Many vehicle manufacturers have lately introduced advance driver support in some of their automobiles. One of those new features is Adaptive Cruise Control DACCE, which extends the conventional cruise control system to control of relative speed and distance to other vehicles. In order to design an ACC controller it is suitable to have a model of driver behavior. The approach in the thesis is to use system identification methodology to obtain dynamic models of driver behavior useful for ACC ap...
Full Text Available This paper describes the Adaptive Cruise Control system (ACC, a system which reduces the driving burden on the driver. The ACC system primarily supports four driving modes on the road and controls the acceleration and deceleration of the vehicle in order to maintain a set speed or to avoid a crash. This paper proposes more accurate methods of detecting the preceding vehicle by radar while cornering, with consideration for the vehicle sideslip angle, and also of controlling the distance between vehicles. By making full use of the proposed identification logic for preceding vehicles and path estimation logic, an improvement in driving stability was achieved.
Larsen, Kim Guldstrand; Mikučionis, Marius; Taankvist, Jakob Haahr
In a series of contributions Olderog et al. have formulated and verified safety controllers for a number of lane-maneuvers on multilane roads. Their work is characterized by great clarity and elegance partly due to the introduction of a special-purpose Multi-Lane Spatial Logic. In this paper, we...... want to illustrate the potential of current modelchecking technology for automatic synthesis of optimal yet safe (collision-free) controllers. We demonstrate this potential on an Adaptive Cruise Control problem, being a small part of the overall safety problem considered by Olderog....
Willigen, W.H. van; Schut, M.C.; Kester, L.J.H.M.
This paper is concerned with safety in (cooperative) adaptive cruise control systems. In these systems, the speed of the cars is maintained automatically, based on the preferred speed of the driver and the speed of the preceding car. Technologies that are used in these systems, such as radar and rad
Ahn, Dae Ryong; Yang, Ji Hyun; Lee, Sang Hun [Kookmin University, Seoul (Korea, Republic of)
Recent development in science and technology has enabled vehicles to be equipped with advanced autonomous functions. ADAS (Advanced Driver Assistance Systems) are examples of such advanced autonomous systems added. Advanced systems have several operational modes and it has been observed that drivers could be unaware of the mode they are in during vehicle operation, which can be a contributing factor of traffic accidents. In this study, possible mode confusions in a simulated environment when vehicles are equipped with an adaptive cruise control system were investigated. The mental model of the system was designed and verified using the formal analysis method. Then, the user interface was designed on the basis of those of the current cruise control systems. A set of human-in-loop experiments was conducted to observe possible mode confusions and redesign the user interface to reduce them. In conclusion, the clarity and transparency of the user interface was proved to be as important as the correctness and compactness of the mental model when reducing mode confusions.
Recent development in science and technology has enabled vehicles to be equipped with advanced autonomous functions. ADAS (Advanced Driver Assistance Systems) are examples of such advanced autonomous systems added. Advanced systems have several operational modes and it has been observed that drivers could be unaware of the mode they are in during vehicle operation, which can be a contributing factor of traffic accidents. In this study, possible mode confusions in a simulated environment when vehicles are equipped with an adaptive cruise control system were investigated. The mental model of the system was designed and verified using the formal analysis method. Then, the user interface was designed on the basis of those of the current cruise control systems. A set of human-in-loop experiments was conducted to observe possible mode confusions and redesign the user interface to reduce them. In conclusion, the clarity and transparency of the user interface was proved to be as important as the correctness and compactness of the mental model when reducing mode confusions
Klunder, G.; Li, M.; Minderhoud, M.
In 2006 in the Netherlands, a field operational test was carried out to study the effect of adaptive cruise control (ACC) and lane departure warning on driver behavior and traffic flow in real traffic. To estimate the effect for larger penetration rates, simulations were needed. For a reliable impac
Milanés, Vicente; Shladover, Steven E.
Vehicle longitudinal control systems such as (commercially available) autonomous Adaptive Cruise Control (ACC) and its more sophisticated variant Cooperative ACC (CACC) could potentially have significant impacts on traffic flow. Accurate models of the dynamic responses of both of these systems are needed to produce realistic predictions of their effects on highway capacity and traffic flow dynamics. This paper describes the develop-ment of models of both ACC and CACC control systems that are ...
Arem, van, Bart; Driel, van, J.; Visser, Ruben
Cooperative adaptive cruise control (CACC) is an extension of ACC. In addition to measuring the distance to a predecessor, a vehicle can also exchange information with a predecessor by wireless communication. This enables a vehicle to follow its predecessor at a closer distance under tighter control. This paper focuses on the impact of CACC on traffic-flow characteristics. It uses the traffic-flow simulation model MIXIC that was specially designed to study the impact of intelligent vehicles o...
The region of string stability of a platoon of adaptive cruise control vehicles, taking into account the delay and response of the vehicle powertrain, is found. An upper bound on the explicit delay time as a function the first-order powertrain response time constant is determined. The system is characterized by a headway time constant, a sensitivity parameter, relative (to the vehicle immediately in front) velocity control, and delayed-velocity feedback or acceleration feedback. -- Highlights: ► I find the region of stability for a realistic adaptive cruise control system. ► Vehicle response time and explicit delay are included in the analysis. ► Delayed-feedback enlarges the parameter space that gives string stability.
Full Text Available The auto-berthing of a ship requires excellent control for safe accomplishment. Crabbing, which is the pure sway motion of a ship without surge velocity, can be used for this purpose. Crabbing is induced by a peculiar operation procedure known as the push-pull mode. When a ship is in the push-pull mode, an interacting force is induced by complex turbulent flow around the ship generated by the propellers and side thrusters. In this paper, three degrees of freedom equations of the motions of crabbing are derived. The equations are used to apply the adaptive backstepping control method to the auto-berthing controller of a cruise ship. The controller is capable of handling the system nonlinearity and uncertainty of the berthing process. A control allocation algorithm for a ship equipped with two propellers and two side thrusters is also developed, the performance of which is validated by simulation of auto-berthing.
Park, Jong-Yong; Kim, Nakwan
The auto-berthing of a ship requires excellent control for safe accomplishment. Crabbing, which is the pure sway motion of a ship without surge velocity, can be used for this purpose. Crabbing is induced by a peculiar operation procedure known as the push-pull mode. When a ship is in the push-pull mode, an interacting force is induced by complex turbulent flow around the ship generated by the propellers and side thrusters. In this paper, three degrees of freedom equations of the motions of crabbing are derived. The equations are used to apply the adaptive backstepping control method to the auto-berthing controller of a cruise ship. The controller is capable of handling the system nonlinearity and uncertainty of the berthing process. A control allocation algorithm for a ship equipped with two propellers and two side thrusters is also developed, the performance of which is validated by simulation of auto-berthing.
Winter, J.C.F. de; Happee, R.; Martens, M.H.; Stanton, N.A.
Adaptive cruise control (ACC), a driver assistance system that controls longitudinal motion, has been introduced in consumer cars in 1995. A next milestone is highly automated driving (HAD), a system that automates both longitudinal and lateral motion. We investigated the effects of ACC and HAD on d
Davis, L C
Wirelessly connected vehicles that exchange information about traffic conditions can reduce delays caused by congestion. At a 2-to-1 lane reduction, the improvement in flow past a bottleneck due to traffic with a random mixture of 40% connected vehicles is found to be 52%. Control is based on connected-vehicle-reported velocities near the bottleneck. In response to indications of congestion the connected vehicles, which are also adaptive cruise control vehicles, reduce their speed in slowdown regions. Early lane changes of manually driven vehicles from the terminated lane to the continuous lane are induced by the slowing connected vehicles. Self-organized congestion at the bottleneck is thus delayed or eliminated, depending upon the incoming flow magnitude. For the large majority of vehicles, travel times past the bottleneck are substantially reduced. Control is responsible for delaying the onset of congestion as the incoming flow increases. Adaptive cruise control increases the flow out of the congested stat...
Winter, de, R.J.; Happee, Riender; Martens, Marieke H.; Stanton, Neville A.
Adaptive cruise control (ACC), a driver assistance system that controls longitudinal motion, has been introduced in consumer cars in 1995. A next milestone is highly automated driving (HAD), a system that automates both longitudinal and lateral motion. We investigated the effects of ACC and HAD on drivers’ workload and situation awareness through a meta-analysis and narrative review of simulator and on-road studies. Based on a total of 32 studies, the unweighted mean self-reported workload wa...
Davis, L. C.
Mixed traffic flow consisting of vehicles equipped with adaptive cruise control (ACC) and manually driven vehicles is analyzed using car-following simulations. Simulations of merging from an on-ramp onto a freeway reported in the literature have not thus far demonstrated a substantial positive impact of ACC. In this paper cooperative merging for ACC vehicles is proposed to improve throughput and increase distance traveled in a fixed time. In such a system an ACC vehicle senses not only the preceding vehicle in the same lane but also the vehicle immediately in front in the other lane. Prior to reaching the merge region, the ACC vehicle adjusts its velocity to ensure that a safe gap for merging is obtained. If on-ramp demand is moderate, cooperative merging produces significant improvement in throughput (20%) and increases up to 3.6 km in distance traveled in 600 s for 50% ACC mixed flow relative to the flow of all-manual vehicles. For large demand, it is shown that autonomous merging with cooperation in the flow of all ACC vehicles leads to throughput limited only by the downstream capacity, which is determined by speed limit and headway time.
Davis, L. C.
Wirelessly connected vehicles that exchange information about traffic conditions can reduce delays caused by congestion. At a 2-to-1 lane reduction, the improvement in flow past a bottleneck due to traffic with a random mixture of 40% connected vehicles is found to be 52%. Control is based on connected-vehicle-reported velocities near the bottleneck. In response to indications of congestion the connected vehicles, which are also adaptive cruise control vehicles, reduce their speed in slowdown regions. Early lane changes of manually driven vehicles from the terminated lane to the continuous lane are induced by the slowing connected vehicles. Self-organized congestion at the bottleneck is thus delayed or eliminated, depending upon the incoming flow magnitude. For the large majority of vehicles, travel times past the bottleneck are substantially reduced. Control is responsible for delaying the onset of congestion as the incoming flow increases. Adaptive cruise control increases the flow out of the congested state at the bottleneck. The nature of the congested state, when it occurs, appears to be similar under a variety of conditions. Typically 80-100 vehicles are approximately equally distributed between the lanes in the 500 m region prior to the end of the terminated lane. Without the adaptive cruise control capability, connected vehicles can delay the onset of congestion but do not increase the asymptotic flow past the bottleneck. Calculations are done using the Kerner-Klenov three-phase theory, stochastic discrete-time model for manual vehicles. The dynamics of the connected vehicles is given by a conventional adaptive cruise control algorithm plus commanded deceleration. Because time in the model for manual vehicles is discrete (one-second intervals), it is assumed that the acceleration of any vehicle immediately in front of a connected vehicle is constant during the time interval, thereby preserving the computational simplicity and speed of a discrete-time model.
Full Text Available Purpose: In this paper, the impact of Cooperative Adaptive Cruise Control (CACC systems on traffic performance is examined using microscopic agent-based simulation. Using a developed traffic simulation model of a freeway with an on-ramp - created to induce perturbations and to trigger stop-and-go traffic, the CACC system’s effect on the traffic performance is studied. The previously proposed traffic simulation model is extended and validated. By embedding CACC vehicles in different penetration levels, the results show significance and indicate the potential of CACC systems to improve traffic characteristics and therefore can be used to reduce traffic congestion. The study shows that the impact of CACC is positive but is highly dependent on the CACC market penetration. The flow rate of the traffic using CACC is proportional to the market penetration rate of CACC equipped vehicles and the density of the traffic.Design/methodology/approach: This paper uses microscopic simulation experiments followed by a quantitative statistical analysis. Simulation enables researchers manipulating the system variables to straightforwardly predict the outcome on the overall system, giving researchers the unique opportunity to interfere and make improvements to performance. Thus with simulation, changes to variables that might require excessive time, or be unfeasible to carry on real systems, are often completed within seconds.Findings: The findings of this paper are summarized as follow:•\tProvide and validate a platform (agent-based microscopic traffic simulator in which any CACC algorithm (current or future may be evaluated.•\tProvide detailed analysis associated with implementation of CACC vehicles on freeways.•\tInvestigate whether embedding CACC vehicles on freeways has a significant positive impact or not.Research limitations/implications: The main limitation of this research is that it has been conducted solely in a computer laboratory. Laboratory
Davis, L C
The dynamics of a platoon of adaptive cruise control vehicles is analyzed for a general mechanical response of the vehicle's power-train. Effects of acceleration-feedback control that were not previously studied are found. For small acceleration-feedback gain, which produces marginally string-stable behavior, the reduction of a disturbance (with increasing car number n) is found to be faster than for the maximum allowable gain. The asymptotic magnitude of a disturbance is shown to fall off as erf(ct./sq. rt. n) when n goes to infinity. For gain approaching the lower limit of stability, oscillations in acceleration associated with a secondary maximum in the transfer function (as a function of frequency) can occur. A frequency-dependent gain that reduces the secondary maximum, but does not affect the transfer function near zero frequency, is proposed. Performance is thereby improved by elimination of the undesirable oscillations while the rapid disturbance reduction is retained.
Zeeshan Ali Memon
Full Text Available Automotive vehicle following systems are essential for the design of automated highway system. The problem associated with the automatic vehicle following system is the string stability of the platoon of vehicles, i.e. the problem of uniform velocity and spacing errors propagation. Different control algorithm for the longitudinal control of a platoon are discussed based on different spacing policies, communication link among the vehicles of a platoon, and the performance of a platoon have been analysed in the presence of disturbance (noise and parametric uncertainties. This paper presented the PID (Proportional Integral Derivative feedback control algorithm for the longitudinal control of a platoon in the presence of noise signal and investigates the performance of platoon under the influence of sudden acceleration and braking in severe conditions. This model has been applied on 6 vehicles moving in a platoon. The platoon has been analysed to retain the uniform velocity and safe spacing among the vehicles. The limitations of PID control algorithm have been discussed and the alternate methods have been suggested. Model simulations, in comparison with the literature, are also presented.
Urnes, James, Sr.; Nguyen, Nhan; Ippolito, Corey; Totah, Joseph; Trinh, Khanh; Ting, Eric
Boeing and NASA are conducting a joint study program to design a wing flap system that will provide mission-adaptive lift and drag performance for future transport aircraft having light-weight, flexible wings. This Variable Camber Continuous Trailing Edge Flap (VCCTEF) system offers a lighter-weight lift control system having two performance objectives: (1) an efficient high lift capability for take-off and landing, and (2) reduction in cruise drag through control of the twist shape of the flexible wing. This control system during cruise will command varying flap settings along the span of the wing in order to establish an optimum wing twist for the current gross weight and cruise flight condition, and continue to change the wing twist as the aircraft changes gross weight and cruise conditions for each mission segment. Design weight of the flap control system is being minimized through use of light-weight shape memory alloy (SMA) actuation augmented with electric actuators. The VCCTEF program is developing better lift and drag performance of flexible wing transports with the further benefits of lighter-weight actuation and less drag using the variable camber shape of the flap.
Baret, Marc; Bomer, Thierry T.; Calesse, C.; Dudych, L.; L'Hoist, P.
Autonomous intelligent cruise control (AICC) systems are not only controlling vehicles' speed but acting on the throttle and eventually on the brakes they could automatically maintain the relative speed and distance between two vehicles in the same lane. And more than just for comfort it appears that these new systems should improve the safety on highways. By applying a technique issued from the space research carried out by MATRA, a sensor based on a charge coupled device (CCD) was designed to acquire the reflected light on standard-mounted car reflectors of pulsed laser diodes emission. The CCD is working in a unique mode called flash during transfer (FDT) which allows identification of target patterns in severe optical environments. It provides high accuracy for distance and angular position of targets. The absence of moving mechanical parts ensures high reliability for this sensor. The large field of view and the high measurement rate give a global situation assessment and a short reaction time. Then, tracking and filtering algorithms have been developed in order to select the target, on which the equipped vehicle determines its safety distance and speed, taking into account its maneuvering and the behaviors of other vehicles.
Full Text Available Recently there has been mammoth growth in the world population which has also contributed to the voluminous growth of vehicles. As a consequence of this, the numbers of accidents on roads have also increased to a large extent. Our system is an attempt to mitigate the same using synchronous programming language. The aim is to develop a safety crash warning system that will address the rear end crashes and also take over the controlling of the vehicle when the threat is at a very high level. Adapting according to the environmental conditions is also a prominent feature of the system. Safety System provides warnings to drivers to assist in avoiding rear-end crashes with other vehicles. Initially the system provides a low level alarm and as the severity of the threat increases the level of warnings or alerts also rises. At the highest level of threat, the system enters in a Cruise Control Mode, wherein the system controls the speed of the vehicle by controlling the engine throttle and if permitted, the brake system of the vehicle. We focus on this crash area as it has a very high percentage of the crash-related fatalities. A reference implementation of the safety algorithm in ESTEREL is proposed, which is also formally verified along with the proofs of various properties that the system obeys.
Jorge, Tiago R.; Lemos, João M; Barão, Miguel
The contribution of this paper consists in a procedure to solve the optimal cruise control problem that consists in transferring the car velocity between two specified values, in a fixed interval of time, with minimum fuel consumption. The solution is obtained by applying a recursive numerical algorithm that provides an approximation to the condition provided by Pontryagin’s Optimum Principle. This solution is compared with the one obtained by using a reduced complexity linear model for the c...
Grefe, William Kevin
This thesis presents collision avoidance integrated with lane keeping and adaptive cruise control for a car. Collision avoidance is the ability to avoid obstacles that are in the vehicleâ s path, without causing damage to the obstacle or car. There are three types of collision avoidance controllers, passive, active, and semi-active. This thesis is designed using active collision avoidance controllers. There are two controllers developed for collision avoidance in this paper. They are ...
With small profit margins in merchant shipping and more than eighty percent of sailing time being cross ocean voyages, speed control is crucial for vessel profitability......With small profit margins in merchant shipping and more than eighty percent of sailing time being cross ocean voyages, speed control is crucial for vessel profitability...
