Comparison between closed-loop and partial open-loop feedback control policies in long term hydrothermal scheduling

Lower-limb exoskeletons are widely researched to improve walking performance and mobility. Low-level sensor-less exoskeleton motor control is attractive for consumer applications due to reduced device complexity and cost, but complex and variable transmission system configurations make the development of effective open-loop motor controllers that are responsive to user input challenging. The objective of this study was to develop and validate an open-loop motor control framework resulting in similar or greater performance vs. closed-loop torque control. We used generalized linear regression to develop two open-loop controllers by modeling motor current during exoskeleton-assisted walking; a "complex" model used desired torque and estimated ankle angular velocity as inputs, while a "simple" model used desired torque alone. Five participants walked at 1.0-1.3 m/s on a treadmill with closed-loop and both open-loop controllers providing ankle exoskeleton assistance. Both open-loop current controllers had similar root-mean-squared torque tracking error (p=0.23) compared to the closed-loop torque-feedback controller. Both open-loop controllers had improved relative average torque production (p<0.001 complex, p=0.022 simple), lower power consumption (p<0.001 for both), and reduced operating noise (p=0.002 complex, p<0.001 simple) over the closed-loop controller. New control models developed for a different ankle exoskeleton configuration showed similar improvements (lower torque error, greater average and peak torque production, lower power consumption) over closed-loop control during over-ground walking. These results demonstrate that our framework can produce open-loop motor controllers that match closed-loop control performance during exoskeleton operation.

THE INFLUENCE OF HYDROLOGIC INFORMATION IN LONG-TERM HYDROTHERMAL SCHEDULING

Voltage source inverters (VSIs) with output LCL filters are the key interfaces for today's distributed energy resource. There are mainly two groups of current control methods of a VSI: direct error tracking control with PWM, and closed-loop feedback control. Direct current error control, such as predictive control and hysteresis control, has some drawbacks like system parameter sensitivity, variable switching frequency, etc. On the other hand, the closed-loop feedback control could eliminate many drawbacks of direct error tracking PWM method while with the limited of control bandwidth. Closed-loop current control of a VSI can be of two types namely single-loop and multiple-loop VSI control. According to the feedback currents or number of current sensors used, the closed-loop current control can also be classified into single current sensor and two current sensors feedback system. The stability and dynamic performance of these control schemes differs from each other. However, a thorough understanding of the differences and the reasons behind is not available. This paper presents a comparative analysis of different closed-loop current control method for a VSI with output LCL filters. Effect of LCL filter parameter variation on their stability is investigated. Recently proposed generalized closed-loop control (GCC) platform is used to explain the comparison results. Simulation and experimental results of different VSI control systems are presented.

This paper presents a predictive control approach for long-term generation scheduling of hydro-thermal power systems. The approach is based on an open-loop feedback control scheme that uses a neural fuzzy network forecasting model, for handling the stochastic nature of inflows, and a deterministic nonlinear optimization model, to determine the discharge decisions to be implemented. As a consequence, inflow correlations on time can be represented by nonlinear relationships, and hydropower generation and thermal fuel cost can be handled by nonlinear functions, allowing a more precise modeling of the problem. A simulation model was also developed for performance assessment of the proposed approach. A comparison with the classical stochastic dynamic programming approach, in the case of single reservoir systems, revealed that the latter and the proposed approach perform similarly. The approach was also applied to a multi-reservoir system composed of 19 hydro plants and 10 reservoirs corresponding to a major cascade of the Brazilian power system. The results show that the proposed approach performs as well as in the single reservoir case study.

Multi-degree-of-freedom robots are widely used in various industries. In order to improve the stability of multi-degree-of-freedom robots, this paper proposes a motion trajectory optimization method based on PSO optimization algorithm and a closed-loop feedback control method for multi-degree-of-freedom robots based on error feedback. The standard D-H parameter method is used for kinematics analysis, combined with the multi-factor constraint parameter fusion method to establish the closed-loop feedback adaptive control law of the robot, and the robot's pose is adaptively adjusted according to the parameter optimization results to realize the stability control of the robot. The analysis results show that the multi-degree-of-freedom robot control with the analysis method in this paper has less error, strong robustness and accuracy of the kinematics method.

