General Control Framework Research Articles

Integration of Robotic Technologies for Rapidly Deployable Robots

The automation of production lines in industrial scenarios implies solving different problems, such as the flexibility to deploy robotic solutions to different production lines, usability to allow non-robotics expert users to teach robots different tasks, and safety to enable operators to physically interact with robots without the need of fences. In this paper, we present a system that integrates three novel technologies to address the above mentioned problems. We use an autocalibrated multi-modal robot skin , a general robot control framework to generate dynamic behaviors fusing multiple sensor signals, and an intuitive and fast teaching by demonstration method based on semantic reasoning. We validate the proposed technologies with a wheeled humanoid robot in an industrial set-up. The benefits of our system are the transferability of the learned tasks to different robots, the reusability of the models when new objects are introduced in the production line, the capability of detecting and recovering from errors, and the reliable detection of collisions and pre-collisions to provide a fast reactive robot that improves the physical human-robot interaction.

Signal Cooperative Control With Traffic Supply and Demand on a Single Intersection

Traffic signal control is widely used at intersection to improve its operation efficiency. However, the existing signal control systems cannot satisfy the control requirements under unsaturated, saturated, and oversaturated conditions, which will induce queue spillover, even network deadlock. A signal Cooperative Control method with traffic Supply and Demand (CCSD) on a single intersection is put forward to maximize the efficiency and avoid queue spillover by the cooperation between traffic supply and demand. A general CCSD control framework is constructed by the control relationship description and discrete-time statespace equations. Furthermore, the uniform matrix description of CCSD is put forward under the framework to fast solve the problem by matrix calculation. An artificial intelligence planning model on CCSD is established by an objective function compromising between throughput and fairness to satisfy the control requirements under dynamic unknown traffic environment. CCSD is compared with the Webster method and capacity-aware back-pressure (CABP) control in the experiments by both the simulation data and investigation data under unsaturated, saturated, and oversaturated conditions. The results show that CCSD is superior to CABP control and the Webster method in the throughput, the number of stops, and stop time, and can avoid the queue spillover. Accordingly, CCSD can be used to improve the efficiency and avoid queue spillover at intersection under all traffic conditions.

Fixed-point based hierarchical MPC control design for a cryogenic refrigerator

In this paper, a simple, general and scalable hierarchical control framework is proposed and validated through the interconnection of the Joule–Thomson and the Brayton cycle stages of a cryogenic refrigerator. The proposed framework enables to handle the case of destabilizing interconnections through state and/or control signals (which is the case of the cryogenic refrigerator example). Moreover, it offers the possibility to simply change the behavior of the overall system (depending on the context) by only changing the coordinator problem's parameters without changing the set of local controllers used by subsystems which is a common industrial requirement regarding industrial control architectures. Finally, the proposed scheme enables a smooth operator handover on a specific subsystem and/or actuator.

Feedback control of multibody systems with joint clearance and dynamic backlash: a tutorial

The problem of feedback control of mechanisms with joint clearance is analysed. Various control strategies are reviewed: impactless trajectories with persistent contact, control through collisions, the stabilization of equilibrium points, and trajectory tracking control. This article sets a general control framework, brings some preliminary answers and leaves some problems open, which are mentioned throughout the article and in the conclusions.

Towards 4D Trajectory Tracking for Transport Aircraft

This paper presents a new approach to perform 4D trajectory tracking for transportation aircraft. As current systems are extensions of 3D guidance with overfly time constraints at some given points and no general control framework has been developed for 4D guidance of a transport aircraft; the main goal of the proposed approach is to introduce a new method based on the inversion of the flight dynamics while avoiding numerical issues. A six degree of freedom model for a wide body transportation aircraft was developed in Matlab to provide a numerical simulation of the proposed approach, showing satisfying results.

H2−H∞ control of discrete-time nonlinear systems using the state-dependent Riccati equation approach

ABSTRACTA novel H2−H∞ State-dependent Riccati equation control approach is presented for providing a generalized control framework to discrete-time nonlinear system. By solving a generalized Riccati equation at each time step, the nonlinear state feedback control solution is found to satisfy mixed performance criteria guaranteeing quadratic optimality with inherent stability property in combination with H∞ type of disturbance attenuation. Two numerical techniques to compute the solution of the resulting Riccati equation are presented: The first one is based on finding the steady-state solution of the difference equation at every step and the second one is based on finding the minimum solution of a linear matrix inequality. The effectiveness of the proposed techniques is demonstrated by simulations involving the control of an inverted pendulum on a cart, a benchmark mechanical system.

Resilient and Robust Control of Time-Delay Wind Energy Conversion Systems

Wind energy is the fastest growing and the most promising renewable energy resource. High efficiency and reliability are required for wind energy conversion systems (WECSs) to be competitive within the energy market. Difficulties in achieving the maximum level of efficiency in power extraction from the available wind energy resources warrant the collective attention of control and power system engineers. A strong movement toward sustainable energy resources and advances in control system methodologies make previously unattainable levels of efficiency possible. In this paper, we design a general resilient and robust control framework for a time-delay variable speed permanent magnet synchronous generator (PMSG)-based WECS. A linear matrix inequality-based control approach is developed to accommodate the unstructured model uncertainties, L2 type of external disturbances, and time delays in input and state feedback variables. Computer simulation results have shown the efficacy of the proposed approach of achieving asymptotic stability and H∞ performance objectives.