Experiences with Advanced Cruise Control in traffic; a limited experiment. Advanced Cruise Control (ACC) is an ordinary cruise control in which the desired speed is installed manually, but in which the headway time to the vehicle in front is also taken into account. If the headway time becomes less than the installed critical threshold value, the system brakes the vehicle gradually. If the vehicle in front is no longer there, or the headway time is greater than the threshold value, the instal...
Wei-Ming Li; Rui-Sheng Sun; Hong-Yang Bai; Peng-Yun Liu
In this paper, an adaptive sliding mode method was proposed for BTT autopilot of cruise missiles with variable-swept wings. To realize the whole state feedback, the roll angle, normal overloads and angular rates were considered as state variables of the autopilot, and a parametric sliding mode controller was designed via feedback linearization. A novel parametric adaptation law was put forward to estimate the nonlinear time-varying parameter perturbations in real time based on Lyapunov stability theory. A sliding mode boundary layer theory was adopted to smooth the discontinuity of control variables and eliminate the control chattering. The simulation was presented for the roll angle and overload commands tracking in different configuration schemes. The results indicated that the controlled system has robust dynamic tracking performance in condition of the large-scale aerodynamic parametric variety resulted from variable-swept wings.
Journet, Bernard A.; Bazin, Gaelle
THe purpose of this paper is to show to what kind of application laser range-finders can be used inside Autonomous Intelligent Cruise Control systems. Even if laser systems present good performances the safety and technical considerations are very restrictive. As the system is used in the outside, the emitted average output power must respect the rather low level of 1A class. Obstacle detection or collision avoidance require a 200 meters range. Moreover bad weather conditions, like rain or fog, ar disastrous. We have conducted measurements on laser rangefinder using different targets and at different distances. We can infer that except for cooperative targets low power laser rangefinder are not powerful enough for long distance measurement. Radars, like 77 GHz systems, are better adapted to such cases. But in case of short distances measurement, range around 10 meters, with a minimum distance around twenty centimeters, laser rangefinders are really useful with good resolution and rather low cost. Applications can have the following of white lines on the road, the target being easily cooperative, detection of vehicles in the vicinity, that means car convoy traffic control or parking assistance, the target surface being indifferent at short distances.
Assunta Di Vaio; Luisa Varriale
The paper aims to investigate the role played by the Accounting Information Systems (AIS) and management control in the cruise events management process. The authors analyse the events planned on the cruise ships stopped at the quay (cruise events on ship berthing) and the events organized on the terminal infrastructures (cruise events on terminal). In the last years, the events planned on the terminals are significantly increasing, but their management is still designed separately from the p...
BIN Yang; LI KeQiang; FENG NengLian
In this study,an innovative dynamics model of LFS(longitudinal vehicle full-speed cruise system)is developed by lumping the dynamics of a controlled vehicle and an inter-vehicles together.On account of the external disturbance,parameters uncertainty and the nonlinearity within LFS,a DDRC(disturbance decoupling robust control)method is proposed.For this method,the theory of NDD(nonlinear disturbance decoupling)is utilized firstly to separate the external disturbance from certain part of the proposed dynamics model.Then,the invariance over the sliding mode of VSC(variable structure control)is used to eliminate the influence of remaining uncertain part.Finally,the DDRC method is adopted to design an LFS ACC(adaptive cruise control)system,and some numerical simulations are carried out to validate its performance.The simulation results demonstrate that the proposed control system not only exhibits an expected dynamic response,high tracking accuracy and a strong robustness,but also achieves a global optimization by means of a simplified control structure.
Oh, B. J.; Jamshidi, M.; Seraji, H.
A decentralized adaptive control is proposed to stabilize and track the nonlinear, interconnected subsystems with unknown parameters. The adaptation of the controller gain is derived by using model reference adaptive control theory based on Lyapunov's direct method. The adaptive gains consist of sigma, proportional, and integral combination of the measured and reference values of the corresponding subsystem. The proposed control is applied to the joint control of a two-link robot manipulator, and the performance in computer simulation corresponds with what is expected in theoretical development.
A control system to aid mobility is presented that is intended to assist living independently and that provides physical guidance. The system has two levels: a human machine interface and an adaptive shared controller.
Narendra, K. S.; Annaswamy, A. M.
Several concepts and results in robust adaptive control are are discussed and is organized in three parts. The first part surveys existing algorithms. Different formulations of the problem and theoretical solutions that have been suggested are reviewed here. The second part contains new results related to the role of persistent excitation in robust adaptive systems and the use of hybrid control to improve robustness. In the third part promising new areas for future research are suggested which combine different approaches currently known.
Yang, Chi-Ming; Beck, James L.
A new robust adaptive structural control design methodology is developed and presented which treats modeling uncertainties and limitations of control devices. Furthermore, no restriction is imposed on the structural models and the nature of the control devices so that the proposed method is very general. A simple linear single degree-of-freedom numerical example is presented to illustrate this approach.
Volkov, Vasily Y; Zhuravlev, Oleg N; Nukhaev, Marat T; Shchelushkin, Roman V
This article presents the idea and realization for the unique Adaptive Inflow Control System being a part of well completion, able to adjust to the changing in time production conditions. This system allows to limit the flow rate from each interval at a certain level, which solves the problem of water and gas breakthroughs. We present the results of laboratory tests and numerical calculations obtaining the characteristics of the experimental setup with dual-in-position valves as parts of adaptive inflow control system, depending on the operating conditions. The flow distribution in the system was also studied with the help of three-dimensional computer model. The control ranges dependences are determined, an influence of the individual elements on the entire system is revealed.
Touran, A; Brackstone, M A; McDonald, M
This paper describes a general framework for safety evaluation of autonomous intelligent cruise control in rear-end collisions. Using data and specifications from prototype devices, two collision models are developed. One model considers a train of four cars, one of which is equipped with autonomous intelligent cruise control. This model considers the car in front and two cars following the equipped car. In the second model, none of the cars is equipped with the device. Each model can predict the possibility of rear-end collision between cars under various conditions by calculating the remaining distance between cars after the front car brakes. Comparing the two collision models allows one to evaluate the effectiveness of autonomous intelligent cruise control in preventing collisions. The models are then subjected to Monte Carlo simulation to calculate the probability of collision. Based on crash probabilities, an expected value is calculated for the number of cars involved in any collision. It is found that given the model assumptions, while equipping a car with autonomous intelligent cruise control can significantly reduce the probability of the collision with the car ahead, it may adversely affect the situation for the following cars. PMID:10440554
Generation of controller of an underwater robot for constant altitude cruising by self-training. 2nd Report. ; Modification of forward model and adaptation process. Jiko kunren ni yoru kaichu robot no teikodo koko. 2. ; Forward model to controller no chosei hoho no kairyo
Suto, T.; Ura, T. (The University of Tokyo, Tokyo (Japan). Institute of Industrial Science)
As a guidance system to be applied to constant altitude cruising of the self-controlling underwater robot, improvement of the SONCS (composed from controller network and forward model network) proposed in the previous paper by the author's laboratory is reported. The forward model network was divided into three modules respectively holding a function representing dynamics of the robot and deriving the quantity of state at a next time-step, a function of deriving the data of distance measurement at the next step, and a function of calculating the altitude from the data of distance measurement. A difference type network which represents the output with the increment from the input and a learning method which generates temporary instruction data train from the signals reversely propagating the forward network and thereby adjusts the controller network were introduced. Effectiveness of these three technical improvements was demonstrated based on numerical simulation. 4 refs., 12 figs.
National Aeronautics and Space Administration — M4 Engineering proposes the development of an adaptive structural mode control system. The adaptive control system will begin from a "baseline" dynamic model of the...
Beall, Jeffery C.
This study investigates an adaptive control scheme designed to maintain accurate motor speed control in spite of high-frequency periodic variations in load torque, load inertia, and motor parameters. The controller adapts, stores and replays a schedule of torques to be delivered at discrete points throughout the periodic load cycle. The controller also adapts to non-periodic changes in load conditions which occur over several load cycles and contains inherent integrator control action to ...
In this paper, the robust output feedback cruise control for high-speed train movement with uncertain parameters is investigated. The dynamic of a high-speed train is modeled by a cascade of cars connected by flexible couplers, which is subject to rolling mechanical resistance, aerodynamic drag and wind gust. Based on Lyapunov’s stability theory, the sufficient condition for the existence of the robust output feedback cruise control law is given in terms of linear matrix inequalities (LMIs), under which the high-speed train tracks the desired speed, the relative spring displacement between the two neighboring cars is stable at the equilibrium state, and meanwhile a small prescribed H∞ disturbance attenuation level is guaranteed. One numerical example is given to illustrate the effectiveness of the proposed methods. (paper)
Heddebaut, M.; Rioult, J.; GHYS, JP; GRANSART, C; AMBELLOUIS, S
For several years road vehicle autonomous cruise control (ACC) systems as well as anti-collision radar have been developed. Several manufacturers currently sell this equipment. The current generation of ACC sensors only track the first preceding vehicle to deduce its speed and position. These data are then used to compute, manage and optimize a safety distance between vehicles, thus providing some assistance to car drivers. However, in real conditions, to elaborate and update a real time driv...
Goodwin, Graham C
Preface1. Introduction to Adaptive TechniquesPart 1. Deterministic Systems2. Models for Deterministic Dynamical Systems3. Parameter Estimation for Deterministic Systems4. Deterministic Adaptive Prediction5. Control of Linear Deterministic Systems6. Adaptive Control of Linear Deterministic SystemsPart 2. Stochastic Systems7. Optimal Filtering and Prediction8. Parameter Estimation for Stochastic Dynamic Systems9. Adaptive Filtering and Prediction10. Control of Stochastic Systems11. Adaptive Control of Stochastic SystemsAppendicesA. A Brief Review of Some Results from Systems TheoryB. A Summary o
M. N. Ab Malek
Full Text Available For long time the optimization of controller parameters uses the well-known classical method such as the Ziegler-Nichols and the Cohen-Coon tuning techniques. Despite its effectiveness, these off-line tuning techniques can be time consuming especially for a case of complex nonlinear system. This paper attempts to show a great deal on how Metamodeling techniques can be utilized to tune the PID controller parameters quickly. Note that the plant use in this study is the cruise control system with 2 different models, which are the linear model and the nonlinear model. The difference between both models is that the disturbances were taken into consideration for the nonlinear model, but in the linear model the disturbances were assumed as zero. The Radial Basis Function Neural Network Metamodel is able to prove that it can minimize the time in tuning process as it is able to give a good approximation to the optimum controller parameters in both models of this system.
Hoedemaeker, D.M.; Brouwer, R.F.T.; Malone, K.; Klunder, G.; et al.
In this subproject, the impact of Cruise Control (CC) was analysed with respect to traffic safety, energy consumption, and environmental pollution. In order to work on this topic from a European perspective, a team of European experts in the fields of driver assistance systems, human factors, engineering and road safety contributed. The subproject was split up into six workpackages: • WP 3.1: Current policy and practice for CC in the EU Member States • WP 3.2: Level of usage of CC by class of...
Corley, Melissa S.
The Navy is interested in developing systems for horizontal, near ocean surface, high-energy laser propagation through the atmosphere. Laser propagation in the maritime environment requires adaptive optics control of aberrations caused by atmospheric distortion. In this research, a multichannel transverse adaptive filter is formulated in Matlab's Simulink environment and compared to a complex lattice filter that has previously been implemented in large system simulations. The adaptive fil...
McDonough, Kevin K.
The dissertation presents contributions to fuel-efficient control of vehicle speed and constrained control with applications to aircraft. In the first part of this dissertation a stochastic approach to fuel-efficient vehicle speed control is developed. This approach encompasses stochastic modeling of road grade and traffic speed, modeling of fuel consumption through the use of a neural network, and the application of stochastic dynamic programming to generate vehicle speed control policies that are optimized for the trade-off between fuel consumption and travel time. The fuel economy improvements with the proposed policies are quantified through simulations and vehicle experiments. It is shown that the policies lead to the emergence of time-varying vehicle speed patterns that are referred to as time-varying cruise. Through simulations and experiments it is confirmed that these time-varying vehicle speed profiles are more fuel-efficient than driving at a comparable constant speed. Motivated by these results, a simpler implementation strategy that is more appealing for practical implementation is also developed. This strategy relies on a finite state machine and state transition threshold optimization, and its benefits are quantified through model-based simulations and vehicle experiments. Several additional contributions are made to approaches for stochastic modeling of road grade and vehicle speed that include the use of Kullback-Liebler divergence and divergence rate and a stochastic jump-like model for the behavior of the road grade. In the second part of the dissertation, contributions to constrained control with applications to aircraft are described. Recoverable sets and integral safe sets of initial states of constrained closed-loop systems are introduced first and computational procedures of such sets based on linear discrete-time models are given. The use of linear discrete-time models is emphasized as they lead to fast computational procedures. Examples of
ZHU Liye; FANG Yuan; ZHANG Weidong
According to a type of normal nonlinear system, an indirect adaptive fuzzy (IAF) controller has been applied to those systems where no accurate mathematical models of the systems under control are available. To satisfy with system performance, an indirect accelerated adaptive fuzzy (IAAF) controller is proposed, and its general form is presented. The general form IAAF controller ensures necessary control criteria and system's global stability using Lyapunov Theorem. It has been proved that the close-loop system error converges to a small neighborhood of equilibrium point. The optimal IAAF controller is derived to guarantee the process's shortest settling time. Simulation results indicate the IAAF controller make the system more stable, accurate, and fast.
Malik, Abdul Mubeen
Ericsson developed the signal processing methods to be used in the digital power to increase the performance and the functionality of the converter. In the continuation of that the method of identifying the load of the DC/DC converter was developed in this project. The aim was to develop the algorithm that controls and communicate with the DC/DC converter “BMR450”. A current sensing circuit was been made for the voltage measurement in the DC/DC converter across the “inductor” in one part of t...
Nguyen, Nhan T.
In the presence of large uncertainties, a control system needs to be able to adapt rapidly to regain performance. Fast adaptation is referred to the implementation of adaptive control with a large adaptive gain to reduce the tracking error rapidly. However, a large adaptive gain can lead to high-frequency oscillations which can adversely affect robustness of an adaptive control law. A new adaptive control modification is presented that can achieve robust adaptation with a large adaptive gain without incurring high-frequency oscillations as with the standard model-reference adaptive control. The modification is based on the minimization of the Y2 norm of the tracking error, which is formulated as an optimal control problem. The optimality condition is used to derive the modification using the gradient method. The optimal control modification results in a stable adaptation and allows a large adaptive gain to be used for better tracking while providing sufficient stability robustness. Simulations were conducted for a damaged generic transport aircraft with both standard adaptive control and the adaptive optimal control modification technique. The results demonstrate the effectiveness of the proposed modification in tracking a reference model while maintaining a sufficient time delay margin.
Wojcik, W.; Kalita, M; Smolarz, A.
This paper presents research on adaptive control (AC) of combastion process in in¬dustry. Results were obtained from research conducted in laboratory combustion chamber with usage of Fiber Optical Measurement System (FOMS) with electronic block. Simulation proved that implementing AC and FOMS to burning process improves flue gasses parameters -direct measure of power boiler ecologic and economical quality of work.
This book introduces a comprehensive methodology for adaptive control design of parabolic partial differential equations with unknown functional parameters, including reaction-convection-diffusion systems ubiquitous in chemical, thermal, biomedical, aerospace, and energy systems. Andrey Smyshlyaev and Miroslav Krstic develop explicit feedback laws that do not require real-time solution of Riccati or other algebraic operator-valued equations. The book emphasizes stabilization by boundary control and using boundary sensing for unstable PDE systems with an infinite relative degree. The book also
Garipov, Emil; Stoilkov, Teodor; Kalaykov, Ivan
The essence of the ideas applied to this text consists in the development of the strategy for control of the arbitrary in complexity continuous plant by means of a set of discrete timeinvariant linear controllers. Their number and tuned parameters correspond to the number and parameters of the linear time-invariant regressive models in the model bank, which approximate the complex plant dynamics in different operating points. Described strategy is known as Multiple Regressive Model Adaptive C...
Hu, Yonghui; Liang, Jianhong; Wang, Tianmiao
This paper presents mechatronic design and locomotion control of a biomimetic robotic fish that swims using thunniform kinematics for fast cruising. Propulsion of the robotic fish is realized with a parallel four-bar propulsive mechanism that delivers combined translational and rotational motion to a lunate caudal fin. A central pattern generator controller, composed of two unidirectionally coupled Hopf oscillators, is employed to generate robust, smooth and coordinated oscillatory control signals for the tail joints. In order to maintain correct phase relation between joints during fast tail beating, a novel phase adjusting mechanism is proposed and incorporated into the controller. The attitude of the robotic fish in fast swimming is stabilized using an attitude and heading reference system unit and a pair of pitching pectoral fins. The maximum speed of the robotic fish can reach 2.0 m s(-1), which is the fastest speed that robotic fishes have achieved. Its outstanding swimming performance presents possibilities for deployment to real-world exploration, probe and survey missions. PMID:25822708
Baret, Marc; Baillarin, S.; Calesse, C.; Martin, Lionel
In the past few years MATRA and RENAULT have developed an Autonomous Intelligent Cruise Control (AICC) system based on a LIDAR sensor. This sensor incorporating a charge coupled device was designed to acquire pulsed laser diode emission reflected by standard car reflectors. The absence of moving mechanical parts, the large field of view, the high measurement rate and the very good accuracy for distance range and angular position of targets make this sensor very interesting. It provides the equipped car with the distance and the relative speed of other vehicles enabling the safety distance to be controlled by acting on the throttle and the automatic gear box. Experiments in various real traffic situations have shown the limitations of this kind of system especially on bends. All AICC sensors are unable to distinguish between a bend and a change of lane. This is easily understood if we consider a road without lane markings. This fact has led MATRA to improve its AICC system by providing the lane marking information. Also in the scope of the EUREKA PROMETHEUS project, MATRA and RENAULT have developed a lane keeping system in order to warn of the drivers lack of vigilance. Thus, MATRA have spread this system to far field lane marking detection and have coupled it with the AICC system. Experiments will be carried out on roads to estimate the gain in performance and comfort due to this fusion.
Trujillo, Anna C.; Gregory, Irene M.; Hempley, Lucas E.