The vision of this work is to build a generalized model of haptic exploratory procedures that can be employed by a wide range of robotic platforms in different environments. Main challenge of combining deep learning and robotics is currently the time-efficiency of sample acquisition. Having to learn to perform a sequence of interactions with the environment, in which next action may depend on the previously acquired data, adds an extra complexity to the task of quickly teaching a robot to perform a haptic task. A meta-model for exploratory procedures built with data acquired by multiple robot platforms in simulation and online, that can be quickly adapted to a new robot or task, may offer a solution to this challenge. Here, we describe our approach to meta-learning of a haptic exploration policy offline, and demonstrate preliminary results achieved after only two gradient steps performed online with data acquired by a robot. We exemplify our approach on the task of learning to classify four simple three-dimensional objects. The meta-learner’s learning rule enables us to learn a generalized policy representing experience from different types of data available offline, and quickly adapt it to a new task – online classification of objects based on a sequence of tactile sensor measurements acquired by a robot. Tactile measurements are acquired through performing of three haptic glances per object at poses generated by the trained closedloop control policy. According to the principles of interactive perception, we optimize the closed-loop location control policy, integration of the data from the past iterations, and a classifier that classifies the objects all in one go. We employ the model resulting from a meta-training to control haptic exploration on the real robot. The classification accuracy achieved after two gradient updates of the meta-model performed with the data acquired by the robot is 93.7 % evaluated on a batch of 16 samples.

In order to improve the efficiency of underground mining and tunneling operations and to realize automatic drilling, it is necessary to develop the automation system for large drill jumbos. This work focuses on one such mining drill jumbo which is actually a redundant robotic manipulator with eight degrees of freedom, because it has six revolute joints and two prismatic joints. To realize the autonomous drilling operation, algorithms are proposed to calculate the desired pose of the end-effector and to solve the inverse kinematics of the drill jumbo, which is one of the key issues for developing the automation system. After that, a control strategy is proposed to independently control the eight joint variables using PID feedback control approaches. The simulation model is developed in Simulink. As the closed-loop controllers corresponding to all joints are local and independent of each other, the whole system is not a closed-loop feedback control. In order to estimate the possible maximal pose error, the analysis of the pose error caused by the errors of the joint variables is conducted. The results are satisfactory for mining applications and the developed automation system is being applied in the drill jumbos built by Mining Technologies International Inc.

A high-precision variable-thrust control method based on real-time measurement of pintle displacement and closed-loop feedback control is proposed to solve the technical problems of deep throttling variable-thrust regulation and control of pintle liquid rocket engines (LRE). By optimizing the system structure and control parameters, the closed-loop control of displacement with high precision and a fast response under a wide range of variable thrust can be realized, and thus the large-range, fast-response, and high-precision control of the chamber pressure, equivalent to thrust, can be indirectly realized. The chamber pressure response time is not more than 0.3 s, the overshoot is not more than ±3%, and the pulsation amplitude is not more than ±5%, which can meet the technical requirements of the large-range thrust adjustment and control of variable-thrust LRE of reusable launch rockets. The proposed variable-thrust LRE thrust control system is simple, reliable, and easy to use and maintain, which solves the problem of the large range, high precision, and fast response of thrust adjustment and control. The proposed system can provide important technical support for carrier rocket recycling and launch cost reduction. This is the first time a closed-loop control method of displacement of an integrated gas generator/flow regulator to achieve a 5:1 large-range continuous-variable-thrust control for the LRE of a reusable launch rocket has been proposed.

This paper addresses the difficult problem of fault-tolerant control and closed-loop control allocation for spacecraft attitude control system with actuator failures, actuator saturation, and external disturbances. As a fundamental step, a modified fault diagnosis observer is proposed utilizing the iterative learning methodology to reconstruct the actuator failures in real time. On the basis of the previously reconstructed failure information, a fault-tolerant control scheme incorporating with a parameter adjusting law is presented to enforce the spacecraft attitude control system to reach the real sliding mode surface in finite time. Meanwhile, the singularity of control command will be avoided using the saturation function, and the chattering problem restrained by the adjusting law. Furthermore, with the concept of control allocation, a novel on-line closed-loop constrained optimal fault-tolerant control allocation scheme is employed to distribute the signals synthesized by the baseline controller over the redundant actuators with failures and constraints. The stability of the closed-loop fault-tolerant control allocation process is guaranteed by the theory of the closed-loop discrete-time feedback control system. The key achievement of the proposed systematic strategy is that the whole closed-loop attitude control system can theoretically be guaranteed to be stable. Numerical simulations are carried out to verify the effectiveness and superiority of the developed approach.