A New Framework for Microgrid Management: Virtual Droop Control

Microgrids can provide the most promising means of integrating large amounts of distributed sources into the power grid and can supply reliable power to critical loads. A generalized control framework is required to regulate microgrid voltage and frequency, maintain system stability, maintain power quality, and manage distributed generations. A microgrid control framework for power management and voltage and frequency regulation is proposed in this paper. The proposed method, virtual droop control, is described and formulated and compared with the existing natural droop control technique. Unit commitment algorithm has also been implemented to manage nonrenewable sources to improve the system efficiency. The proposed technique operates the microgrid at a constant voltage and frequency, and uses communication for power sharing. It also provides the means to operate the microgrid in case of lost communication and sabotage on communication network. The proposed method has been applied to Fort Sill microgrid and the modeling results have been compared with natural droop control technique. A laboratory setup, which consists of a 100 kW natural gas generator, 56 kWh Li-ion based battery with 250 kW inverter, and 100 kW load bank, has been built and tested. The results of the setup have been provided, which confirms the viability of the proposed technique.

Homogeneous Active Disturbance Attenuation for a Perturbed Chain of Integrators

Abstract: Motivated by the homogeneous system theory and its facility in nonlinear control design, a global homogeneous active anti-disturbance method for a class of higher-order nonlinear systems subject to mismatched disturbances is investigated in this paper. Utilizing the flexibility of disturbance soft-estimations with active elimination of the adverse effects caused by disturbances, a homogeneous domination feedback technique is integrated such that a general composite active anti-disturbance control framework is proposed. With a delicate recursive handling procedure of the non-vanishing nonlinearities, the mismatched disturbances are compensated in a novel step-by-step way. A rigorous stability analysis assures the effectiveness of the proposed strategy. Numerical simulation results affirm the control and disturbance rejection performances.

A generalized control framework of assistive controllers and its application to lower limb exoskeletons

Various control methods have been studied for the natural assistance of human motions by exoskeletal robots, i.e., wearable robots for assisting the human motions. For example, impedance control and compliance control are widely used for controlling interaction forces between a human and a robot. When an accurate measurement of the human muscular force is available (e.g., electromyography), a direct use of the estimated human joint torque is possible in the control of an assistive robot. The human motions in a daily living, however, are so complex that they are constituted by multiple phases, such as walking, sitting, and standing, where the walking can be further categorized into multiple sub-phases. Therefore, a single control method cannot be the best option for all the motion phases; a switch in the control algorithms may be necessary for assisting human movements in multiple motion phases. In this paper, a generalized control framework is proposed to incorporate the various assistive control methods in one general controller structure, which consists of Feedforward Disturbance Compensation Control, Reference Tracking Feedback Control, Reference Tracking Feedforward Control, Model-based Torque Control. The proposed control framework is designed taking into consideration of the linearity of each control algorithm, and thus it enables the continuous and smooth switching of assistive control algorithms, and makes it possible to analyze the stability of the overall control loop. The proposed method is implemented into a lower-limb exoskeleton robot and is verified by experimental results.

A novel exergy-event based model predictive control strategy for energy saving

Industrial processes are among the biggest energy consumers and also the highest energy-wasting fields and many applied methods have been proposed to save energy more in these processes. The main purpose of event-based control is to reduce the computing load and communication efforts only after an event occurs which could save energy. Energy consumption and control performance are major challenges in event-based control. Exergy is the basic criterion to analyze a process in terms of the energy associated with control performance. MPC a widely used in industry, is utilized to solve an optimal control problem based on control performance aiming to save more energy. Moreover, MPC enables the controller to cope explicitly with MIMO plants and constraints such as state constraints and actuator constraints. The exergy-event based strategy under the general model predictive control (MPC) framework from viewpoint of energy saving is investigated in this paper. It will be shown that the proposed architecture is guaranteed to reduce the energy and exergy losses, the computational burden and communication effort of the whole system.

A General Mandatory Access Control Framework in Distributed Environments

A General Mandatory Access Control Framework in Distributed Environments

Optimal regime switching and threshold effects

We consider a general control problem with two types of optimal regime switch. The first one concerns technological and/or institutional regimes indexed by a finite number of discrete parameter values, and the second features regimes relying on given threshold values for given state variables. We propose a general optimal control framework allowing to derive the first-order optimality conditions and in particular to characterize the geometry of the shadow prices at optimal switching times (if any). We apply this new optimal control material to address the problem of the optimal management of natural resources under ecological irreversibility, and with the possibility to switch to a backstop technology.