Adaptive control provides robustness and resilience for highly uncertain, and potentially unpredictable, flight dynamics characteristic. Some of the recent flight experiences of pilot-in-the-loop with an adaptive controller have exhibited unpredicted interactions. In retrospect, this is not surprising once it is realized that there are now two adaptive controllers interacting, the software adaptive control system and the pilot. An experiment was conducted to categorize these interactions on the pilot with an adaptive controller during control surface failures. One of the objectives of this experiment was to determine how the adaptation time of the controller affects pilots. The pitch and roll errors, and stick input increased for increasing adaptation time and during the segment when the adaptive controller was adapting. Not surprisingly, altitude, cross track and angle deviations, and vertical velocity also increase during the failure and then slowly return to pre-failure levels. Subjects may change their behavior even as an adaptive controller is adapting with additional stick inputs. Therefore, the adaptive controller should adapt as fast as possible to minimize flight track errors. This will minimize undesirable interactions between the pilot and the adaptive controller and maintain maneuvering precision.
Kuo, Sen M.; Vijayan, Dipa
Feedforward active noise control (ANC) systems use a reference sensor that senses a reference input to the controller. This signal is assumed to be unaffected by the secondary source and is a good measure of the undesired noise to be cancelled by the system. The reference sensor may be acoustic (e.g., microphone) or non-acoustic (e.g., tachometer, optical transducer). An obvious problem when using acoustic sensors is that the reference signal may be corrupted by the canceling signal generated by the secondary source. This problem is known as acoustic feedback. One way of avoiding this is by using a feedback active noise control (FANC) system which dispenses with the reference sensor. The FANC technique originally proposed by Olson and May employs a high gain negative feedback amplifier. This system suffered from the drawback that the error microphone had to be placed very close to the loudspeaker. The operation of the system was restricted to low frequency range and suffered from instability due to the possibility of positive feedback. Feedback systems employing adaptive filtering techniques for active noise control were developed. This paper presents the FANC system modeled as an adaptive prediction scheme.
. Firstly, it is assumed that the nonlinear processes can be divided into a dynamic linear part and static nonlinear part. Consequently the processes with input nonlinearity and output nonlinearity are treated separately. With the nonlinearity at the input it is easy to set up a model which is linear in...... parameters, and thus directly lends itself to parameter estimation and adaptive control. The extremum control law is derived based on static optimization of a performance function. For a process with nonlinearity at output the intermediate signal between the linear part and nonlinear part plays an important...... measuring device. The investigation of control design is divided into below rated operation and above rated operation. Below ratedpower, the aim of control is to extract maximumenergy from the wind. The pitch angle of the rotor blades is xed at its optimal value and turbine speed is adjusted to follow...
On the simple continuously variable transmission (CVT) driveline model, the design of adaptive fuzzy control system for CVT vehicle is presented. The adaptive fuzzy control system consists of a scaling factor self-tuning fuzzy-PI throttle controller, and a hybrid fuzzy-PID CVT ratio and brake controller. The presented adaptive fuzzy control strategy is vehicle model independent, which depends only on the instantaneous vehicle states, but does not depend on vehicle parameters. So it has good robustness against uncertain vehicle parameters and exogenous load disturbance. Simulation results show that the proposed adaptive fuzzy strategy has good adaptability and practicality value.
Heddebaut, M.; Rioult, J.; Ghys, J. P.; Gransart, Ch; Ambellouis, S.
For several years road vehicle autonomous cruise control (ACC) systems as well as anti-collision radar have been developed. Several manufacturers currently sell this equipment. The current generation of ACC sensors only track the first preceding vehicle to deduce its speed and position. These data are then used to compute, manage and optimize a safety distance between vehicles, thus providing some assistance to car drivers. However, in real conditions, to elaborate and update a real time driving solution, car drivers use information about speed and position of preceding and following vehicles. This information is essentially perceived using the driver's eyes, binocular stereoscopic vision performed through the windscreens and rear-view mirrors. Furthermore, within a line of vehicles, the frontal road perception of the first vehicle is very particular and highly significant. Currently, all these available data remain strictly on-board the vehicle that has captured the perception information and performed these measurements. To get the maximum effectiveness of all these approaches, we propose that this information be shared in real time with the following vehicles, within the convoy. On the basis of these considerations, this paper technically explores a cost-effective solution to extend the basic ACC sensor function in order to simultaneously provide a vehicle-to-vehicle radio link. This millimetre wave radio link transmits relevant broadband perception data (video, localization...) to following vehicles, along the line of vehicles. The propagation path between the vehicles uses essentially grazing angles of incidence of signals over the road surface including millimetre wave paths beneath the cars.
Adaptive fuzzy controllers by means of variable universe are proposed based on interpolation forms of fuzzy control. First, monotonicity of control rules is defined, and it is proved that the monotonicity of interpolation functions of fuzzy control is equivalent to the monotonicity of control rules. This means that there is not any contradiction among the control rules under the condition for the control rules being monotonic. Then structure of the contraction-expansion factor is discussed. At last, three models of adaptive fuzzy control based on variable universe are given which are adaptive fuzzy control model with potential heredity, adaptive fuzzy control model with obvious heredity and adaptive fuzzy control model with successively obvious heredity.
Pavlock, Kate Maureen; Less, James L.; Larson, David Nils
The National Aeronautics and Space Administration s Dryden Flight Research Center completed flight testing of adaptive controls research on a full-scale F-18 testbed. The validation of adaptive controls has the potential to enhance safety in the presence of adverse conditions such as structural damage or control surface failures. This paper describes the research interface architecture, risk mitigations, flight test approach and lessons learned of adaptive controls research.
Brown, S.K.; Baum, C.C.; Bowling, P.S.; Buescher, K.L.; Hanagandi, V.M.; Hinde, R.F. Jr.; Jones, R.D.; Parkinson, W.J.
One can derive a model for use in a Model Predictive Controller (MPC) from first principles or from experimental data. Until recently, both methods failed for all but the simplest processes. First principles are almost always incomplete and fitting to experimental data fails for dimensions greater than one as well as for non-linear cases. Several authors have suggested the use of a neural network to fit the experimental data to a multi-dimensional and/or non-linear model. Most networks, however, use simple sigmoid functions and backpropagation for fitting. Training of these networks generally requires large amounts of data and, consequently, very long training times. In 1993 we reported on the tuning and optimization of a negative ion source using a special neural network. One of the properties of this network (CNLSnet), a modified radial basis function network, is that it is able to fit data with few basis functions. Another is that its training is linear resulting in guaranteed convergence and rapid training. We found the training to be rapid enough to support real-time control. This work has been extended to incorporate this network into an MPC using the model built by the network for predictive control. This controller has shown some remarkable capabilities in such non-linear applications as continuous stirred exothermic tank reactors and high-purity fractional distillation columns. The controller is able not only to build an appropriate model from operating data but also to thin the network continuously so that the model adapts to changing plant conditions. The controller is discussed as well as its possible use in various of the difficult control problems that face this community.
Ni, Y.; Lan, Z.; Gan, D
In this paper a new nonlinear robust adaptive excitation control strategy for multi-machine power systems is presented. The designed controller is adaptive to unknown generator parameters, and robust to model errors or disturbances. It is locally implemented and independent of network topology or load conditions. In the paper the power system model is presented and the control law and adaptive law are derived. The close-loop system stability is proven. Computer test results show clearly that ...
O. F. Opeiko
Full Text Available A synthesis of adaptive PID controller has been executed for flux linkage and speed channels of a vector control system for an induction short-circuited motor. While using an imitation simulation method results of a synthesized system analysis show that the adaptive PID controller has some advantages under conditions of parametric disturbances affecting the object.
Villeneuve d'Ascq: IFAC, 2010, s. 1-6. [12th LSS symposium, Large Scale Systems: Theory and Applications. Villeneuve d'Ascq (FR), 12.07.2010-14.07.2010] R&D Projects: GA MŠk 1M0572; GA ČR GP102/08/P250 Institutional research plan: CEZ:AV0Z10750506 Keywords : decentralized control * LQG control * fully probabilistic design Subject RIV: BC - Control Systems Theory http://library.utia.cas.cz/separaty/2010/AS/smidl-on adaptation of loss functions in decentralized adaptive control .pdf
Adaptive control strategies carry a promise for on-line design of control actions in automation of nuclear power plants and components. Operational reliability analysis of a typical adaptive control algorithm is performed using failure modes and effects analysis. The adaptive controller is susceptible to failure characteristic of the process of model identification involved in the on-line design of the control. Means of failure detection and enhancement of the controller fault tolerance are sought as well as means of placing the controlled process and the plant into a safe state, or termination of the process in case of encountering control failure. Those means are incorporated in a supervisory system to monitor the control system performance, mitigate some of the failure consequences and alert the operator of the state of the plant. Recommendations are given of design improvement to upgrade the adaptive control system performance in nuclear environments. (author)
Cheadle, Samuel; WYART, Valentin; Tsetsos, Konstantinos; Myers, Nicholas; de Gardelle, Vincent; Herce Castañón, Santiago; Summerfield, Christopher
Neural systems adapt to background levels of stimulation. Adaptive gain control has been extensively studied in sensory systems, but overlooked in decision-theoretic models. Here, we describe evidence for adaptive gain control during the serial integration of decision-relevant information. Human observers judged the average information provided by a rapid stream of visual events (samples). The impact that each sample wielded over choices depended on its consistency with the previous sample, w...
In this paper, we present an adaptive, stable fuzzy controller whose parameters are optimized via a genetic algorithm. The controller model is capable of building itself on the basis of measured plant data and then of adapting to new dynamics. The stability of the overall system, made up of the plant and the controller, is guaranteed by Lyapunov's theory. As a case study, the stable adaptive fuzzy controller is employed to drive the narrow water level of a simulated Steam Generator (SG) to a desired reference trajectory. The numerical results confirm that the controller bears good performances in terms of small oscillations and fast settling time even in presence of external disturbances. (authors)
Full Text Available The paper presents an adaptive method using the controlled grid deformation over an elastic, isotropic and continuous domain. The adaptive process is controlled with the principal strains and principal strain directions and uses the finite elements method. Numerical results are presented for several test cases.
Wei, Sun; Lujin, Zhang; Jinhai, Zou; Siyi, Miao
In this paper, the adaptive control based on neural network is studied. Firstly, a neural network based adaptive robust tracking control design is proposed for robotic systems under the existence of uncertainties. In this proposed control strategy, the NN is used to identify the modeling uncertainties, and then the disadvantageous effects caused by neural network approximating error and external disturbances in robotic system are counteracted by robust controller. Especially the proposed cont...
Šteblaj, Peter; Čudina, Mirko; Lipar, Primož; Prezelj, Jurij
An adaptive muffler with a flexible internal structure is considered. Flexibility is achieved using controlled flow valves. The proposed adaptive muffler is able to adapt to changes in engine operating conditions. It consists of a Helmholtz resonator, expansion chamber, and quarter wavelength resonator. Different combinations of the control valves' states at different operating conditions define the main working principle. To control the valve's position, an active noise control approach was used. With the proposed muffler, the transmission loss can be increased by more than 10 dB in the selected frequency range. PMID:26093462
Pavlock, Kate Maureen; Less, James L.; Larson, David Nils
The National Aeronautics and Space Administration's Dryden Flight Research Center completed flight testing of adaptive controls research on a full-scale F-18 testbed. The testbed served as a full-scale vehicle to test and validate adaptive flight control research addressing technical challenges involved with reducing risk to enable safe flight in the presence of adverse conditions such as structural damage or control surface failures. This paper describes the research interface architecture, risk mitigations, flight test approach and lessons learned of adaptive controls research.
Efficient removal of sulfur is important in the operation of a gas processing plant. Control of the sulfur recovery unit (SRU) is difficult using conventional controllers due to variations in gas composition and time delays within the recovery process itself. Adaptive controllers are well-suited to the problem of handling lengthy and varying process time delays. Adaptive controllers use a mathematical model of the process, including time delay, to forecast a process response. A new approach to adaptive control is presented which uses orthogonal functions to model the process. The transfer function required for implementing the controller can then be identified using a minimum of historical process information. The controller can do this while it controls the process, automatically adapting to changes in gain, time constants, or time delay in order to maintain optimal control. The sulfur recovery process is explained and test results are presented showing the performance of the new adaptive controller compared to the performance of a conventional controller in recovering sulfur and reducing SO2 emissions. The adaptive controller had a 38% lower standard deviation and the improved tail gas ratio control alone is estimated to have resulted in a 0.4% increase in sulfur recovery efficiency. Using the adaptive controller on other stages of the plant could raise the total improvement to 0.6-0.7%. Additional benefits of using the new controller include increased production, avoidance of major capital and operating expense to achieve increases in recovery efficiency, avoidance of penalties for exceeding sulfur emission limits, and extension of catalyst bed life. 3 refs., 8 figs., 2 tabs
WANG Yi-jing; WANG Long
The problem of adaptive generalized predictive control which consists of output prediction errors for a class of switched systems is studied. The switching law is determined by the output predictive errors of a finite number of subsystems. For the single subsystem and multiple subsystems cases, it is proved that the given direct algorithm of generalized predictive control guarantees the global convergence of the system. This algorithm overcomes the inherent drawbacks of the slow convergence and large transient errors for the conventional adaptive control.
Precise knowledge of dynamics not required. Proposed scheme for control of multijointed robotic manipulator calls for independent control subsystem for each joint, consisting of proportional/integral/derivative feedback controller and position/velocity/acceleration feedforward controller, both with adjustable gains. Independent joint controller compensates for unpredictable effects, gravitation, and dynamic coupling between motions of joints, while forcing joints to track reference trajectories. Scheme amenable to parallel processing in distributed computing system wherein each joint controlled by relatively simple algorithm on dedicated microprocessor.
Hartmann, G. L.; Stein, G.
Honeywell has designed a digital self-adaptive flight control system for flight test in the VALT Research Aircraft (a modified CH-47). The final design resulted from a comparison of two different adaptive concepts: one based on explicit parameter estimates from a real-time maximum likelihood estimation algorithm and the other based on an implicit model reference adaptive system. The two designs are compared on the basis of performance and complexity.
We consider one of the fundamental limitations of indirect adaptive control based on the minimization of a quadratic cost criterion and the certainty equivalence principle. We show that the interaction between (closed-loop) identification and optimal control is conflictive in the sense that almost all possible limits of the sequence of parameter estimates induce suboptimal behavior of the adaptively controlled system.
A decentralized model reference adaptive scheme is developed for digital control of robot manipulators. The adaptation laws are derived using hyperstability theory, which guarantees asymptotic trajectory tracking despite gross robot parameter variations. The control scheme has a decentralized structure in the sense that each local controller receives only its joint angle measurement to produce its joint torque. The independent joint controllers have simple structures and can be programmed using a very simple and computationally fast algorithm. As a result, the scheme is suitable for real-time motion control.
National Aeronautics and Space Administration — An Adaptive Feedforward and Feedback Control (AFFC) Framework is proposed to suppress the aircraft's structural vibrations and to increase the resilience of the...
Šindelář, Jan; Kárný, Miroslav
Strasbourg cedex: European Science Foundation, 2007, s. 1-6. [Advanced Mathematical Methods for Finance. Vídeň (AT), 17.09.2007-22.09.2007] R&D Projects: GA MŠk(CZ) 2C06001 Institutional research plan: CEZ:AV0Z10750506 Keywords : bayesian statistics * portfolio optimization * finance * adaptive control Subject RIV: BB - Applied Statistics, Operational Research http://library.utia.cas.cz/separaty/2007/si/sindelar-adaptive control applied to financial market data.pdf
Landau, Ioan; Lozano, Rogelio; M'Saad, Mohammed; Karimi, Alireza
Adaptive Control (second edition) shows how a desired level of system performance can be maintained automatically and in real time, even when process or disturbance parameters are unknown and variable. It is a coherent exposition of the many aspects of this field, setting out the problems to be addressed and moving on to solutions, their practical significance and their application. Discrete-time aspects of adaptive control are emphasized to reflect the importance of digital computers in the ...
Bobtsov, Alexey; Faronov, Maxim; Kolyubin, Sergey; Pyrkin, Anton
The problem of simple adaptive and robust control is studied for the case of parametric and dynamic dimension uncertainties: only the maximum possible relative degree of the plant model is known. The control approach "consecutive compensator" is investigated. To illustrate the efficiency of proposed approach an example with the mobile robot motion control using computer vision system is considered.
Battistelli, Giorgio; Mari, Daniele; Selvi, Daniela; Tesi, Alberto; Tesi, Pietro
The problem of adaptive disturbance attenuation is addressed in this paper using a switching control approach. A finite family of stabilizing controllers is pre-designed, with the assumption that, for any possible operating condition, at least one controller is able to achieve a prescribed level of
Schmidt, Lasse; Andersen, Torben Ole; Pedersen, Henrik C.;
This paper presents a new adaptive sliding mode controller generally applicable for position tracking control of electro-hydraulic valve-cylinder drives (VCD’s). The proposed control scheme requires limited knowledge on system parameters, and employs only piston- and valve spool position feedback...
Wang Xin; Li Shaoyuan; Wang Zhongjie
When the parameters of the system change abruptly, a new multivariable adaptive feedforward decoupling controller using multiple models is presented to improve the transient response. The system models are composed of multiple fixed models, one free-running adaptive model and one re-initialized adaptive model. The fixed models are used to provide initial control to the process. The re-initialized adaptive model can be reinitialized as the selected model to improve the adaptation speed. The free-running adaptive controller is added to guarantee the overall system stability. At each instant, the best system model is selected according to the switching index and the corresponding controller is designed. During the controller design, the interaction is viewed as the measurable disturbance and eliminated by the choice of the weighting polynomial matrix. It not only eliminates the steady-state error but also decouples the system dynamically. The global convergence is obtained and several simulation examples are presented to illustrate the effectiveness of the proposed controller.
Karr, C. Lucas; Harper, Tony R.
