Optimal Robust Output-Tracking of Autonomous Rovers with Dynamic Traction Control

With global aging people and patients with lower-limb dysfunction growing, motion control of the omnidirectional lower-limb rehabilitation robot during centre-of-gravity shift is becoming more and more important. This paper proposes a robust trajectory tracking control strategy for omnidirectional lower-limb rehabilitation robot during centre-of-gravity shift. The main contents of this paper consist of three parts: 1) The kinematic and dynamic model that considered centre-of-gravity shift are presented firstly. 2) A robust control strategy with H ∞ tracking performance is developed and used to achieve the desired trajectories. 3) Simulation tests are performed and demonstrate the feasibility and efficacy of the proposed approach.

In this paper, robust adaptive control strategies are designed for Underwater Remotely Operated Vehicles (ROVs) with velocity constraints. First, robust control strategies are investigated for under-water ROVs, and then adaptive robust control strategies are further developed with online parameter estimation. To prevent the velocity constraint violation, the Barrier Lyapunov Function (BLF) is employed in Lyapunov synthesis. By ensuring the boundedness of the BLF, we also guarantee that the velocity constraints are not transgressed. The stability analysis of the closed-loop system is provided and all closed-loop signals are ensured to be bounded. Simulation results for 5 degree-of-freedom (DOF) underwater ROV demonstrate the effectiveness of the proposed approach.

This article describes an adaptive robust control algorithm of the mobile manipulator based on robust neural network to solve disturbances, nonlinearity, nonholonomic constraints between the mobile platform and the mounted manipulator. According to the nonlinear mapping ability of neural network and fast learning ability, neural network and robust control strategies are integrated into the adaptive control algorithm for the mobile manipulator with nonlinear and nonholonomic constraints. Basis on the mobile manipulator dynamics model and its modeling analysis, the controller can drive the trajectory tracking error of the mobile manipulator to converge to zero. The simulation results show that the algorithm has higher precision of trajectory tracking control and can achieve good control effect.

The objective is to control a web transport system with winder and unwinder for elastic material. A physical modeling of this plant is made based on the general laws of physics. For this type of control problem, it is extremely important to prevent the occurrence of web break or fold by decoupling the web tension and the web velocity. Due to the wide-range variation of the radius and inertia of the rollers the system dynamics change considerably during the winding/unwinding process. Different strategies for web tension control and linear transport velocity control are presented. First, an H/sub /spl infin// robust control strategy which reduces the coupling between tension and velocity, is compared to the decentralized control strategy with proportional integral derivative (PID) controllers commonly used in the industry. Second, an H/sub /spl infin// robust control strategy with varying gains is shown to render the control more robust to the radius variations. Then, a linear parameter varying (LPV) control strategy with smooth scheduling of controllers is synthesized for different operating points and compared to the previous methods. Finally, this LPV control and the H/sub /spl infin// robust control strategy with varying gains are combined to give the best results on an experimental setup, for the rejection of the disturbances introduced by velocity variations and for the robustness to radius and inertia changes.

This paper presents a robust adaptive control strategy for nonlinear teleoperation systems. The controller is based on estimation of the impedance of human hand as well as that of the environment. The mentioned system is subjected to unmodeled dynamics, time-varying parameters and external force disturbances. The upper bound for the norm of disturbances and system uncertainties are not used in the presented control scheme. Furthermore, there is no constraint on the rate of changes and the amount of unknown parameters and perturbations. Given a robust adaptive control action and adaptation laws, the transparency and stability in teleoperation systems are mathematically proved using Lyapunov's direct method. Finally, simulation results obtained from a teleoperation system with two-link rotary robots are presented to show the effectiveness of the proposed control scheme.

The paper illustrates a methodology to design a robust control strategy for mechanical systems in which stiction, friction, parameter variations and external disturbances have relevant effects. A methodology for the rapid prototyping of a robust control strategy is presented. The effects of external disturbances, stiction, and friction phenomena are compensated by implementing a disturbance observer and an inverse friction model. The robust control strategy is designed by applying a dedicated software. The experimental results related to a complex laboratory mechanical system are presented.

This paper discusses the modeling and control of a spatial mobile manipulator which consists of a robotic manipulator mounted upon a wheeled mobile platform. By neglecting slip of the wheeled platform’s tires, nonholonomic constraints are introduced into the equations of motion which complicates the control problem. The dynamic equations of the mobile manipulator are derived using the Lagrange-d’Alembert formulation. In this formulation, the equations of motion are projected onto the subspace of allowable motions. Then, the solvability of tracking problems for the mobile manipulator is investigated by using input-output feedback linearization. The feasibility of the control approach is demonstrated through computer simulation.

