disturbances and unknown nonlinear dead‐zone inputs. Our aim is to design distributed adaptive controllers based on integral sliding mode control techniques that guarantee practical exponential convergence (i.e., exponential stability of an arbitrarily small neighborhood of zero) of the spacing errors and the string stability of the whole vehicular platoon. The contributions of this paper are that: (i) based on a modified constant time headway policy, the whole vehicular platoon is guaranteed to have string stability despite dead zone inputs; (ii) adaptive compensation terms are constructed to compensate for the time‐variant effects caused by unknown bounded velocity/acceleration disturbances, and unknown dead zone inputs; (iii) an efficient numerical method for avoiding the singularity problem of the control law is also proposed. Numerical simulation results show the validity and advantages of the proposed method are significantly higher traffic density and string stability. Copyright © 2016 John Wiley & Sons, Ltd.     

基于J1939的车辆下线检测系统的数据库设计

SAE J1939协议是重型车辆广泛采用的一种车载网络规范,它详细定义了大量的参数,通过对车上协议数据报文的分析就可以获取车辆重要电控单元的各项状态信息.针对整车厂车辆下线检测的需求,在J1939协议应用层的功能基础上,经过需求分析并使用PowerDesigner建模工具对J1939的参数数据库进行建模,建立具体数据库管理系统的物理数据库,并在此基础上利用CodeSmith代码生成工具以及.Nettiers模板来生成该数据库应用系统中数据访问层的.NET代码框架,实现车辆下线检测系统中对J1939协议参数的支持,最终完成设计.     

Attainability of the minimum data rate for stabilization of linear systems via logarithmic quantization

This paper investigates the attainability of the minimum average data rate for stabilization of linear systems via logarithmic quantization. It is shown that a finite-level logarithmic quantizer suffices to approach the well-known minimum average data rate for stabilizing an unstable linear discrete-time system under two basic network configurations. In particular, we derive explicit finite-level logarithmic quantizers and the corresponding controllers to approach the minimum average data rate.