Researchers at the U.S. Bureau of Mines have developed adaptive process control systems in which genetic algorithms (GA's) are used to augment fuzzy logic controllers (FLC's). GA's are search algorithms that rapidly locate near-optimum solutions to a wide spectrum of problems by modeling the search procedures of natural genetics. FLC's are rule based systems that efficiently manipulate a problem environment by modeling the 'rule-of-thumb' strategy used in human decision making. Together, GA's and FLC's possess the capabilities necessary to produce powerful, efficient, and robust adaptive control systems. To perform efficiently, such control systems require a control element to manipulate the problem environment, an analysis element to recognize changes in the problem environment, and a learning element to adjust fuzzy membership functions in response to the changes in the problem environment. Details of an overall adaptive control system are discussed. A specific computer-simulated chemical system is used to demonstrate the ideas presented.
Nguyen, Nhan T.; Krishnakumar, Kalmanje; Boskovic, Jovan
This paper presents a method that can achieve fast adaptation for a class of model-reference adaptive control. It is well-known that standard model-reference adaptive control exhibits high-gain control behaviors when a large adaptive gain is used to achieve fast adaptation in order to reduce tracking error rapidly. High gain control creates high-frequency oscillations that can excite unmodeled dynamics and can lead to instability. The fast adaptation approach is based on the minimization of the squares of the tracking error, which is formulated as an optimal control problem. The necessary condition of optimality is used to derive an adaptive law using the gradient method. This adaptive law is shown to result in uniform boundedness of the tracking error by means of the Lyapunov s direct method. Furthermore, this adaptive law allows a large adaptive gain to be used without causing undesired high-gain control effects. The method is shown to be more robust than standard model-reference adaptive control. Simulations demonstrate the effectiveness of the proposed method.
Bialasiewicz, Jan T.
The control problem of a flexible robotic arm has been investigated. The control strategies that have been developed have a wide application in approaching the general control problem of flexible space structures. The following control strategies have been developed and evaluated: neural self-tuning control algorithm, neural-network-based fuzzy logic control algorithm, and adaptive pole assignment algorithm. All of the above algorithms have been tested through computer simulation. In addition, the hardware implementation of a computer control system that controls the tip position of a flexible arm clamped on a rigid hub mounted directly on the vertical shaft of a dc motor, has been developed. An adaptive pole assignment algorithm has been applied to suppress vibrations of the described physical model of flexible robotic arm and has been successfully tested using this testbed.
Butler, H.; Honderd, G.; Amerongen, van, W.E.
This paper introduces the method of reference model decomposition as a way to improve the robustness of model reference adaptive control systems (MRACs) with respect to unmodelled dynamics with a known structure. Such unmodelled dynamics occur when some of the nominal plant dynamics are purposely neglected in the controller design with the aim of keeping the controller order low. One of the effects of such undermodelling of the controller is a violation of the perfect model-matching condition...
Cheadle, Samuel; Wyart, Valentin; Tsetsos, Konstantinos; Myers, Nicholas; de Gardelle, Vincent; Castañón, Santiago Herce; Summerfield, Christopher
Neural systems adapt to background levels of stimulation. Adaptive gain control has been extensively studied in sensory systems, but overlooked in decision-theoretic models. Here, we describe evidence for adaptive gain control during the serial integration of decision-relevant information. Human observers judged the average information provided by a rapid stream of visual events (samples). The impact that each sample wielded over choices depended on its consistency with the previous sample, with more consistent or expected samples wielding the greatest influence over choice. This bias was also visible in the encoding of decision information in pupillometric signals, and in cortical responses measured with functional neuroimaging. These data can be accounted for with a new serial sampling model in which the gain of information processing adapts rapidly to reflect the average of the available evidence. PMID:24656259
Udink ten Cate, A.J.
The material presented in this thesis can be grouped around four themes, system concepts, modeling, control and adaptive control. In this summary these themes will be treated separately.System conceptsIn Chapters 1 and 2 an overview of the problem formulation is presented. It is suggested that there
The problem of direct adaptive neural network control for a class of uncertain nonlinear systems with unknown constant control gain is studied in this paper. Based on the supervisory control strategy and the approximation capability of multilayer neural networks (MNNs), a novel design scheme of direct adaptive neural network controller is proposed.The adaptive law of the adjustable parameter vector and the matrix of weights in the neural networks and the gain of sliding mode control term to adaptively compensate for the residual and the approximation error of MNNs is determined by using a Lyapunov method. The approach does not require the optimal approximation error to be square-integrable or the supremum of the optimal approximation error to be known. By theoretical analysis, the closed-loop control system is proven to be globally stable in the sense that all signals involved are bounded, with tracking error converging to zero.Simulation results demonstrate the effectiveness of the approach.
Tzou, H.S.; Bao, Y.
Adaptive structures with controllable geometries and shapes are rather useful in many engineering applications, such as adaptive wings, variable focus mirrors, adaptive machines, micro-electromechanical systems, etc. Dynamics and feedback control effectiveness of adaptive shells whose curvatures are actively controlled and continuously changed are evaluated. An adaptive piezoelectric laminated cylindrical shell composite with continuous curvature changes is studied, and its natural frequencie...
Demirci, R. [Abant Izzet Baysal Univ., Technical Education Faculty, Electrical Dept., Dunez (Turkey); Dursun, M. [Gazi University, Technical Education Faculty, Electrical Dept., Ankara (Turkey)
An adaptive position controller has been proposed for double armature brushless DC linear motor. The proposed position control system comprises an inner model reference adaptive velocity control loop and an outer position control loop. The parameters of the adaptive controller have been adjusted by using modified gradient type parameter adaptation algorithm. (orig.)
An approach is developed for the evaluation of the reliability of logic of adaptive control strategies, taking into account logic structural complexity and potential failure of programming modules. Flaws in the control system algorithm may not be discovered during debugging or initial testing and may only affect the performance under abnormal situations although the system may appear reliable in normal operations. Considering an adaptive control system designed for use in control of equipment employed in nuclear power stations, logic reliability evaluation is demonstrated. The approach given is applicable to any other designs and may be used to compare different control system logic structures from the reliability viewpoint. Evaluation of the reliability of control systems is essential to automated operation of equipment used in nuclear power plants. (author)
Couceiro, Micael S.; Ferreira, Nuno M. F.; Machado, J. A. Tenreiro
Dragonflies show unique and superior flight performances than most of other insect species and birds. They are equipped with two pairs of independently controlled wings granting an unmatchable flying performance and robustness. In this paper, it is presented an adaptive scheme controlling a nonlinear model inspired in a dragonfly-like robot. It is proposed a hybrid adaptive ( HA) law for adjusting the parameters analyzing the tracking error. At the current stage of the project it is considered essential the development of computational simulation models based in the dynamics to test whether strategies or algorithms of control, parts of the system (such as different wing configurations, tail) as well as the complete system. The performance analysis proves the superiority of the HA law over the direct adaptive ( DA) method in terms of faster and improved tracking and parameter convergence.
Full Text Available Passive vibration control solutions are often limited to working reliably at one design point. Especially applied to lightweight structures, which tend to have unwanted vibration, active vibration control approaches can outperform passive solutions. To generate dynamic forces in a narrow frequency band, passive single-degree-of-freedom oscillators are frequently used as vibration absorbers and neutralizers. In order to respond to changes in system properties and/or the frequency of excitation forces, in this work, adaptive vibration compensation by a tunable piezoelectric vibration absorber is investigated. A special design containing piezoelectric stack actuators is used to cover a large tuning range for the natural frequency of the adaptive vibration absorber, while also the utilization as an active dynamic inertial mass actuator for active control concepts is possible, which can help to implement a broadband vibration control system. An analytical model is set up to derive general design rules for the system. An absorber prototype is set up and validated experimentally for both use cases of an adaptive vibration absorber and inertial mass actuator. Finally, the adaptive vibration control system is installed and tested with a basic truss structure in the laboratory, using both the possibility to adjust the properties of the absorber and active control.
Kjems, Erik; Bolet, Lars; Agerholm, Niels; Plausinaitis, Darius
This study uses theoretical considerations along with computer simulation and driving experiments on a road section to evaluate the possibilities of defining an energy-efficient speed adaptation strategy. The goal of the overall study is to include various external parameters not only the alignme...... works and a field experiment using a small vehicle with automatic transmission. The experiment showed promising results....
Akira Inoue; Ming-Cong Deng
This paper presents a framework of a combined adaptive and non-adaptive attitude control system for a helicopter experimental system. The design method is based on a combination of adaptive nonlinear control and non-adaptive nonlinear control. With regard to detailed attitude control system design, two schemes are shown for different application cases.
Lemos, João M; Igreja, José M
This book describes methods for adaptive control of distributed-collector solar fields: plants that collect solar energy and deliver it in thermal form. Controller design methods are presented that can overcome difficulties found in these type of plants:they are distributed-parameter systems, i.e., systems with dynamics that depend on space as well as time;their dynamics is nonlinear, with a bilinear structure;there is a significant level of uncertainty in plant knowledge.Adaptive methods form the focus of the text because of the degree of uncertainty in the knowledge of plant dynamics. Parts
Full Text Available Most of existing adaptive control schemes are designed to minimize error between plant state and goal state despite the fact that executing actions that are predicted to result in smaller errors only can mislead to non-goal states. We develop an adaptive control scheme that involves manipulating a controller of a general type to improve its performance as measured by an evaluation function. The developed method is closely related to a theory of Reinforcement Learning (RL but imposes a practical assumption made for faster learning. We assume that a value function of RL can be approximated by a function of Euclidean distance from a goal state and an action executed at the state. And, we propose to use it for the gradient search as an evaluation function. Simulation results provided through application of the proposed scheme to a pole-balancing problem using a linear state feedback controller and fuzzy controller verify the scheme’s efficacy.
Thor I. Fossen
Full Text Available The problem of controlling underwater mobile robots in 6 degrees of freedom (DOF is addressed. Uncertainties in the input matrix due to partly known nonlinear thruster characteristics are modeled as multiplicative input uncertainty. This paper proposes two methods to compensate for the model uncertainties: (1 an adaptive passivity-based control scheme and (2 deriving a hybrid (adaptive and sliding controller. The hybrid controller consists of a switching term which compensates for uncertainties in the input matrix and an on-line parameter estimation algorithm. Global stability is ensured by applying Barbalat's Lyapunovlike lemma. The hybrid controller is simulated for the horizontal motion of the Norwegian Experimental Remotely Operated Vehicle (NEROV.
Frost, Susan A.; Balas, Mark J.
We propose a new framework called Evolving Systems to describe the self-assembly, or autonomous assembly, of actively controlled dynamical subsystems into an Evolved System with a higher purpose. An introduction to Evolving Systems and exploration of the essential topics of the control and stability properties of Evolving Systems is provided. This chapter defines a framework for Evolving Systems, develops theory and control solutions for fundamental characteristics of Evolving Systems, and provides illustrative examples of Evolving Systems and their control with adaptive key component controllers.
Variations in systems dynamics and modeling uncertainty(due to unmodeled systems behavior and/or presence of disturbances),have posed significant challenges to the effective luminosity and orbit control in accelerators.Problems of similar nature occur in a wide variety of other applications from chemical processes to power plants to financial systems.Adaptive control has long been pursued as a possible solution,but difficulties with online model identification and robust implementation of the adaptive control algorithms has prevented their widespread application.In general developing and maintaining appropriate models is the key to the success of any deployed control solution.Meanwhile the performance of the control system is contingent on the responsiveness of the control algorithm to the inevitable deviations of the model from the actual system.This project uses neural networks to detect significant changes in system behavior,and develops an optimal model-predictive-based adaptive control algorithm that enables the robust implementation of an effective control strategy that is applicable in a wide range of applications.Simulation studies were conducted to clearly demonstrate the feasibility and benefits of implementing model predictive control technology in accelerator control problems.The requirements for an effective commercial product that can meet the challenge of optimal model-predictive-based adaptive control technology were developed.A prototype for the optimal model-predictive-based adaptive control algorithm was developed for a well-known nonlinear temperature control problem for gas-phase reactors that proved the feasibility of the proposed approach.This research enables a commercial party to leverage the knowledge gained through collaboration with a national laboratory to develop new system identification and optimal model-predictive-based adaptive control software to address current and future challenges in process industries,power systems
For discrete-time nonlinear stochastic systems with unknown nonparametric structure, a kernel estimation-based nonparametric adaptive controller is constructed based on truncated certainty equivalence principle. Global stability and asymptotic optimality of the closed-loop systems are established without resorting to any external excitations.
Optimal adaptive automatic control system for gas producing wells cluster is proposed intended for solving the problem of stabilization of the output gas pressure in the cluster at conditions of changing gas flow rate and changing parameters of the wells themselves, providing the maximum high resource of hardware elements of automation
This work addresses the control allocation problem for a nonlinear over-actuated time-varying system where parameters a¢ ne in the actuator dynamics and actuator force model may be assumed unknown. Instead of optimizing the control allocation at each time instant, a dynamic approach is considered by constructing update-laws that represent asymptotically optimal allocation search and adaptation. A previous result on uniform global asymptotic stability (UGAS) of the equilibrium of cascaded time...
Robust and Adaptive Control shows the reader how to produce consistent and accurate controllers that operate in the presence of uncertainties and unforeseen events. Driven by aerospace applications the focus of the book is primarily on continuous-dynamical systems. The text is a three-part treatment, beginning with robust and optimal linear control methods and moving on to a self-contained presentation of the design and analysis of model reference adaptive control (MRAC) for nonlinear uncertain dynamical systems. Recent extensions and modifications to MRAC design are included, as are guidelines for combining robust optimal and MRAC controllers. Features of the text include: · case studies that demonstrate the benefits of robust and adaptive control for piloted, autonomous and experimental aerial platforms; · detailed background material for each chapter to motivate theoretical developments; · realistic examples and simulation data illustrating key features ...
Said G. Khan
Full Text Available In this study, a partially model based adaptive control of humanoid robot arm is presented. The aim of the adaptive control scheme is to deal with the uncertain parameters in its own dynamic model such as link masses or actuators inertias as well as to cope with changing dynamics in the tasks like passing objects between a human and a robot. The main idea here is to derive a dynamic model of the robot’s arm via a software package and parameterized it. Then, employ the adaptive control scheme to identify uncertain parameters such as link masses and actuator inertias online. This scheme will also be suitable for the tasks where robot is lifting weight and or passing an object to a human or vice versa (which is the ultimate goal of this work. The adaptive scheme is simulated and experimentally tested on the Bristol Robotics Laboratory humanoid Bristol- Elumotion-Robot-Torso (BERT Arm. Humanoid BERT robot is developed as a collaboration between Bristol Robotics Laboratory and Elumotion (a Bristol based robotic company.
Kloiber, Bernhard; Strang, Thomas; de Ponte Müller, Fabian
The Electric Vehicle is seen to be one of the most important enablers for a more environmentally friendly mobility of people. Unfortunately, state of the art electric vehicles suffer from a series of problems, with facing a very limited traveling distance compared to gasoline vehicles being one of the most relevant ones. In this paper we present an approach how to reduce the energy consumption while traveling over longer distances by using the slipstream effect behind a vehicle ahead. We show...
Full Text Available An adaptive control scheme for mobile slotted ALOHA is presented and the effect of capture on the adaptive control scheme is investigated. It is shown that with the proper choice of adaptation parameters the adaptive control scheme can be made independent of the effect of capture.
Park, K. C.; Alvin, Kenneth F.; Belvin, W. Keith; Chong, K. P. (Editor); Liu, S. C. (Editor); Li, J. C. (Editor)
The equations of motion for structures with adaptive elements for vibration control are presented for parallel computations to be used as a software package for real-time control of flexible space structures. A brief introduction of the state-of-the-art parallel computational capability is also presented. Time marching strategies are developed for an effective use of massive parallel mapping, partitioning, and the necessary arithmetic operations. An example is offered for the simulation of control-structure interaction on a parallel computer and the impact of the approach presented for applications in other disciplines than aerospace industry is assessed.
Hogema, J.H.; Janssen, W.H.
In een simulatorexperiment is gebleken dat Intelligent Cruisse Control (ICC) resulteert in een vermindering van korte volgtijden en een iets lagere snelheidskeuze in kritische situaties was er met ICC sprake van een iets tragere reactie.
Jie LUO; Chengyu CAO
This paper presents an adaptive control scheme with an integration of sliding mode control into the L1 adaptive control architecture, which provides good tracking performance as well as robustness against matched uncertainties. Sliding mode control is used as an adaptive law in the L1 adaptive control architecture, which is considered as a virtual control of error dynamics between estimated states and real states. Low-pass filtering mechanism in the control law design prevents a discontinuous signal in the adaptive law from appearing in actual control signal while maintaining control accuracy. By using sliding mode control as a virtual control of error dynamics and introducing the low-pass filtered control signal, the chattering effect is eliminated. The performance bounds between the close-loop adaptive system and the closed-loop reference system are characterized in this paper. Numerical simulation is provided to demonstrate the performance of the presented adaptive control scheme.
Santillo, Mario A. (Inventor); Bernstein, Dennis S. (Inventor)
A discrete-time adaptive control law for stabilization, command following, and disturbance rejection that is effective for systems that are unstable, MIMO, and/or nonminimum phase. The adaptive control algorithm includes guidelines concerning the modeling information needed for implementation. This information includes the relative degree, the first nonzero Markov parameter, and the nonminimum-phase zeros. Except when the plant has nonminimum-phase zeros whose absolute value is less than the plant's spectral radius, the required zero information can be approximated by a sufficient number of Markov parameters. No additional information about the poles or zeros need be known. Numerical examples are presented to illustrate the algorithm's effectiveness in handling systems with errors in the required modeling data, unknown latency, sensor noise, and saturation.
In order to reduce output-voltage ripple of power supply, an active filter is necessary. In this paper, the active filter with DSP is proposed. The waveform from active filter can be flexibly improved by DSP programming. The output-voltage ripple can be enough reduced by mixing frequency components of the input-voltage ripple. The result of adaptive control using LMS algorism is presented. The improvement by using filtered-X method is discussed. (author)
Full Text Available In this study, the problem of Fault-Tolerant Control (FTC for a class of uncertain nonlinear systems is studied. A novel FTC scheme is proposed to deal with both lock-in-place and loss of effectiveness faults of actuators. By employing fuzzy approximation and on-line adaptive updating, the proposed control scheme can tolerate the faults without detection and diagnosis mechanism. It is proved in theory that the FTC scheme can guarantee the closed-loop stability and desired output tracking performance in spite of all kinds of the faults and external disturbances. A simulation example is also included to show the effectiveness of the scheme.