This paper presents the nonlinear closed-loop feedback control strategy for the spacecraft rendezvous problem with finite low thrust between libration orbits in the Sun–Earth system. The model of spacecraft rendezvous takes the perturbations in initial states, the actuator saturation limits, the measurement errors, and the external disturbance forces into consideration from an engineering point of view. The proposed nonlinear closed-loop feedback control strategy is not analytically explicit; rather, it is implemented by a rapid re-computation of the open-loop optimal control at each update instant. To guarantee the computational efficiency, a novel numerical algorithm for solving the open-loop optimal control is given. With the aid of the quasilinearization method, the open-loop optimal control problem is replaced successfully by a series of sparse symmetrical linear equations coupled with linear complementary problem, and the computational efficiency can be significantly increased. The numerical simulations of spacecraft rendezvous problems in the paper well demonstrate the robustness, high precision, and dominant real-time merits of the proposed closed-loop feedback control strategy.

This paper describes a new approximation method to synthesize open loop control schemes for the control of copolymer composition and molecular weight in batch and semibatch polymerization reactors. The open loop control policies are derived from the transient response of the fictitious feedback control system obtained by numerical model simulations. The applicability of the proposed method is demonstrated through numerical examples.

This study presents a survey on quantum control theory and applications from a control systems perspective. Some of the basic concepts and main developments (including open-loop control and closed-loop control) in quantum control theory are reviewed. In the area of open-loop quantum control, the paper surveys the notion of controllability for quantum systems and presents several control design strategies including optimal control, Lyapunov-based methodologies, variable structure control and quantum incoherent control. In the area of closed-loop quantum control, this study reviews closed-loop learning control and several important issues related to quantum feedback control including quantum filtering, feedback stabilisation, linear-quadratic-Gaussian control and robust quantum control.

Stabilogram-diffusion analysis was used to examine how prolonged periods in microgravity affect the open-loop and closed-loop postural control mechanisms. It was hypothesized that following spaceflight: (1) the effective stochastic activity of the open-loop postural control schemes in astronauts is increased; (2) the effective stochastic activity and uncorrelated behavior, respectively, of the closed-loop postural control mechanisms in astronauts are increased; and (3) astronauts utilized open-loop postural controls schemes for shorter time intervals and smaller displacements. Four crew members and two alternates from the 14-day Spacelab Life Sciences 2 Mission were included in the study. Each subject was tested under eyes-open, quiet-standing conditions on multiple preflight and postflight days. The subjects' center-of-pressure trajectories were measured with a force platform and analyzed according to stabilogram-diffusion analysis. It was found that the effective stochastic activity of the open-loop postural control schemes in three of the four crew members was increased following spaceflight. This result is interpreted as an indication that there may be in-flight adaptations to higher-level descending postural control pathways, e.g., a postflight increase in the tonic activation of postural muscles. This change may also be the consequence of a compensatory (e.g., "stiffening") postural control strategy that is adopted by astronauts to account for general feeling of postflight unsteadiness. The crew members, as a group, did not exhibit any consistent preflight/postflight differences in the steady-state behavior of their closed-loop postural control mechanisms or in the functional interaction of their open-loop and closed-loop postural control mechanisms. These results are interpreted as indications that although there may be in-flight adaptations to the vestibular system and/or proprioceptive system, input from the visual system can compensate for such changes during undisturbed stance.

Using closed-loop ellipsometric feedback control, we have grown a variety of epitaxial AlxGa1−xAs structures by chemical beam epitaxy where compositions x vary continuously with thickness according to a given input function. Present limits are exemplified by a 200 Å parabolic quantum well structure grown using compositions determined from the outermost running ∼3 Å (∼1 monolayer) of depositing material.

In a DC microgrid, a converter connecting two DC buses is a DC-DC interlinking converter (ILC). In the ILCs, this paper proposes a simple control solution to handle two control issues simultaneously: a) high-voltage-side-series low-voltage-side-parallel (HSLP) modular ILC, b) control adaptability in different grid-working modes. Existing closed-loop control methods are complex and usually do not consider the two issues together. Open-loop controls feature very low cost for realization. Some open-loop controlled ILCs show good performances in the two issues: automatic voltage sharing in HSLP modules, good adaptability in different grid-working modes. The secret is that in these open-loop controlled ILCs: when the steady converter power changes, steady voltages of the two ports are nearly proportional. However, open-loop controls are restricted to certain converter topologies and they cannot modify the converter performances based on sampling feedback. For DC-DC ILCs, this paper proposes a very simple but comprehensive closed-loop control named ‘virtual transformer’. This control uses closed-loop feedback to learn the proportional-port-voltage feature from the open-loop controlled ILCs. Thus these good performances and the low cost are inherited, while the main shortcomings of open-loop controls are overcome.