Switched model predictive control for performance enhancement

This article presents a switched model predictive control (MPC) algorithm for non-linear discrete time systems where the weights on the state and control variables in the cost function to be minimised depend on the current value of the state. In so doing, with a reduced computational burden one can easily include, in the problem formulation, a number of control specifications, such as the requirement to avoid critical regions in the state space or to reduce as much as possible the use of some actuators in other zones of the state space. The proposed MPC method has stability properties and is applied for control of a thermal system. The reported simulation results witness its favourable characteristics with respect to a standard MPC implementation.     

3D stable biped walking control and implementation on real robot

A combination of walking control methods was proposed and implemented on a biped robot. The LIPM-based model predictive control (MPC) was adopted to generate a basic stable walking pattern. The stability of pitch and yaw rotation was improved through pitch and yaw momentum control as a supplementation of MPC. It is found that biped robot walking tends to deviate from the planned walking direction if not considering the rotation friction torque in yaw axis under the support foot. There are basically two methods to control yaw momentum, waist and swing arms rotation control. However, the upper body is often needed to accomplish other tasks. Therefore, a yaw momentum control method based on swing leg dynamics was proposed. This idea does not depend on upper body’s motion and is highlighted in this paper. Through experiments, the feasibility of the combination of the control methods proved to be practical in keeping biped robot walking stable both in linear and rotation motion. The pros and cons of the yaw momentum control method were also tested and discussed through comparison experiments, such as walking on flat and uneven terrain, walking with different payloads.     

Robust Sliding-mode Control of Nine-link Biped Robot Walking

A nine-link planar biped robot model is considered which, in addition tothe main links (i.e., legs, thighs and trunk), includes a two-segment foot.First, a continuous walking pattern of the biped on a flat terrain issynthesized, and the corresponding desired trajectories of the robot jointsare calculated. Next, the kinematic and dynamic equations that describe itslocomotion during the various walking phases are briefly presented. Finally,a nonlinear robust control approach is followed, motivated by the fact thatthe control which has to guarantee the stability of the biped robot musttake into account its exact nonlinear dynamics. However, an accurate modelof the biped robot is not available in practice, due to the existence ofuncertainties of various kinds such as unmodeled dynamics and parameterinaccuracies. Therefore, under the assumption that the estimation error onthe unknown (probably time-varying) parameters is bounded by a givenfunction, a sliding-mode controller is applied, which provides a successfulway to preserve stability and achieve good performance, despite the presenceof strong modeling imprecisions or uncertainties. The paper includes a setof representative simulation results that demonstrate the very good behaviorof the sliding-mode robust biped controller.     

双足机器人稳定步行模式预测控制实现方法的研究

针对现有的预测控制生成步行模式方法中忽略了参数间关系和参数取值范围的问题进行探讨.预测控制通过控制质心运动生成步行模式以实现ZMP目标轨迹跟踪,根据预测控制器模型研究参数间的关系,并通过极点分析讨论其取值范围,提出关键参数在容许取值范围内,可以保证系统的稳定性,并生成满足稳定步行的质心运动.通过仿真实验分析了在存在扰动情况下,关键参数取适当值,能够生成稳定的步行模式.     

五杆四驱动平面双足机器人动态步态规划与非线性控制

以五杆四驱动的平面双足步行机器人为对象,研究了其动态步行的时不变步态规划和限定时间的非线性控制策略．揭示了其模型的欠驱动和完全驱动的混杂和非光滑动力学特性,推导了其碰撞模型．基于虚拟约束的概念,提出时不变步态的输出函数解析设计方法,设计了反馈线性化控制器,将系统转化为双积分环节．然后采用限定时间控制器在一步内零化输出函数．仿真实验表明,动态步行趋于一个稳定的极限环,实现了规划的行走模式,验证了该方法的有效性．     

一种双足机器人实时步态规划方法及相关数值算法

针对步行双足机器人实时步态规划问题,提出了一种改进的非线性模型预测控制（NMPC）方法．采用扩展的关节坐标,将单腿支撑相（SSP）和双腿支撑相（DSP）统一表示为一个非线性动力学模型．通过对SSP和DSP的3个阶段设定运动学和动力学虚拟约束,将复杂实时步态规划问题转化为4个以预测时域内控制量二次型为代价函数的NMPC问题．采用直接法将连续优化问题参数化为有限维优化问题,并采用惩罚函数法将状态变量约束转化为代价函数中的惩罚项,从而得到能够用渐进二次规划（SQP）求解的有限维静态优化问题．仿真结果表明,应用该方法对BIP机器人模型进行实时步态规划,实现了包含足部转动的动态步行,且机器人满足稳定性条件,不发生侧滑,从而证明了该方法的有效性和可实现性．     