Full Text Available Abstract. This paper deals with adaptive regulation of a discrete-time linear time-invariant plant witharbitrary bounded disturbances whose control input is constrained to lie within certain limits. The adaptivecontrol algorithm exploits the one-step-ahead control strategy and the gradient projection type estimationprocedure using the modified dead zone. The convergence property of the estimation algorithm is shown tobe ensured. The sufficient conditions guaranteeing the global asymptotical stability and simultaneously thesuboptimality of the closed-loop systems are derived. Numerical examples and simulations are presented tosupport the theoretical results.
Šindelář, Jan; Kárný, Miroslav
Vol. I. Praha : Matfyz press, 2007, s. 1-6. ISBN 978-80-7378-023-4. [Week of Doctoral Students 2007. Praha (CZ), 05.06.2007-08.06.2007] R&D Projects: GA MŠk(CZ) 2C06001 Institutional research plan: CEZ:AV0Z10750506 Keywords : baysian statistics * finance * financial engineering * stochastic control Subject RIV: BB - Applied Statistics, Operational Research http://library.utia.cas.cz/separaty/2007/si/sindelar-adaptive control applied to financial market data.pdf
Full Text Available Problem statement: Research into robot motion control offers research opportunities that will change scientists and engineers for year to come. Autonomous robots are increasingly evident in many aspects of industry and everyday life and a robust robot motion control can be used for homeland security and many consumer applications. This study discussed the adaptive fuzzy knowledge based controller for robot motion control in indoor and outdoor environment. Approach: The proposed method consisted of two components: the process monitor that detects changes in the process characteristics and the adaptation mechanism that used information passed to it by the process monitor to update the controller parameters. Results: Experimental evaluation had been done in both indoor and outdoor environment where the robot communicates with the base station through its Wireless fidelity antenna and the performance monitor used a set of five performance criteria to access the fuzzy knowledge based controller. Conclusion: The proposed method had been found to be robust.
In light of the complex and highly uncertain nature of dynamical systems requiring controls, it is not surprising that reliable system models for many high performance engineering and life science applications are unavailable. In the face of such high levels of system uncertainty, robust controllers may unnecessarily sacrifice system performance whereas adaptive controllers are clearly appropriate since they can tolerate far greater system uncertainty levels to improve system performance. In this dissertation, we develop a Lyapunov-based direct adaptive and neural adaptive control framework that addresses parametric uncertainty, unstructured uncertainty, disturbance rejection, amplitude and rate saturation constraints, and digital implementation issues. Specifically, we consider the following research topics; direct adaptive control for nonlinear uncertain systems with exogenous disturbances; robust adaptive control for nonlinear uncertain systems; adaptive control for nonlinear uncertain systems with actuator amplitude and rate saturation constraints; adaptive reduced-order dynamic compensation for nonlinear uncertain systems; direct adaptive control for nonlinear matrix second-order dynamical systems with state-dependent uncertainty; adaptive control for nonnegative and compartmental dynamical systems with applications to general anesthesia; direct adaptive control of nonnegative and compartmental dynamical systems with time delay; adaptive control for nonlinear nonnegative and compartmental dynamical systems with applications to clinical pharmacology; neural network adaptive control for nonlinear nonnegative dynamical systems; passivity-based neural network adaptive output feedback control for nonlinear nonnegative dynamical systems; neural network adaptive dynamic output feedback control for nonlinear nonnegative systems using tapped delay memory units; Lyapunov-based adaptive control framework for discrete-time nonlinear systems with exogenous disturbances
Fossen, Thor I.
In the adaptive scheme presented by Slotine and Benedetto (1990) for attitude tracking control of rigid spacecraft, the spacecraft is parameterized in terms of the inertial frame. This note shows how a parameterization in body coordinates considerably simplifies the representation of the adaptation scheme. The new symbolic expression for the regressor matrix is easy to find even for 6-degrees of freedom (DOF) Hamiltonian systems with a large number of unknown parameters. If the symbolic expression for the regressor matrix is known in advance, the computational complexity is approximately equal for both representations. In the scheme presented by Slotine and Benedetto this is not trivial because the transformation matrix between the inertial frame and the body coordinates is included in the expression for the regressor matrix. Hence, implementation for higher DOF systems is strongly complicated. An example illustrates the advantage of the new representation when modeling a simple three-DOF model of the lateral motion of a space shuttle.
Kahveci, Nazli E.
The objective of meeting higher endurance requirements remains a challenging task for any type and size of Unmanned Aerial Vehicles (UAVs). According to recent research studies significant energy savings can be realized through utilization of thermal currents. The navigation strategies followed across thermal regions, however, are based on rather intuitive assessments of remote pilots and lack any systematic path planning approaches. Various methods to enhance the autonomy of UAVs in soaring applications are investigated while seeking guarantees for flight performance improvements. The dynamics of the aircraft, small UAVs in particular, are affected by the environmental conditions, whereas unmodeled dynamics possibly become significant during aggressive flight maneuvers. Besides, the demanded control inputs might have a magnitude range beyond the limits dictated by the control surface actuators. The consequences of ignoring these issues can be catastrophic. Supporting this claim NASA Dryden Flight Research Center reports considerable performance degradation and even loss of stability in autonomous soaring flight tests with the subsequent risk of an aircraft crash. The existing control schemes are concluded to suffer from limited performance. Considering the aircraft dynamics and the thermal characteristics we define a vehicle-specific trajectory optimization problem to achieve increased cross-country speed and extended range of flight. In an environment with geographically dispersed set of thermals of possibly limited lifespan, we identify the similarities to the Vehicle Routing Problem (VRP) and provide both exact and approximate guidance algorithms for the navigation of automated UAVs. An additional stochastic approach is used to quantify the performance losses due to incorrect thermal data while dealing with random gust disturbances and onboard sensor measurement inaccuracies. One of the main contributions of this research is a novel adaptive control design with
D M Shenoy; M Dileep Kumar; V V S S Sarma
The air-sea exchange is one of the main mechanisms maintaining the abundances of trace gases in the atmosphere. Some of these, such as carbon dioxide and dimethyl sulphide (DMS), will have a bearing on the atmospheric heat budget. While the former facilitates the trapping of radiation (greenhouse effect) the latter works in the opposite direction through reflectance of radiation back into space by sulphate aerosols that form from oxidation of DMS in atmosphere. Here we report on the first measurements made on DMS in the Bay of Bengal and the factors regulating its abundance in seawater. Phytoplankton alone does not seem to control the extent of DMS concentrations. We find that changes in salinity could effectively regulate the extent of DMSP production by marine phytoplankton. In addition, we provide the first ever evidence to the occurrence of DMS precursor, DMSP, in marine aerosols collected in the boundary layer. This suggests that the marine aerosol transport of DMSP will supplement DMS gaseous evasion in maintaining the atmospheric non-sea salt sulphur budget.
Shi Yingjing; Ma Guangfu; Ma Hongzhong
A global controller design methodology for a flight stage of the cruise missile is proposed.This methodology is based on the method of least squares.To prove robust stability in the full airspace with parameter disturbances.the Concepts of Convex polytopic models and quadratic stability are introduced.The effect of aerodynamic parameters on system performance is analyzed.The designed controller is applied to track the over loading signal of the cruise segment of the cruise missile,avoiding system disturbance owing to controller switching.Simulation results demonstrate the validity of the proposed method.
Corneliu Andrei NAE
Full Text Available The paper presents an approach towards the control of a supersonic blowdown wind tunnel plant (as evidenced by experimental data collected from “INCAS Supersonic Blowdown Wind Tunnel” using a PI type controller. The key to maintain the imposed experimental conditions is the control of the air flow using the control valve of the plant. A proposed mathematical model based on the control valve will be analyzed using the PI controller. This control scheme will be validated using experimental data collected from real test cases. In order to improve the control performances an adaptive fuzzy PI controller will be implemented in SIMULINK in the present paper. The major objective is to reduce the transient regimes and the global reduction of the start-up loads on the models during this phase.
Gómez, E.; A. S. Poznyak; Lozano, R, R.
Existen en la literatura de Control Adaptable, diferentes procedimientos en los que es posible identificar un sistema lineal. El problema fundamental es que una cantidad importante de fenómenos de la vida real son de tipo no lineal y no es tan sencillo el modelar este tipo de dinámicas. En este trabajo se presenta una forma de identificar sistemas no lineales utilizando las propiedades de las Redes Neuronales Artificiales y las técnicas de Algoritmo Genético en la optimización de ...
Frost, Susan A.; Balas, Mark J.
Many dynamic systems containing a large number of modes can benefit from adaptive control techniques, which are well suited to applications that have unknown parameters and poorly known operating conditions. In this paper, we focus on a model reference direct adaptive control approach that has been extended to handle adaptive rejection of persistent disturbances. We extend this adaptive control theory to accommodate problematic modal subsystems of a plant that inhibit the adaptive controller by causing the open-loop plant to be non-minimum phase. We will augment the adaptive controller using a Residual Mode Filter (RMF) to compensate for problematic modal subsystems, thereby allowing the system to satisfy the requirements for the adaptive controller to have guaranteed convergence and bounded gains. We apply these theoretical results to design an adaptive collective pitch controller for a high-fidelity simulation of a utility-scale, variable-speed wind turbine that has minimum phase zeros.
Selinger, Jessica C; Donelan, J Maxwell
We have designed and tested a myoelectric controller that automatically adapts energy harvesting from the motion of leg joints to match the power available in different walking conditions. To assist muscles in performing negative mechanical work, the controller engages power generation only when estimated joint mechanical power is negative. When engaged, the controller scales its resistive torque in proportion to estimated joint torque, thereby automatically scaling electrical power generation in proportion to the available mechanical power. To produce real-time estimates of joint torque and mechanical power, the controller leverages a simple model that predicts these variables from measured muscle activity and joint angular velocity. We first tested the model using available literature data for a range of walking speeds and found that estimates of knee joint torque and power well match the corresponding literature profiles (torque R(2): 0.73-0.92; power R(2): 0.60-0.94). We then used human subject experiments to test the performance of the entire controller. Over a range of steady state walking speeds and inclines, as well as a number of non-steady state walking conditions, the myoelectric controller accurately identified when the knee generated negative mechanical power, and automatically adjusted the magnitude of electrical power generation. PMID:26841402
Balas, Mark J.; Frost, Susan
Flexible structures containing a large number of modes can benefit from adaptive control techniques which are well suited to applications that have unknown modeling parameters and poorly known operating conditions. In this paper, we focus on a direct adaptive control approach that has been extended to handle adaptive rejection of persistent disturbances. We extend our adaptive control theory to accommodate troublesome modal subsystems of a plant that might inhibit the adaptive controller. In some cases the plant does not satisfy the requirements of Almost Strict Positive Realness. Instead, there maybe be a modal subsystem that inhibits this property. This section will present new results for our adaptive control theory. We will modify the adaptive controller with a Residual Mode Filter (RMF) to compensate for the troublesome modal subsystem, or the Q modes. Here we present the theory for adaptive controllers modified by RMFs, with attention to the issue of disturbances propagating through the Q modes. We apply the theoretical results to a flexible structure example to illustrate the behavior with and without the residual mode filter. We have proposed a modified adaptive controller with a residual mode filter. The RMF is used to accommodate troublesome modes in the system that might otherwise inhibit the adaptive controller, in particular the ASPR condition. This new theory accounts for leakage of the disturbance term into the Q modes. A simple three-mode example shows that the RMF can restore stability to an otherwise unstable adaptively controlled system. This is done without modifying the adaptive controller design.
Full Text Available Multimedia communications are communications with several types of media, such as audio, video and data. The current Internet has some levels of capability to support multimedia communications, unfortunately, the QoS (Quality of Service is still challenging. A large number of QoS mechanisms has been proposed; however, the main concern is for low levels, e.g. layer 2 (Data Link or 3 (Transport. In this paper, mechanisms for control the quality of audio and video are proposed. G.723.1 and MPEG-4 are used as the audio and video codec respectively. The proposed algorithm for adaptive quality control of audio communication is based on forward error correction (FEC. In the case of video communication, the proposed algorithm adapts the value of key frame interval, which is an encoding parameter of MPEG-4. We evaluated our proposed algorithms by computer simulation. We have shown that, in most cases, the proposed scheme gained a higher throughput compared to other schemes.
Handelman, David A.
The agility and adaptability of biological systems are worthwhile goals for next-generation unmanned ground vehicles. Management of the requisite number of degrees of freedom, however, remains a challenge, as does the ability of an operator to transfer behavioral intent from human to robot. This paper reviews American Android research funded by NASA, DARPA, and the U.S. Army that attempts to address these issues. Limb coordination technology, an iterative form of inverse kinematics, provides a fundamental ability to control balance and posture independently in highly redundant systems. Goal positions and orientations of distal points of the robot skeleton, such as the hands and feet of a humanoid robot, become variable constraints, as does center-of-gravity position. Behaviors utilize these goals to synthesize full-body motion. Biped walking, crawling and grasping are illustrated, and behavior parameterization, layering and portability are discussed. Robotic skill acquisition enables a show-and-tell approach to behavior modification. Declarative rules built verbally by an operator in the field define nominal task plans, and neural networks trained with verbal, manual and visual signals provide additional behavior shaping. Anticipated benefits of the resultant adaptive collaborative controller for unmanned ground vehicles include increased robot autonomy, reduced operator workload and reduced operator training and skill requirements.
Johnson, K. E.
The primary focus of this work is a new adaptive controller that is designed to resemble the standard non-adaptive controller used by the wind industry for variable speed wind turbines below rated power. This adaptive controller uses a simple, highly intuitive gain adaptation law designed to seek out the optimal gain for maximizing the turbine's energy capture. It is designed to work even in real, time-varying winds.
Hidetoshi Oya; Daisuke Yamasaki; Shunya Nagai; Kojiro Hagino
We present a new adaptive gain robust controller for polytopic uncertain systems. The proposed adaptive gain robust controller consists of a state feedback law with a fixed gain and a compensation input with adaptive gains which are tuned by updating laws. In this paper, we show that sufficient conditions for the existence of the proposed adaptive gain robust controller are given in terms of LMIs. Finally, illustrative examples are presented to show the effectiv...
Dimino, I.; Concilio, A.; Schueller, M.; Gratias, A.
A key technology to enable morphing aircraft for enhanced aerodynamic performance is the design of an adaptive control system able to emulate target structural shapes. This paper presents an approach to control the shape of a morphing wing by employing internal, integrated actuators acting on the trailing edge. The adaptive-wing concept employs active ribs, driven by servo actuators, controlled in turn by a dedicated algorithm aimed at shaping the wing cross section, according to a pre-defined geometry. The morphing control platform is presented and a suitable control algorithm is implemented in a dedicated routine for real-time simulations. The work is organized as follows. A finite element model of the uncontrolled, non-actuated structure is used to obtain the plant model for actuator torque and displacement control. After having characterized and simulated pure rotary actuator behavior over the structure, selected target wing shapes corresponding to rigid trailing edge rotations are achieved through both open-loop and closed-loop control logics.
Henningsen, Arne; Ravn, Ole
A comparison of the standard concepts in MRAC design suggests that a combination of the implicit and the explicit design techniques may lead to an improvement of the overall system performance in the presence of unmodelled dynamics. Using the ideas of adaptive stability augmentation a combined...
Henningsen, Arne; Ravn, Ole
A comparison of the standard concepts in MRAC design suggests that a combination of the implicit and the explicit design techniques may lead to an improvement of the overall system performance in the presence of unmodelled dynamics. Using the ideas of adaptive stability augmentation a combined...
Linearization by feedback of states is based on the idea of transform the nonlinear dynamic equation of a system in a linear form. This linear behavior can be achieve well in a complete way (input state) or in partial way (input output). This can be applied to systems of single or multiple inputs, and can be used to solve problems of stabilization and tracking of references trajectories. Comparing this method with conventional ones, linearization by feedback of states is exact in certain region of the space of state, instead of linear approximations of the equations in a certain point of the operation. In the presence of parametric uncertainties in the model of the system, the introduction of adaptive schemes provide a type toughness to the control system by nonlinear feedback, which gives as result the eventual cancellation of the nonlinear terms in the dynamic relationship between the output and the input of the auxiliary control. In the same way, it has been presented the design of a nonlinearizing control for the non lineal model of a TRIGA Mark III type reactor, with the aim of tracking a predetermined power profile. The asymptotic tracking of such profile is, at the present moment, in the stage of verification by computerized simulation the relative easiness in the design of auxiliary variable of control, as well as the decoupling action of the output variable, make very attractive the utilization of the method herein presented. (Author)
Ferreira, E. C.; Azevedo, S. Feyo de
This work deals with the development of model-based adaptive control algorithms for bioprocess operation. Non-linear adaptive control laws are proposed for single input single output regulation. Parameters are continuously adapted following a new adaptive scheme which ensures second-order dynamics of the parameter error system. A computational study is presented of the application of this theory to baker’s yeast fermentation. Results put in evidence the efficient performance both of ...
... Counterfeit Drugs Cruise Ship Travel Families with Children Fish Poisoning in Travelers Food and Water Getting Health ... INJURY ABOARD CRUISE SHIPS Cruise ship medical clinics deal with a wide variety of illnesses and injuries. ...
Full Text Available For the generator excitation control system which is equipped with static var compensator (SVC and unknown parameters, a novel adaptive dynamic surface control scheme is proposed based on neural network and tracking error transformed function with the following features: (1 the transformation of the excitation generator model to the linear systems is omitted; (2 the prespecified performance of the tracking error can be guaranteed by combining with the tracking error transformed function; (3 the computational burden is greatly reduced by estimating the norm of the weighted vector of neural network instead of the weighted vector itself; therefore, it is more suitable for the real time control; and (4 the explosion of complicity problem inherent in the backstepping control can be eliminated. It is proved that the new scheme can make the system semiglobally uniformly ultimately bounded. Simulation results show the effectiveness of this control scheme.
Chen, Cheng-Hung; Naidu, D. Subbaram; Perez-Gracia, Alba; Schoen, Marco P.