Linear-quadratic model predictive control for urban traffic networks

Advancements in the efficiency, quality and manufacturability of sensing and communication systems are driving the field of intelligent transport systems (ITS) into the twenty first century. One key aspect of ITS is the need for efficient and robust integrated network management of urban traffic networks. This paper presents a general model predictive control framework for both centralized traffic signal and route guidance systems aiming to minimize network congestion. Our novel model explicitly captures both non-zero travel time and spill-back constraints while remaining linear and thus generally tractable with quadratic costs. The end result is a central control scheme that may be realized for large urban networks containing thousands of sensors and actuators.We demonstrate the essence of our model and controller through a detailed mathematical description coupled with simulation results of specific scenarios. We show that using a central scheme such as ours may reduce the congestion inside the network by up to half while still achieving better throughput compared to that of other conventional control schemes.

A general analysis and control framework for process systems with inventory recycling

SUMMARY In this work, we generalize our previous results concerning the impact of material recycling and energy recovery on plant dynamics and control. We define a generic class of integrated process systems, in which an extensive quantity that obeys conservation laws is recovered from the process output and recycled to the process feed; the operation of the system is assumed to be subject to time-varying, measurable disturbances. We establish, in this general case, that integration is conducive to the emergence of a two-time-scale dynamic behavior and derive reduced-order models for the dynamics in each time scale. Subsequently, we postulate a hierarchical control framework that exploits these dynamics results in the design of coordinated fast and slow feedback/feedforward controllers and formulate a stability result for the closed-loop system. We demonstrate these concepts on a case study concerning an energy-integrated process. Copyright © 2013 John Wiley & Sons, Ltd.

Linear-Quadratic Model Predictive Control for Urban Traffic Networks

Advancements in the efficiency, quality and manufacturability of sensing and communication systems are driving the field of intelligent transport systems (ITS) into the twenty first century. One key aspect of ITS is the need for efficient and robust integrated network management of urban traffic networks. This paper presents a general model predictive control framework for both centralized traffic signal and route guidance systems aiming to minimize network congestion. Our novel model explicitly captures both non-zero travel time and spill-back constraints while remaining linear and thus generally tractable with quadratic costs. The end result is a central control scheme that may be realized for large urban networks containing thousands of sensors and actuators.We demonstrate the essences of our model and controller through a detailed mathematical description coupled with simulation results of specific scenarios. We show that using a central scheme such as ours may reduce the congestion inside the network by up to half while still achieving better throughput compared to that of other conventional control schemes.

Reflexive stability control framework for humanoid robots

In this paper we propose a general control framework for ensuring stability of humanoid robots, determined through a normalized zero-moment-point (ZMP). The proposed method is based on the modified...

Bounded control for preserving connectivity of multi-agent systems using the constraint function approach

In multi-agent control systems, coordination of agents often relies critically on the connectivity of the underlying communication network. This study analyses the problem of preserving connectivity with bounded control inputs for multi-agent systems. Firstly, a general potential-based control framework is investigated and sufficient conditions for achieving rendezvous while preserving connectivity are presented. Then, based on the modification of the potential-based control, a novel bounded control law with very mild design requirements is proposed and the issues of preserving connectivity, the agent group rendezvous, and the input bound of the controller are discussed. The effectiveness of the proposed control law and the boundedness of the inputs are illustrated by numerical examples.

A general hybrid semi-parametric process control framework

A general hybrid semi-parametric process control framework is proposed in this study. The motivation was the integration of different levels of knowledge systems into a general hybrid semi-parametric control structure, of which the general linear controller or the PID controller are, for instance, particular cases.Several hybrid semi-parametric control structure variants and tuning methods are benchmarked in relation to a simulated bioprocess control problem, namely closed-loop control of the biomass concentration through manipulation of the substrate feeding rate, coupled with the closed-loop control of the dissolved oxygen concentration through the stirring velocity. The results demonstrate that (i) due to the hybrid approach the control loop can be closed without any additional identification experiments; (ii) the incorporation of different types of knowledge can enhance the controller performance, when compared to structures without a priori knowledge; (iii) knowledge incorporation seems to facilitate the tuning of the controller; and (iv) the control action can be analyzed in relation to structural information incorporated into the hybrid controller.

Modeling Hysteresis with Inertial-Dependent Prandtl-Ishlinskii Model in Wide-Band Frequency-Operated Piezoelectric Actuator

One of the major problems occurring in many technical applications is the presence of the hysteretic behavior in sensors and actuators, which causes a nonlinear relationship between input and output variables in such devices. Since the nonlinear phenomenon of hysteresis degrades the performance of the piezoelectric materials and piezoelectric drive mechanisms, for example, in positioning control framework, it has to be characterized in order to mitigate the effect of the nonlinearity in the devices. This paper is aimed to characterize and model the hysteresis in typical piezoelectric actuators under load-free and preloaded circumstances incorporating the inertial effect of the system. For this purpose, the piezoelectric actuator is modeled as a mass-spring-damper system, which is expressed in terms of a stop operator as one of the essential yet efficient hysteresis operators in the Prandtl-Ishlinskii (PI) model. The reason of utilizing the stop operator in this study is for the sake of control purposes, as the stop operator plays as the inverse of the play operator in the PI model and can be used in a feed-forward controller scheme to suppress the effect of hysteresis in general control framework. The results reveal that this model exhibits better correspondence to the measurement output compared to that of the classical PI model.