The coupling of finite element simulations to mathematical optimization techniques has contributed significantly to product improvements and cost reductions in the metal forming industries. The next challenge is to bridge the gap between deterministic optimization techniques and the industrial need for robustness. This paper introduces a generally applicable strategy for modeling and efficiently solving robust optimization problems based on time consuming simulations. Noise variables and their effect on the responses are taken into account explicitly. The robust optimization strategy consists of four main stages: modeling, sensitivity analysis, robust optimization and sequential robust optimization. Use is made of a metamodel-based optimization approach to couple the computationally expensive finite element simulations with the robust optimization procedure. The initial metamodel approximation will only serve to find a first estimate of the robust optimum. Sequential optimization steps are subsequently applied to efficiently increase the accuracy of the response prediction at regions of interest containing the optimal robust design. The applicability of the proposed robust optimization strategy is demonstrated by the sequential robust optimization of an analytical test function and an industrial V-bending process. For the industrial application, several production trial runs have been performed to investigate and validate the robustness of the production process. For both applications, it is shown that the robust optimization strategy accounts for the effect of different sources of uncertainty onto the process responses in a very efficient manner. Moreover, application of the methodology to the industrial V-bending process results in valuable process insights and an improved robust process design.

This paper focuses on the direct current - alternating current (DC-AC) interfaced microsource based H? robust control strategies in microgrids. It presents detail of a DC-AC interfaced microsource model which is connected to the power grid through a controllable switch. A double loop current-regulated voltage control scheme for the DC-AC interface is designed. In the case of the load disturbance and the model uncertainties, the inner voltage and current loop are produced based on the H? robust control strategies. The outer power loop uses the droop characteristic controller. Finally, the scheme is simulated using the Matlab/Simulink. The simulation results demonstrate that DC-AC interfaced microsource system can supply high quality power. Also, the proposed control scheme can make the system switch smoothly between the isolated mode and grid-connected mode.

5 - Robust control strategy for HBV treatment: Considering parametric and nonparametric uncertainties

In this paper, a robust control scheme is proposed for a class of nonlinear systems that have not only additive nonlinear uncertainties but also unknown multiplicative signs. These signs are called control directions since they represent effectively the direction of motion under any given control. Except for the unknown control directions, the class of systems satisfy the generalized matching conditions. The proposed robust control is continuous and guarantees global stability of uniform ultimate boundedness without a priori knowledge of the control directions nor the knowledge of nonlinear dynamics except their size bounding functions. This is achieved by online identifying control directions and by utilizing shifting laws that change smoothly and accordingly the signs of robust controls. The analysis and design is done using Lyapunov's direct method.

Dynamic analysis and linear control strategies for proton exchange membrane fuel cell using a distributed parameter model

State estimation-based robust optimal control of influenza epidemics in an interactive human society

From the previous work, when solving the LQ optimal control problem with random coefficients (SLQ, for short), it is remarkably shown that the solution of the backward stochastic Riccati equations is not regular enough to guarantee the robustness of the feedback control. As a generalization of SLQ, interesting questions are, “how about the situation in the differential game?”, “will the same phenomenon appear in SLQ?”. This paper will provide the answers. In this paper, we consider a closed-loop two-person zero-sum LQ stochastic differential game with random coefficients (SDG, for short) and generalize the results of Lü–Wang–Zhang into the stochastic differential game case. Under some regularity assumptions, we establish the equivalence between the existence of the robust optimal feedback control strategy operators and the solvability of the corresponding backward stochastic Riccati equations, which leads to the existence of the closed-loop saddle points. On the other hand, the problem is not closed-loop solvable if the solution of the corresponding backward stochastic Riccati equations does not have the needed regularity.

High-fidelity quantum gates are crucial for achieving fault-tolerant quantum computing; however, decoherence significantly reduces gate fidelities during long operation times. Although optimal control techniques can theoretically minimize these operation times, they often neglect realistic uncertainties in system parameters. In this work, we demonstrate that by using robust optimal control strategies, the cross-resonance gate in superconducting systems can be operated within 64 ns, achieving fidelities of [Formula: see text] while maintaining robustness against up to 10% uncertainty in a single parameter. Alternatively, by extending the control time to 71 ns, we achieve fidelities of [Formula: see text] with robustness against up to 3% uncertainty. Our results identify the minimal control times attainable with experimentally feasible pulses and system parameters, as well as the maximum allowable static parameter error for high-fidelity operations. Furthermore, we demonstrate simultaneous robustness against both static and time-dependent errors by generating 100 ns control pulses ([Formula: see text]) that maintain robustness against 10% static parameter error and time-dependent parameter fluctuations two orders of magnitude stronger than typical experimental noise. These findings demonstrate a viable open-loop strategy for implementing fast, high-fidelity quantum gates in the presence of realistic system uncertainties that would otherwise degrade conventional control pulses.