This paper presents a hybrid of a soft computing technique of adaptive neuro-fuzzy inference system (ANFIS) and a hard computing technique of adaptive control for a two- dimensional movement of a prosthetic hand with a thumb and index ﬁnger. In particular, ANFIS is used for inverse kinematics, and the adaptive control is used for linearized dynamics to minimize tracking error. The simulations of this hybrid controller, when compared with the proportional-integral-derivative (PID) controller s...
Prabhu, K; V. Murali Bhaskaran
Continues Stirred Tank Reactor (CSTR) is an important issue in chemical process and a wide range of research in the area of chemical engineering. Temperature Control of CSTR has been an issue in the chemical control engineering since it has highly non-linear complex equations. This study presents problem of temperature control of CSTR with the adaptive Controller. The Simulation is done in MATLAB and result shows that adaptive controller is an efficient controller for temperature control of C...
van Nort, Douglas
parameters. In this view, desired gestural dynamics and sonic response are achieved through modular construction of mapping layers that are themselves subject to parametric control. Complementing this view of the design process, the work concludes with an approach in which the creation of gestural control/sound dynamics are considered in the low-level of the underlying sound model. The result is an adaptive system that is specialized to noise-based transformations that are particularly relevant in an electroacoustic music context. Taken together, these different approaches to design and evaluation result in a unified framework for creation of an instrumental system. The key point is that this framework addresses the influence that mapping structure and control dynamics have on the perceived feel of the instrument. Each of the results illustrate this using either top-down or bottom-up approaches that consider musical control context, thereby pointing to the greater potential for refined sonic articulation that can be had by combining them in the design process.
SATOH, YASUYUKI; Nakamura, Hisakazu; Katayama, Hitoshi; Nishitani, Hirokazu
In this article, we proposed an adaptive inverse optimal controller for the magnetic levitation system. First, we designed an inverse optimal controller with a pre-feedback gravity compensator and applied it to the magnetic levitation system. However, this controller cannot guarantee any stability margin. We demonstrated that the controller did not work well (offset error remained) in the experiment. Hence, we proposed an improved controller via an adaptive control technique to guarantee the ...
Grzegorz Mikułowski; Łukasz Jankowski
An adaptive landing gear is a landing gear (LG) capable of active adaptation to particular landing conditions by means of controlled hydraulic force. The objective of the adaptive control is to mitigate the peak force transferred to the aircraft structure during touch-down, and thus to limit the structural fatigue factor. This paper investigates the ultimate limits for improvement due to various strategies of active control. Five strategies are proposed and investigated numerically using a~va...
Juntao Fei; Hongfei Ding
This paper presents an adaptive control approach for Micro-Electro-Mechanical Systems (MEMS) z-axis gyroscope sensor. The dynamical model of MEMS gyroscope sensor is derived and adaptive state tracking control for MEMS gyroscope is developed. The proposed adaptive control approaches can estimate the angular velocity and the damping and stiffness coefficients including the coupling terms due to the fabrication imperfection. The stability of the closed-loop systems is established with the propo...
Lefeber, AAJ Erjen; Nijmeijer, H Henk
We study an example of an adaptive (state) tracking control problem for a four-wheel mobile robot, as it is an illustrative example of the general adaptive state-feedback tracking control problem. It turns out that formulating the adaptive state-feedback tracking control problem is not straightforward, since specifying the reference state-trajectory can be in conflict with not knowing certain parameters. Our example illustrates this difficulty and we propose a problem formulation for the adap...
Presents an adaptive controller for continuous systems with unknown deadzones and known linear part which consists of an adaptive deadzone inverse to cancel the effects of deadzone and a linear-like control law to track the system output. It concludes from simulation results that this control possesses good robustness and improves the tracking performance of the system.
Jantzen, Jan; Poulsen, Niels Kjølstad
This simulation study provides an analysis of the adaptation mechanism in the self-organising fuzzy controller, SOC. The approach is to apply a traditional adaptive control viewpoint. A simplified performance measure in the SOC controller is used in a loss function, and thus the MIT rule implies an...
National Aeronautics and Space Administration — Adaptive control offers an opportunity to fulfill present and future aircraft safety objectives though automated vehicle recovery while maintaining performance and...
Full Text Available The problem of robust adaptive stabilization of a class of multi-input nonlinear systems with arbitrary unknown parameters and unknown structure of bounded variation have been considered. By employing the direct adaptive and control Lyapunov function method, a robust adaptive controller is designed to complete the globally adaptive stability of the system states. By employing our result, a kind of nonlinear system is analyzed, the concrete form of the control law is given and the meaningful quadratic control Lyapunov function for the system is constructed. Simulation of parallel manipulator is provided to illustrate the effectiveness of the proposed method.
LIU Hai-ou; CHEN Hui-yan; DING Hua-rong; HE Zhong-bo
Based on detail analysis of clutch engaging process control targets and adaptive demands, a control strategy which is based on speed signal, different from that of based on main clutch displacement signal, is put forward. It considers both jerk and slipping work which are the most commonly used quality evaluating indexes of vehicle starting phase. The adaptive control system and its reference model are discussed profoundly.Taking the adaptability to different starting gears and different road conditions as examples, some proving field test records are shown to illustrate the main clutch adaptive control strategy at starting phase. Proving field test gives acceptable results.
National Aeronautics and Space Administration — Adaptive control offers an opportunity to fulfill aircraft safety objectives though automated vehicle recovery while maintaining performance and stability...
Full Text Available Adaptive structures with controllable geometries and shapes are rather useful in many engineering applications, such as adaptive wings, variable focus mirrors, adaptive machines, micro-electromechanical systems, etc. Dynamics and feedback control effectiveness of adaptive shells whose curvatures are actively controlled and continuously changed are evaluated. An adaptive piezoelectric laminated cylindrical shell composite with continuous curvature changes is studied, and its natural frequencies and controlled damping ratios are evaluated. The curvature change of the adaptive shell starts from an open shallow shell (30° and ends with a deep cylindrical shell (360°. Dynamic characteristics and control effectiveness (via the proportional velocity feedback of this series of shells are investigated and compared at every 30° curvature change. Analytical solutions suggest that the lower modes are sensitive to curvature changes and the higher modes are relatively insensitive.
The paper describes the design considerations and implementational aspects of the Adaptive Blockset for Simulink which has been developed in a prototype implementation. The concept behind the Adaptive Blockset for Simulink is to bridge the gap between simulation and prototype controller...... implementation. This is done using the code generation capabilities of Real Time Workshop in combination with C s-function blocks for adaptive control in Simulink. In the paper the design of each group of blocks normally found in adaptive controllers is outlined. The block types are, identification, controller...... design, controller and state variable filter.The use of the Adaptive Blockset is demonstrated using a simple laboratory setup. Both the use of the blockset for simulation and for rapid prototyping of a real-time controller are shown....
Full Text Available Stress initiates adaptive processes that allow the organism to physiologically cope with prolonged or intermittent exposure to real or perceived threats. A major component of this response is repeated activation of glucocorticoid secretion by the hypothalamo-pituitary-adrenocortical (HPA axis, which promotes redistribution of energy in a wide range of organ systems, including the brain. Prolonged or cumulative increases in glucocorticoid secretion can reduce benefits afforded by enhanced stress reactivity and eventually become maladaptive. The long-term impact of stress is kept in check by the process of habituation, which reduces HPA axis responses upon repeated exposure to homotypic stressors and likely limits deleterious actions of prolonged glucocorticoid secretion. Habituation is regulated by limbic stress-regulatory sites, and is at least in part glucocorticoid feedback-dependent. Chronic stress also sensitizes reactivity to new stimuli. While sensitization may be important in maintaining response flexibility in response to new threats, it may also add to the cumulative impact of glucocorticoids on the brain and body. Finally, unpredictable or severe stress exposure may cause long-term and lasting dysregulation of the HPA axis, likely due to altered limbic control of stress effector pathways. Stress-related disorders, such as depression and PTSD, are accompanied by glucocorticoid imbalances and structural/ functional alterations in limbic circuits that resemble those seen following chronic stress, suggesting that inappropriate processing of stressful information may be part of the pathological process.
Verschure, Paul F M J
Understanding the nature of consciousness is one of the grand outstanding scientific challenges. The fundamental methodological problem is how phenomenal first person experience can be accounted for in a third person verifiable form, while the conceptual challenge is to both define its function and physical realization. The distributed adaptive control theory of consciousness (DACtoc) proposes answers to these three challenges. The methodological challenge is answered relative to the hard problem and DACtoc proposes that it can be addressed using a convergent synthetic methodology using the analysis of synthetic biologically grounded agents, or quale parsing. DACtoc hypothesizes that consciousness in both its primary and secondary forms serves the ability to deal with the hidden states of the world and emerged during the Cambrian period, affording stable multi-agent environments to emerge. The process of consciousness is an autonomous virtualization memory, which serializes and unifies the parallel and subconscious simulations of the hidden states of the world that are largely due to other agents and the self with the objective to extract norms. These norms are in turn projected as value onto the parallel simulation and control systems that are driving action. This functional hypothesis is mapped onto the brainstem, midbrain and the thalamo-cortical and cortico-cortical systems and analysed with respect to our understanding of deficits of consciousness. Subsequently, some of the implications and predictions of DACtoc are outlined, in particular, the prediction that normative bootstrapping of conscious agents is predicated on an intentionality prior. In the view advanced here, human consciousness constitutes the ultimate evolutionary transition by allowing agents to become autonomous with respect to their evolutionary priors leading to a post-biological Anthropocene.This article is part of the themed issue 'The major synthetic evolutionary transitions'. PMID
Nguyen, Charles C.; Antrazi, Sami S.
The implementation of a joint-space adaptive control scheme used to control non-compliant motion of a Stewart Platform-based Manipulator (SPBM) is presented. The SPBM is used in a facility called the Hardware Real-Time Emulator (HRTE) developed at Goddard Space Flight Center to emulate space operations. The SPBM is comprised of two platforms and six linear actuators driven by DC motors, and possesses six degrees of freedom. The report briefly reviews the development of the adaptive control scheme which is composed of proportional-derivative (PD) controllers whose gains are adjusted by an adaptation law driven by the errors between the desired and actual trajectories of the SPBM actuator lengths. The derivation of the adaptation law is based on the concept of model reference adaptive control (MRAC) and Lyapunov direct method under the assumption that SPBM motion is slow as compared to the controller adaptation rate. An experimental study is conducted to evaluate the performance of the adaptive control scheme implemented to control the SPBM to track a vertical and circular paths under step changes in payload. Experimental results show that the adaptive control scheme provides superior tracking capability as compared to fixed-gain controllers.
Mahmoud Mohamed Elkholy; Mohammed Abd Elhameed Abd Elnaiem
Conventional speed controllers of DC motors suffer from being not adaptive, this is because of the nonlinearity in the motor model due to saturation. Structure of DC motor speed controller should vary according to its operating conditions, so that the transient performance is acceptable. In this paper an adaptive and optimal Neuro-Genetic controller is used to control a DC motor speed. GA will be used first to obtain the optimal controller parameter for each load torque and motor refer...
ZHANG Yanxia; GUO Lei
It is well known that the transient behaviors of the traditional adaptive control may be very poor in general, and that the adaptive control designed based on switching between multiple models is an intuitively appealing and practically feasible approach to improve the transient performances. In this paper, we shall prove that for a typical class of linear systems disturbed by random noises, the multiple model based least-squares (LS)adaptive switching control is stable and convergent, and has the same convergence rate as that established for the standard least-squares-based self-tunning regulators. Moreover,the mixed case combining adaptive models with fixed models is also considered.
Sun, B.; Salter, P. S.; Booth, M. J.
The focusing of ultrashort laser pulses is extremely important for processes including microscopy, laser fabrication and fundamental science. Adaptive optic elements, such as liquid crystal spatial light modulators or membrane deformable mirrors, are routinely used for the correction of aberrations in these systems, leading to improved resolution and efficiency. Here, we demonstrate that adaptive elements used with ultrashort pulses should not be considered simply in terms of wavefront modification, but that changes to the incident pulse front can also occur. We experimentally show how adaptive elements may be used to engineer pulse fronts with spatial resolution.
National Aeronautics and Space Administration — To address the NASA need for quiet on-orbit crew quarters (CQ), Physical Optics Corporation (POC) proposes to develop a new Adaptive Intelligent Ventilation Noise...
National Aeronautics and Space Administration — To address NASA needs for quiet crew volumes in a space habitat, Physical Optics Corporation (POC) proposes to develop a new Adaptive Intelligent Ventilation Noise...
Xiao-juan WU; Xin-jian ZHU; Guang-yi CAO; Heng-yong TU
The operating temperature of a solid oxide fuel cell (SOFC) stack is a very important parameter to be controlled, which impacts the performance of the SOFC due to thermal cycling. In this paper, an adaptive fuzzy control method based on an affine nonlinear temperature model is developed to control the temperature of the SOFC within a specified range. Fuzzy logic systems are used to approximate nonlinear functions in the SOFC system and an adaptive technique is employed to construct the controller. Compared with the traditional fuzzy and proportion-integral-derivative (PID) control, the simulation results show that the designed adaptive fuzzy control method performed much better. So it is feasible to build an adaptive fuzzy controller for temperature control of the SOFC.
Farid, R.; Ibrahim, A.; Zalam, B., E-mail: firstname.lastname@example.org [Menofia University, Faculty of Electronic Engineering, Department of Industrial Electronics and Control, Menuf, Menofia (Egypt)
Chaos control here means to design a controller that is able to mitigating or eliminating the chaos behavior of nonlinear systems that experiencing such phenomenon. In this paper, an Adaptive Sliding Mode Controller (ASMC) is presented based on Lyapunov stability theory. The well known Chua's circuit is chosen to be our case study in this paper. The study shows the effectiveness of the proposed adaptive sliding mode controller.
In this report a problem is studied to construct a fuzzy controller for a mobile robot to move autonomously along a given reference direction curve, for which control rules are generated and acquired through an adaptive learning process. An adaptive learning fuzzy controller has been developed for a mobile robot. Good properties of the controller are shown through the travelling experiments of the mobile robot. (author)
Peng Song; Guo-kai Xu; Xiu-chun Zhao
Automatic profiling machine is a movement system that has a high degree of parameter variation and high frequency of transient process, and it requires an accurate control in time. In this paper, the discrete model reference adaptive control system of automatic profiling machine is discussed. Firstly, the model of automatic profiling machine is presented according to the parameters of DC motor. Then the design of the discrete model reference adaptive control is proposed, and the control rules...
Chaos control here means to design a controller that is able to mitigating or eliminating the chaos behavior of nonlinear systems that experiencing such phenomenon. In this paper, an Adaptive Sliding Mode Controller (ASMC) is presented based on Lyapunov stability theory. The well known Chua's circuit is chosen to be our case study in this paper. The study shows the effectiveness of the proposed adaptive sliding mode controller
Yucelen, Tansel (Inventor); Kim, Kilsoo (Inventor); Calise, Anthony J. (Inventor)
An adaptive control system is disclosed. The control system can control uncertain dynamic systems. The control system can employ one or more derivative-free adaptive control architectures. The control system can further employ one or more derivative-free weight update laws. The derivative-free weight update laws can comprise a time-varying estimate of an ideal vector of weights. The control system of the present invention can therefore quickly stabilize systems that undergo sudden changes in dynamics, caused by, for example, sudden changes in weight. Embodiments of the present invention can also provide a less complex control system than existing adaptive control systems. The control system can control aircraft and other dynamic systems, such as, for example, those with non-minimum phase dynamics.
In this Letter, it is shown that a couple of the modified Chua's systems with different parameters and initial conditions can be synchronized using active control when the values of parameters both in drive system and response system are known aforehand. Furthermore, an adaptive active control approach is proposed based on Lyapunov stability theory to make the states of two identical Chua's systems with unknown constant parameters be asymptotically synchronized. In addition, the proposed adaptive active control method guarantees that the designed controller is independent to those uncertain parameters. Simulation results by using both active control and adaptive active control are provided, and the feasibility and effectiveness of the proposed adaptive active control are demonstrated
GUAN Ping; LIU Xiang-dong; CHEN Jia-bin; LIU Xiao-he
The adaptive fuzzy control is combined with input-output linearization control to constitute the hybrid controller. The control method is then applied to the attitude maneuver control of the flexible satellite.The basic control structure is given. The rules of the controller parameter selection, which guarantee the attitude stabilization of the satellite with parameter uncertainties, have been analyzed. Simulation results show that the precise attitude control is accomplished in spite of the uncertainty in the system.
WUZhao-Jing; XIEXue-Jun; ZHANGSi-Ying
For a class of systems with unmodeled dynamics, robust adaptive stabilization problem is considered in this paper. Firstly， by a series of coordinate changes, the original system is reparameterized. Then, by introducing a reduced-order observer, an error system is obtained. Based on the system, a reduced-order adaptive backstepping controller design scheme is given. It is proved that all the signals in the adaptive control system are globally uniformly bounded, and the regulation error converges to zero asymptotically. Due to the order deduction of the controller, the design scheme in this paper has more practical values. A simulation example further demonstrates the efficiency of the control scheme.
Andersen, T.O.; Hansen, M.R.; Conrad, Finn
A method for synthesis of a robust adaptive scheme for a hydraulically driven manipulator, that takes full advantage of any known system dynamics to simplify the adaptive control problem for the unknown portion of the dynamics is presented. The control method is based on adaptive perturbation...... control.Using the Lyapunov approach, under slowly time-varying assumptions, it is shown that the tracking error and the parameter error remain bounded. This bound is a function of the ideal parameters and a bounded disturbance. The control algorithm decouples and linearizes the manipulator so that each...... joint behaves as an independent second-order system with fixed dynamics....
Andersen, T.O.; Hansen, M.R.; Conrad, Finn
control.Using the Lyapunov approach, under slowly time-varying assumptions, it is shown that the tracking error and the parameter error remain bounded. This bound is a function of the ideal parameters and a bounded disturbance. The control algorithm decouples and linearizes the manipulator so that each......A method for synthesis of a robust adaptive scheme for a hydraulically driven manipulator, that takes full advantage of any known system dynamics to simplify the adaptive control problem for the unknown portion of the dynamics is presented. The control method is based on adaptive perturbation...