A two-tier control architecture for nonlinear process systems with continuous/asynchronous feedback

In this work, we introduce a two-tier control architecture for nonlinear process systems with both continuous and asynchronous sensing and actuation. This class of systems arises naturally in the context of process control systems based on hybrid communication networks (i.e. point-to-point wired links integrated with networked wired or wireless communication) and utilising multiple heterogeneous measurements (e.g. temperature and concentration). Assuming that there exists a lower-tier control system which relies on point-to-point communication and continuous measurements to stabilise the closed-loop system, we propose to use Lyapunov-based model predictive control to design an upper-tier networked control system to profit from both the continuous and the asynchronous measurements as well as from additional networked control actuators. The proposed two-tier control system architecture preserves the stability properties of the lower-tier controller while improving the closed-loop performance. The theoretical results are demonstrated using two different chemical process examples.     

基于反馈无源化的切换非线性系统H∞跟踪控制

针对切换非线性系统,提出一种基于反馈无源化的H_∞跟踪控制策略.首先,提出依赖状态切换的控制方法,在子系统不满足有界参考弱最小相位这一标准假设时,给出解决H_∞跟踪问题的充分条件,通过零状态可检测条件保证切换系统的内部稳定性,并利用无源不等式验证切换非线性系统满足H_∞跟踪性能;然后,提出依赖时间切换的跟踪策略,得到H_∞跟踪问题的可解性条件,该方法不依赖系统内部状态进行切换,将系统输出和参考信号之间的误差作为控制输入,并计算出切换系统满足的平均驻留时间;最后,给出仿真算例,以验证结果的正确性.     

基于集结策略的非线性稳定预测控制器

针对有约束非线性系统预测控制在线计算量大的问题,引入集结策略降低其在线计算量并重点讨论了系统的稳定性问题．指出当控制器的终端状态处于某集合内且集结衰减系数的上界满足一定条件时,其最优目标函数递减．进而提出了一个双模控制律,可使系统渐近稳定．最后,通过仿真对该结论进行了验证．     

Adaptive-Predictive Control of a Class of SISO Nonlinear Systems

In this paper, an adaptive-predictive control algorithm is developed for a class of SISO nonlinear discrete-time systems based on a generalized predictive control (GPC) approach. The design is model-free, based directly on pseudo-partial-derivatives derived on-line from the input and output information of the system using a recursive least squares type of identification algorithm. The proposed control is especially useful for nonlinear systems with vaguely known dynamics. Robust stability of the closed-loop system is analyzed and proven in the paper. Simulation and real-time application examples are provided for real nonlinear systems which are known to be difficult to model and control.     

A Control Strategy for Terrain Adaptive Bipedal Locomotion

Rhythmic movements of a five-link sagittal biped with muscle-likeactuators are considered. In walking, as the support phases changecontact is periodically made with the environment. The inputs toevery actuator are modeled after the inputs to muscles in mammals. Thesystem possesses intrinsic position and velocity feedback due to theactuator dynamics. A control strategy is articulated that is novelin that it; a) is physiologically viable; b) simplifies the dynamics;and c) adapts to the speed of walking, going up and down stairs,going up or down inclines, maneuvering over obstacles or holes, andthe tempo and stride length of walking. Walking simulations of afive-link sagittal biped are presented.     

一类非线性系统的广义预测控制研究

针对一类难以线性化的单输入单输出非线性离散系统,就其实际输出信号跟踪参考输出信号的控制问题,研究了它的广义预测控制律设计方法。在系统数学模型非线性项的系数多项式满足一定条件的情况下,通过适当的数学处理,使问题的本质归结为求解线性差分系统的一组Diophantine方程,从而解出了非线性系统广义预测控制律表达式中的各个系数多项式,并给出了广义预测控制律的具体解析形式。通过仿真实例验证了所提出设计方法的正确性和有效性。     

约束非线性系统理想点多目标安全预测控制

考虑具有状态和控制约束的仿射非线性系统多目标安全控制问题,本文提出一种保证安全和稳定的多目标安全模型预测控制(MOSMPC)策略.首先通过理想点逼近方法解决多个控制目标的冲突问题.其次,利用控制李雅普诺夫障碍函数(CLBF)参数化局部控制律,并确定系统不安全域.在此基础上,构造非线性系统的参数化双模控制器,减少在线求解模型预测控制(MPC)优化问题的计算量.进一步,应用双模控制原理和CLBF约束,建立MOSMPC策略的递推可行性和闭环系统的渐近稳定性,并保证闭环系统状态避开不安全域.最后,以加热系统的多目标控制为例,验证了本文策略的有效性.