Three strategies for adaptive control of cooperative dual-arm robots are discussed. Implementation of these adaptive controllers does not require the use of complex mathematical models of the arm dynamics or knowledge of the arm dynamic parameters or load parameters. These strategies have simple structures, and are computationally fast for on-line implementation with high sampling rates. In all three cases, the coupling effects between the arms through the load are treated as disturbances which are rejected by the adaptive controllers while following desired commands in a common frame of reference. Simulation results demonstrate the usefulness of the controllers.
Jin J; Allison B.Z.; Sellers E.W.; Brunner & C.; Horki P.; Wang X; Neuper C.
An adaptive P300 brain-computer interface (BCI) using a 12 × 7 matrix explored new paradigms to improve bit rate and accuracy. During online use, the system adaptively selects the number of flashes to average. Five different flash patterns were tested. The 19-flash paradigm represents the typical row/column presentation (i.e., 12 columns and 7 rows). The 9- and 14-flash A & B paradigms present all items of the 12 × 7 matrix three times using either nine or 14 flashes (instead of 19), decreasi...
Johnson, Kathryn E.
Wind is a clean, renewable resource that has become more popular in recent years due to numerous advances in technology and public awareness. Wind energy is quickly becoming cost competitive with fossil fuels, but further reductions in the cost of wind energy are necessary before it can grow into a fully mature technology. One reason for higher-than-necessary cost of the wind energy is uncertainty in the aerodynamic parameters, which leads to inefficient controllers. This thesis explores an adaptive control technique designed to reduce the negative effects of this uncertainty. The primary focus of this work is a new adaptive controller that is designed to resemble the standard non-adaptive controller used by the wind industry. The standard controller was developed for variable speed wind turbines operating below rated power. The new adaptive controller uses a simple, highly intuitive gain adaptation law intended to seek out the optimal gain for maximizing the turbine's energy capture. It is designed to work even in real, time-varying winds. The adaptive controller has been tested both in simulation and on a real turbine, with numerous experimental results provided in this work. Simulations have considered the effects of erroneous wind measurements and time-varying turbine parameters, both of which are concerns on the real turbine. The adaptive controller has been found to operate as desired under realistic operating conditions, and energy capture has increased on the real turbine as a result. Theoretical analyses of the standard and adaptive controllers were performed, as well, providing additional insight into the system. Finally, a few extensions were made with the intent of making the adaptive control idea even more appealing in the commercial wind turbine market.
Hormetic dose response occurs for many endpoints associated with exposures of biological organisms to environmental stressors. Cell-based U- or inverted U-shaped responses may derive from common processes involved in activation of adaptive responses required to protect cells from...
Carlos A. Saldarriaga-Cortés; Víctor D. Correa-Ramírez; Didier Giraldo-Buitrago
This paper presents a methodology to implement an adaptive control of the inverted pendulum system; which uses the recursive square minimum method for the identification of a dynamic digital model of the plant and then, with its estimated parameters, tune in real time a pole placement control. The plant to be used is an unstable and nonlinear system. This fact, combined with the adaptive controller characteristics, allows the obtained results to be extended to a great variety of systems. The ...
© 2015 Mathematical Sciences Publishers. Adaptive step-size control is a critical feature for the robust and efficient numerical solution of initial-value problems in ordinary differential equations. In this paper, we show that adaptive step-size control can be incorporated within a family of parallel time integrators known as revisionist integral deferred correction (RIDC) methods. The RIDC framework allows for various strategies to implement stepsize control, and we report results from exploring a few of them.
Herzallah, R.; Kárný, Miroslav
Roč. 24, č. 10 (2011), s. 1128-1135. ISSN 0893-6080 R&D Projects: GA ČR GA102/08/0567 Institutional research plan: CEZ:AV0Z10750506 Keywords : Stochastic control design * Fully probabilistic design * Adaptive control * Adaptive critic Subject RIV: BC - Control Systems Theory Impact factor: 2.182, year: 2011 http://library.utia.cas.cz/separaty/2011/AS/karny-0364820.pdf
Burken, John J.; Nguyen, Nhan T.; Griffin, Brian J.
In the presence of large uncertainties, a control system needs to be able to adapt rapidly to regain performance. Fast adaptation is referred to as the implementation of adaptive control with a large adaptive gain to reduce the tracking error rapidly; however, a large adaptive gain can lead to high-frequency oscillations which can adversely affect the robustness of an adaptive control law. A new adaptive control modification is presented that can achieve robust adaptation with a large adaptive gain without incurring high-frequency oscillations as with the standard model-reference adaptive control. The modification is based on the minimization of the Y2 norm of the tracking error, which is formulated as an optimal control problem. The optimality condition is used to derive the modification using the gradient method. The optimal control modification results in a stable adaptation and allows a large adaptive gain to be used for better tracking while providing sufficient robustness. A damping term (v) is added in the modification to increase damping as needed. Simulations were conducted on a damaged F-18 aircraft (McDonnell Douglas, now The Boeing Company, Chicago, Illinois) with both the standard baseline dynamic inversion controller and the adaptive optimal control modification technique. The results demonstrate the effectiveness of the proposed modification in tracking a reference model.
Yu, Yongxin; Zhang, Yuhua
To improve ophthalmic adaptive optics speed and compensate for ocular wavefront aberration of high temporal frequency, the adaptive optics wavefront correction has been implemented with a control scheme including 2 parallel threads; one is dedicated to wavefront detection and the other conducts wavefront reconstruction and compensation. With a custom Shack-Hartmann wavefront sensor that measures the ocular wave aberration with 193 subapertures across the pupil, adaptive optics has achieved a ...
Hanson, Curt; Schaefer, Jacob; Johnson, Marcus; Nguyen, Nhan
Flight research experiments have demonstrated that adaptive flight controls can be an effective technology for improving aircraft safety in the event of failures or damage. However, the nonlinear, timevarying nature of adaptive algorithms continues to challenge traditional methods for the verification and validation testing of safety-critical flight control systems. Increasingly complex adaptive control theories and designs are emerging, but only make testing challenges more difficult. A potential first step toward the acceptance of adaptive flight controllers by aircraft manufacturers, operators, and certification authorities is a very simple design that operates as an augmentation to a non-adaptive baseline controller. Three such controllers were developed as part of a National Aeronautics and Space Administration flight research experiment to determine the appropriate level of complexity required to restore acceptable handling qualities to an aircraft that has suffered failures or damage. The controllers consist of the same basic design, but incorporate incrementally-increasing levels of complexity. Derivations of the controllers and their adaptive parameter update laws are presented along with details of the controllers implementations.
Adaptive control techniques are well suited to applications that have unknown modeling parameters and poorly known operating conditions. Many physical systems experience external disturbances that are persistent or continually recurring. Flexible structures and systems with compliance between components often form a class of systems that fail to meet standard requirements for adaptive control. For these classes of systems, a residual mode filter can restore the ability of the adaptive controller to perform in a stable manner. New theory will be presented that enables adaptive control with accommodation of persistent disturbances using residual mode filters. After a short introduction to some of the control challenges of large utility-scale wind turbines, this theory will be applied to a high-fidelity simulation of a wind turbine.
Stress initiates adaptive processes that allow the organism to physiologically cope with prolonged or intermittent exposure to real or perceived threats. A major component of this response is repeated activation of glucocorticoid secretion by the hypothalamo-pituitary-adrenocortical (HPA) axis, which promotes redistribution of energy in a wide range of organ systems, including the brain. Prolonged or cumulative increases in glucocorticoid secretion can reduce benefits afforded by enhanced s...
Mead, W.C.; Brown, S.K.; Jones, R.D.; Bowling, P.S.; Barnes, C.W.
Recent work has demonstrated the ability of neural-network-based controllers to optimize and control machines with complex, non-linear, relatively unknown control spaces. We present a brief overview of neural networks via a taxonomy illustrating some capabilities of different kinds of neural networks. We present some successful control examples, particularly the optimization and control of a small-angle negative ion source.
Erik D. Engeberg
Full Text Available Eight human test subjects attempted to track a desired position trajectory with an instrumented manipulandum (MN. The test subjects used the MN with three different levels of stiffness. A transfer function was developed to represent the human application of a precision grip from the data when the test subjects initially displaced the MN so as to learn the position mapping from the MN onto the display. Another transfer function was formed from the data of the remainder of the experiments, after significant displacement of the MN occurred. Both of these transfer functions accurately modelled the system dynamics for a portion of the experiments, but neither was accurate for the duration of the experiments because the human grip dynamics changed while learning the position mapping. Thus, an adaptive system model was developed to describe the learning process of the human test subjects as they displaced the MN in order to gain knowledge of the position mapping. The adaptive system model was subsequently validated following comparison with the human test subject data. An examination of the average absolute error between the position predicted by the adaptive model and the actual experimental data yielded an overall average error of 0.34mm for all three levels of stiffness.
Chen Feng-Xiang; Wang Wei; Zhang Wei-Dong
The paper is concerned with adaptive tracking problem for a class of chaotic system with time-varying uncertainty,but bounded by norm polynomial. Based on adaptive technique, it proposes a novel controller to asymptotically track the arbitrary desired bounded trajectory. Simulation on the Rossler chaotic system is performed and the result verifies the effectiveness of the proposed method.
Stepanyan, Vahram; Krishnakumar, Kalmanje; Nguyen, Nhan; VanEykeren, Luarens
This paper addresses the problem of verifying adaptive control techniques for enabling safe flight in the presence of adverse conditions. Since the adaptive systems are non-linear by design, the existing control verification metrics are not applicable to adaptive controllers. Moreover, these systems are in general highly uncertain. Hence, the system's characteristics cannot be evaluated by relying on the available dynamical models. This necessitates the development of control verification metrics based on the system's input-output information. For this point of view, a set of metrics is introduced that compares the uncertain aircraft's input-output behavior under the action of an adaptive controller to that of a closed-loop linear reference model to be followed by the aircraft. This reference model is constructed for each specific maneuver using the exact aerodynamic and mass properties of the aircraft to meet the stability and performance requirements commonly accepted in flight control. The proposed metrics are unified in the sense that they are model independent and not restricted to any specific adaptive control methods. As an example, we present simulation results for a wing damaged generic transport aircraft with several existing adaptive controllers.
This research focuses on development of L 1 adaptive output-feedback control. The objective is to extend the L1 adaptive control framework to a wider class of systems, as well as obtain architectures that afford more straightforward tuning. We start by considering an existing L1 adaptive output-feedback controller for non-strictly positive real systems based on piecewise constant adaptation law. It is shown that L 1 adaptive control architectures achieve decoupling of adaptation from control, which leads to bounded away from zero time-delay and gain margins in the presence of arbitrarily fast adaptation. Computed performance bounds provide quantifiable performance guarantees both for system output and control signal in transient and steady state. A noticeable feature of the L1 adaptive controller is that its output behavior can be made close to the behavior of a linear time-invariant system. In particular, proper design of the lowpass filter can achieve output response, which almost scales for different step reference commands. This property is relevant to applications with human operator in the loop (for example: control augmentation systems of piloted aircraft), since predictability of the system response is necessary for adequate performance of the operator. Next we present applications of the L1 adaptive output-feedback controller in two different fields of engineering: feedback control of human anesthesia, and ascent control of a NASA crew launch vehicle (CLV). The purpose of the feedback controller for anesthesia is to ensure that the patient's level of sedation during surgery follows a prespecified profile. The L1 controller is enabled by anesthesiologist after he/she achieves sufficient patient sedation level by introducing sedatives manually. This problem formulation requires safe switching mechanism, which avoids controller initialization transients. For this purpose, we used an L1 adaptive controller with special output predictor initialization routine
Szelitzky, Tibor; Henrietta Dulf, Eva
Permanent variations of the electric properties of the load in induction heating equipment make difficult to control the plant. To overcome these disadvantages, the authors propose a new approach based on adaptive control methods. For real plants it is enough to present desired performances or start-up variables for the controller, from which the algorithms tune the controllers by itself. To present the advantages of the proposed controllers, comparisons are made to a PI controller tuned through Ziegler-Nichols method.
Lin, Chih-Min; Peng, Ya-Fu
An adaptive cerebellar model articulation controller (CMAC) is proposed for command to line-of-sight (CLOS) missile guidance law design. In this design, the three-dimensional (3-D) CLOS guidance problem is formulated as a tracking problem of a time-varying nonlinear system. The adaptive CMAC control system is comprised of a CMAC and a compensation controller. The CMAC control is used to imitate a feedback linearization control law and the compensation controller is utilized to compensate the difference between the feedback linearization control law and the CMAC control. The online adaptive law is derived based on the Lyapunov stability theorem to learn the weights of receptive-field basis functions in CMAC control. In addition, in order to relax the requirement of approximation error bound, an estimation law is derived to estimate the error bound. Then the adaptive CMAC control system is designed to achieve satisfactory tracking performance. Simulation results for different engagement scenarios illustrate the validity of the proposed adaptive CMAC-based guidance law. PMID:15940993
JIANG Rui; LUO Guiming
The least-squares(LS)algorithm has been used for system modeling for a long time. Without any excitation conditions, only the convergence rate of the common LS algorithm can be obtained. This paper analyzed the weighted least-squares(WLS)algorithm and described the good properties of the WLS algorithm. The WLS algorithm was then used for daptive control of linear stochastic systems to show that the linear closed-loop system was globally stable and that the system identification was consistent. Compared to the past optimal adaptive controller,this controller does not impose restricted conditions on the coefficients of the system, such as knowing the first coefficient before the controller. Without any persistent excitation conditions, the analysis shows that, with the regulation of the adaptive control, the closed-loop system was globally stable and the adaptive controller converged to the one-step-ahead optimal controller in some sense.
Taeed, Fazel; Nymand, Morten
converter duty cycle. The adaptive slope compensation provides optimum controller operation in term of bandwidth over wide range of operating points. In this paper operation principle of the controller is discussed. The proposed controller is implemented in an FPGA to control a 100 W buck converter. The......An adaptive slope compensation method for digital current mode control of dc-dc converters is proposed in this paper. The compensation slope is used for stabilizing the inner current loop in peak current mode control. In this method, the compensation slope is adapted with the variations in...... experimental results of measured loop-gain at different operating points are presented to validate the theoretical performance of the controller....
Alex M C Smith
Full Text Available In this paper we present a hybrid control scheme, combining the advantages of task-space and joint-space control. The controller is based on a human-like adaptive design, which minimises both control effort and tracking error. Our novel hybrid adaptive controller has been tested in extensive simulations, in a scenario where a Baxter robot manipulator is affected by external disturbances in the form of interaction with the environment and tool-like end-effector perturbations. The results demonstrated improved performance in the hybrid controller over both of its component parts. In addition, we introduce a novel method for online adaptation of learning parameters, using the fuzzy control formalism to utilise expert knowledge from the experimenter. This mechanism of meta-learning induces further improvement in performance and avoids the need for tuning through trial testing.
Kappen, H. J.; Ruiz, H. C.
Path integral (PI) control problems are a restricted class of non-linear control problems that can be solved formally as a Feynman-Kac PI and can be estimated using Monte Carlo sampling. In this contribution we review PI control theory in the finite horizon case. We subsequently focus on the problem how to compute and represent control solutions. We review the most commonly used methods in robotics and control. Within the PI theory, the question of how to compute becomes the question of importance sampling. Efficient importance samplers are state feedback controllers and the use of these requires an efficient representation. Learning and representing effective state-feedback controllers for non-linear stochastic control problems is a very challenging, and largely unsolved, problem. We show how to learn and represent such controllers using ideas from the cross entropy method. We derive a gradient descent method that allows to learn feed-back controllers using an arbitrary parametrisation. We refer to this method as the path integral cross entropy method or PICE. We illustrate this method for some simple examples. The PI control methods can be used to estimate the posterior distribution in latent state models. In neuroscience these problems arise when estimating connectivity from neural recording data using EM. We demonstrate the PI control method as an accurate alternative to particle filtering.
Schulz, Richard; And Others
Research suggests that primary control increases as humans develop from infancy through middle age and then decreases in old age. To minimize losses, individuals rely on cognitively based secondary control processes in middle and old age. Literature on adult control processes is reviewed. (SLD)
National Aeronautics and Space Administration — The innovation of the proposed project is the development of High Efficiency Lighting with Integrated Adaptive Control (HELIAC) systems to drive plant growth. Solar...
National Aeronautics and Space Administration — SSCI, in collaboration with Boeing Phantom Works, proposes to develop and test an efficient Integrated Damage Adaptive Control System (IDACS). The proposed system...
French, Mark; Trenn, Stephan
A class of discrete plants controlled by a switching adaptive strategy is considered, and $l^p$ bounds, $1 \\le p \\le \\infty$, are obtained for the closed loop gain relating input and output disturbances to internal signals.
National Aeronautics and Space Administration — The proposed project is the continued development of the High Efficiency Lighting with Integrated Adaptive Control (HELIAC) system. Solar radiation is not a viable...
National Aeronautics and Space Administration — Most fault adaptive control research addresses the preservation of system stability or functionality in the presence of a specific failure (fault). This paper...
National Aeronautics and Space Administration — SSCI proposes to further develop, implement and test the damage-adaptive control algorithms developed in Phase I within the framework of an Integrated Damage...
Nguyen, Nhan T.
This paper presents a new model-reference adaptive control method based on a bi-objective optimal control formulation for systems with input uncertainty. A parallel predictor model is constructed to relate the predictor error to the estimation error of the control effectiveness matrix. In this work, we develop an optimal control modification adaptive control approach that seeks to minimize a bi-objective linear quadratic cost function of both the tracking error norm and predictor error norm simultaneously. The resulting adaptive laws for the parametric uncertainty and control effectiveness uncertainty are dependent on both the tracking error and predictor error, while the adaptive laws for the feedback gain and command feedforward gain are only dependent on the tracking error. The optimal control modification term provides robustness to the adaptive laws naturally from the optimal control framework. Simulations demonstrate the effectiveness of the proposed adaptive control approach.
Belik, Vitaly; Hövel, Philipp
We consider recurrent contagious processes on a time-varying network. As a control procedure to mitigate the epidemic, we propose an adaptive rewiring mechanism for temporary isolation of infected nodes upon their detection. As a case study, we investigate the network of pig trade in Germany. Based on extensive numerical simulations for a wide range of parameters, we demonstrate that the adaptation mechanism leads to a significant extension of the parameter range, for which most of the index nodes (origins of the epidemic) lead to vanishing epidemics. We find that diseases with detection times around a week and infectious periods up to 3 months can be effectively controlled. Furthermore the performance of adaptation is very heterogeneous with respect to the index node. We identify index nodes that are most responsive to the adaptation strategy and quantify the success of the proposed adaptation scheme in dependence on the infectious period and detection times.
Hansen, Poul Erik; Conrad, Finn
Presentation of two new developed adaptive non-liner controllers for hydraulic actuator systems to give stable operation and improved performance.Results from the IMCIA project supported by the Danish Technical Research Council (STVF).......Presentation of two new developed adaptive non-liner controllers for hydraulic actuator systems to give stable operation and improved performance.Results from the IMCIA project supported by the Danish Technical Research Council (STVF)....
Alejandro Carrasco Elizalde; Peter Goldsmith
The collective behaviour of swarms produces smarter actions than those achieved by a single individual. Colonies of ants, flocks of birds and fish schools are examples of swarms interacting with their environment to achieve a common goal. This cooperative biological intelligence is the inspiration for an adaptive fuzzy controller developed in this paper. Swarm intelligence is used to adjust the parameters of the membership functions used in the adaptive fuzzy controller. The rules of the cont...
Hansen, Poul Erik; Conrad, Finn
Presentation of two new developed adaptive non-liner controllers for hydraulic actuator systems to give stable operation and improved performance.Results from the IMCIA project supported by the Danish Technical Research Council (STVF).......Presentation of two new developed adaptive non-liner controllers for hydraulic actuator systems to give stable operation and improved performance.Results from the IMCIA project supported by the Danish Technical Research Council (STVF)....
Kárný, Miroslav; Herzallah, R.
-, - (2016). ISSN 2168-2216 R&D Projects: GA ČR GA13-13502S Institutional support: RVO:67985556 Keywords : Adaptive control * Adaptive estimation * Bayes methods * Complex networks * Decentralized control * Feedback * Feedforward systems * Recursive estimation Subject RIV: BB - Applied Statistics, Operational Research Impact factor: 1.699, year: 2014 http://library.utia.cas.cz/separaty/2016/AS/karny-0457337.pdf
Luković, Tihomir; Asić, Antun; Šperanda, Ivo
Cruising tourism is the largest growing tourism sub-system. The importance of cruising tourism should be viewed in a far wider context than tourism itself. Namely, cruising tourism is maintained by numerous shareholders whose interests need to be reassured for the purpose of sustainable destination development. Tourism’s sub-system, cruise ships, in comparison to the sub-system of coastal tourism, has its own specifics which may easily prove contradictory in itself and thus compromise sustain...
Sullivan, Gerald A.
Adaptive control is presently one of the methods available which may be used to control plants with poorly modelled dynamics or time varying dynamics. Although many variations of adaptive controllers exist, a common characteristic of all adaptive control schemes, is that input/output measurements from the plant are used to adjust a control law in an on-line fashion. Ideally the adjustment mechanism of the adaptive controller is able to learn enough about the dynamics of the plant from input/output measurements to effectively control the plant. In practice, problems such as measurement noise, controller saturation, and incorrect model order, to name a few, may prevent proper adjustment of the controller and poor performance or instability result. In this work we set out to avoid the inadequacies of procedurally implemented safety nets, by introducing a two level control scheme in which an expert system based 'supervisor' at the upper level provides all the safety net functions for an adaptive controller at the lower level. The expert system is based on a shell called IPEX, (Interactive Process EXpert), that we developed specifically for the diagnosis and treatment of dynamic systems. Some of the more important functions that the IPEX system provides are: (1) temporal reasoning; (2) planning of diagnostic activities; and (3) interactive diagnosis. Also, because knowledge and control logic are separate, the incorporation of new diagnostic and treatment knowledge is relatively simple. We note that the flexibility available in the system to express diagnostic and treatment knowledge, allows much greater functionality than could ever be reasonably expected from procedural implementations of safety nets. The remainder of this chapter is divided into three sections. In section 1.1 we give a detailed review of the literature in the area of supervisory systems for adaptive controllers. In particular, we describe the evolution of safety nets from simple ad hoc techniques, up
An H(sub infinity)-NMA architecture for the Crew Launch Vehicle was developed in a state feedback setting. The minimal complexity adaptive law was shown to improve base line performance relative to a performance metric based on Crew Launch Vehicle design requirements for all most all of the Worst-on-Worst dispersion cases. The adaptive law was able to maintain stability for some dispersions that are unstable with the nominal control law. Due to the nature of the H(sub infinity)-NMA architecture, the augmented adaptive control signal has low bandwidth which is a great benefit for a manned launch vehicle.
Ping He; Chun-Guo Jing; Chang-Zhong Chen; Tao Fan; Hassan Saberi Nik
In this paper, the synchronization problem of general complex networks is investigated by using adaptive control schemes. Time-delay coupling, derivative coupling, nonlinear coupling etc. exist universally in real-world complex networks. The adaptive synchronization scheme is designed for the complex network with multiple class of coupling terms. A criterion guaranteeing synchronization of such complex networks is established by employing the Lyapunov stability theorem and adaptive control schemes. Finally, an illustrative example with numerical simulation is given to show the feasibility and efficiency of theoretical results.
Belda, Květoslav; Böhm, Josef
Roč. 5, č. 8 (2006), s. 1830-1837. ISSN 1109-2777 R&D Projects: GA ČR GP102/06/P275; GA ČR GA102/05/0271 Institutional research plan: CEZ:AV0Z10750506 Keywords : on-line identification * predictive control * input/output equations of predictions * real-time control Subject RIV: BC - Control Systems Theory http://library.utia.cas.cz/separaty/historie/belda-0040149.pdf
El-Deen, M. M. G. Naser
Significant progress has been made on maximising passive solar heating loads through the careful selection of glazing, orientation and internal mass within building spaces. Control of space heating in buildings of this type has become a complex problem. Additionally, and in common with most building control applications, there is a need to develop control solutions that permit simple and transparent set up and commissioning procedures. This work concerns the development and testing of an adap...
Wrangham, Richard W.; Carmody, Rachel Naomi
Charles Darwin attributed human evolutionary success to three traits. Our social habits and anatomy were important, he said, but the critical feature was our intelligence, because it led to so much else, including such traits as language, weapons, tools, boats, and the control of fire. Among these, he opined, the control of fire was “probably the greatest ever [discovery] made by man, excepting language.” Despite this early suggestion that the control of fire was even more important than tool...
Mingjun ZHANG; Huaguang ZHANG
In this paper, a robust adaptive fuzzy control scheme for a class of nonlinear system with uncertainty is proposed. First, using prior knowledge about the plant we obtain a fuzzy model, which is called the generalized fuzzy hyperbolic model (GFHM). Secondly, for the case that the states of the system are not available an observer is designed and a robust adaptive fuzzy output feedback control scheme is developed. The overall control system guarantees that the tracking error converges to a small neighborhood of origin and that all signals involved are uniformly bounded. The main advantages of the proposed control scheme are that the human knowledge about the plant under control can be used to design the controller and only one parameter in the adaptive mechanism needs to be on-line adjusted.
Karr, C. L.
Researchers at the U.S. Bureau of Mines have developed adaptive process control systems in which genetic algorithms (GA's) are used to augment fuzzy logic controllers (FLC's). GA's are search algorithms that rapidly locate near-optimum solutions to a wide spectrum of problems by modeling the search procedures of natural genetics. FLC's are rule based systems that efficiently manipulate a problem environment by modeling the 'rule-of-thumb' strategy used in human decision making. Together, GA's and FLC's possess the capabilities necessary to produce powerful, efficient, and robust adaptive control systems. To perform efficiently, such control systems require a control element to manipulate the problem environment, and a learning element to adjust to the changes in the problem environment. Details of an overall adaptive control system are discussed. A specific laboratory acid-base pH system is used to demonstrate the ideas presented.
Karr, C. L.
Researchers at the U.S. Bureau of Mines have developed adaptive process control systems in which genetic algorithms (GA's) are used to augment fuzzy logic controllers (FLC's). GA's are search algorithms that rapidly locate near-optimum solutions to a wide spectrum of problems by modeling the search procedures of natural genetics. FLC's are rule based systems that efficiently manipulate a problem environment by modeling the 'rule-of-thumb' strategy used in human decision-making. Together, GA's and FLC's possess the capabilities necessary to produce powerful, efficient, and robust adaptive control systems. To perform efficiently, such control systems require a control element to manipulate the problem environment, an analysis element to recognize changes in the problem environment, and a learning element to adjust to the changes in the problem environment. Details of an overall adaptive control system are discussed. A specific laboratory acid-base pH system is used to demonstrate the ideas presented.
Mekel, R.; Nachmias, S.
A learning control system and its utilization as a flight control system for F-8 Digital Fly-By-Wire (DFBW) research aircraft is studied. The system has the ability to adjust a gain schedule to account for changing plant characteristics and to improve its performance and the plant's performance in the course of its own operation. Three subsystems are detailed: (1) the information acquisition subsystem which identifies the plant's parameters at a given operating condition; (2) the learning algorithm subsystem which relates the identified parameters to predetermined analytical expressions describing the behavior of the parameters over a range of operating conditions; and (3) the memory and control process subsystem which consists of the collection of updated coefficients (memory) and the derived control laws. Simulation experiments indicate that the learning control system is effective in compensating for parameter variations caused by changes in flight conditions.
Ran Maopeng; Wang Qing; Hou Delong; Dong Chaoyang
This paper presents an integrated missile guidance and control law based on adaptive fuzzy sliding mode control. The integrated model is formulated as a block-strict-feedback nonlinear system, in which modeling errors, unmodeled nonlinearities, target maneuvers, etc. are viewed as unknown uncertainties. The adaptive nonlinear control law is designed based on backstepping and sliding mode control techniques. An adaptive fuzzy system is adopted to approximate the coupling nonlinear functions of...
Yizhong WANG; Huaguang ZHANG; Jun YANG
This paper focuses on the robust adaptive control problems for a class of interval time-delay systems and a class of large-scale interconnected systems. The nonlinear uncertainties of the systems under study are bounded by high-order polynomial functions with unknown gains. Firstly, the adaptive feedback controller which can guarantee the stability of the closed-loop system in the sense of uniform ultimate boundedness is proposed. Then the proposed adaptive idea is extended to robust stabilizing designing method for a class of large-scale interconnected systems. Here, another problem we address is to design a decentralized feedback adaptive controller such that the closed-loop system is stable in the sense of uniform ultimate boundedness for all admissible uncertainties and time-delay. Finally, an illustrative example is given to show the validity of the proposed approach.
Šmídl, Václav; Andrýsek, Josef
Seattle : IEEE, 2008, s. 3414-3415. ISBN 978-1-4244-2078-0. [American Control Conference. Seattle (US), 11.06.2008-13.06.2008] R&D Projects: GA MŠk 1M0572; GA ČR GP102/08/P250 Institutional research plan: CEZ:AV0Z10750506 Keywords : adaptive control * decentralised control * probability Subject RIV: BC - Control Systems Theory http://library.utia.cas.cz/separaty/2008/AS/smidl-merging of multistep predictors for decentralized adaptive.pdf
Jens G. Balchen
Full Text Available A technique for the adaptation of controller parameters in a single control loop based upon the estimation of frequency response parameters has been presented in an earlier paper. This paper contains an extension and a generalization of the first method and results in a more versatile solution which is applicable to a wider range of process characteristics. The application of this adaptive control technique is illustrated by a laboratory refrigeration cycle in which the evaporator pressure controls the speed of the compressor.
This paper presents the control problem of a class of propagation bio-processes that are carried out in fixed bed reactors. Since the dynamics of these processes are described by partial differential equations, in order to obtain useful models for control purposes, a possible method consists of approximation of their infinitely order associated models by finite order models. A class of nonlinear adaptive controllers are then designed based on these finite order models, which consist of a set of ordinary differential equations obtained here by orthogonal collocation method. Computer simulations conducted in the case of a fixed bed reactor are included to illustrate the performances of the proposed adaptive controllers. (authors)
Galeazzi, Roberto; Borup, Kasper Trolle; Niemann, Hans Henrik;
This paper investigates the feasibility of operating a wind turbine with lightweight tower in the full load region exploiting an adaptive nonlinear controller that allows the turbine to dynamically lean against the wind while maintaining nominal power output. The use of lightweight structures for...... towers and foundations would greatly reduce the construction cost of the wind turbine, however extra features ought be included in the control system architecture to avoid tower collapse. An adaptive backstepping collective pitch controller is proposed for tower point tracking control, i.e. to modify the...
SZWABE Andrzej; SCHORR Andreas; HAUCK Franz J.; KASSLER Andreas J.
Dynamic adaptation of multimedia content is seen as an important feature of next generation networks and pervasive systems enabling terminals and applications to adapt to changes in e.g. context, access network, and available Quality-of-Service(QoS) due to mobility of users, devices or sessions. We present the architecture of a multimedia stream adaptation service which enables communication between terminals having heterogeneous hardware and software capabilities and served by heterogeneous networks. The service runs on special content adaptation nodes which can be placed at any location within the network. The flexible structure of our architecture allows using a variety of different adaptation engines. A generic transcoding engine is used to change the codec of streams. An MPEG-21 Digital Item Adaptation (DIA) based transformation engine allows adjusting the data rate of scalable media streams. An intelligent decision-taking engine implements adaptive flow control which takes into account current network QoS parameters and congestion information. Measurements demonstrate the quality gains achieved through adaptive congestion control mechanisms under conditions typical for a heterogeneous network.
The author presents a simple decentralized adaptive-control scheme for multijoint robot manipulators based on the independent joint control concept. The control objective is to achieve accurate tracking of desired joint trajectories. The proposed control scheme does not use the complex manipulator dynamic model, and each joint is controlled simply by a PID (proportional-integral-derivative) feedback controller and a position-velocity-acceleration feedforward controller, both with adjustable gains. Simulation results are given for a two-link direct-drive manipulator under adaptive independent joint control. The results illustrate trajectory tracking under coupled dynamics and varying payload. The proposed scheme is implemented on a MicroVAX II computer for motion control of the three major joints of a PUMA 560 arm. Experimental results are presented to demonstrate that trajectory tracking is achieved despite coupled nonlinear joint dynamics.
Belda, Květoslav; Böhm, Josef
Athens: WSEAS, 2006 - (Bardis, N.; Mladenov, V.), s. 307-312 ISBN 960-8457-47-5. [WSEAS International Conference on System. Athens (GR), 10.07.2006-12.07.2006] R&D Projects: GA ČR GP102/06/P275; GA ČR GA102/05/0271 Institutional research plan: CEZ:AV0Z10750506 Keywords : on-line identification * predictive control * input/output equations of predictions * real time control Subject RIV: BC - Control Systems Theory http://library.utia.cas.cz/separaty/historie/belda-0040145.pdf
LIU Yu-sheng; CHEN Jiang; LI Xing-yuan
Many physical systems such as biochemical processes and machines with friction are of nonlinearly parameterized systems with uncertainties.How to control such systems effectively is one of the most challenging problems.This paper presents a robust adaptive controller for a significant class of nonlinearly parameterized systems.The controller can be used in cases where there exist parameter and nonlinear uncertainties,unmodeled dynamics and unknown bounded disturbances.The design of the controller is based on the control Lyapunov function method.A dynamic signal is introduced and adaptive nonlinear damping terms are used to restrain the effects of unmodeled dynamics,nonlinear uncertainties and unknown bounded disturbances.The backstepping procedure is employed to overcome the complexity in the design.With the proposed method,the estimation of the unknown parameters of the system is not required and there is only one adaptive parameter no matter how high the order of the system is and how many unknown parameters.there are.It is proved theoretically that the proposed robust adaptive control scheme guarantees the stability of nonlinearly parameterized system.Furthermore,all the states approach the equilibrium in arbitrary precision by choosing some design constants appropriately.Simulation results illustrate the effectiveness of the proposed robust adaptive controller.
National Aeronautics and Space Administration — A novel approach is proposed for the suppression of the aircraft's structural vibration to increase the resilience of the flight control law in the presence of the...
Merrill, W.; Leininger, G.
The objective of this paper is to utilize the design methods of modern control theory to realize a 'dual-adaptive' feedback control unit for a highly non-linear single spool airbreathing turbojet engine. Using a very detailed and accurate simulation of the non-linear engine as the data source, linear operating point models of unspecified dimension are identified. Feedback control laws are designed at each operating point for a prespecified set of sampling rates using sampled-data output regulator theory. The control system sampling rate is determined by an adaptive sampling algorithm in correspondence with turbojet engine performance. The result is a 'dual-adpative' control law that is functionally dependent upon the sampling rate selected and environmental operating conditions. Simulation transients demonstrate the utility of the dual-adaptive design to improve on-board computer utilization while maintaining acceptable levels of engine performance.
In the book (Adaptive Identification,Prediction and Control-Multi Level Recursive Approach), the concept of dynamical linearization of nonlinear systems has been presented.This dynamical linearization is formal only,not a real linearization.From the linearization procedure,we can find a new approach of system identification,which is on-line real-time modeling and real-time feedback control correction.The modeling and real-time feedback control have been integrated in the identification approach,with the parameter adaptation model being abandoned.The structure adaptation of control systems has been achieved,which avoids the complex modeling steps.The objective of this paper is to introduce the approach of integrated modeling and control.
Full Text Available This paper presents an application of adaptive neuro-fuzzy (ANFIS control for switched reluctance motor (SRM speed. The ANFIS has the advantages of expert knowledge of the fuzzy inference system and the learning capability of neural networks. An adaptive neuro-fuzzy controller of the motor speed is then designed and simulated. Digital simulation results show that the designed ANFIS speed controller realizes a good dynamic behaviour of the motor, a perfect speed tracking with no overshoot and a good rejection of impact loads disturbance. The results of applying the adaptive neuro-fuzzy controller to a SRM give better performance and high robustness than those obtained by the application of a conventional controller (PI.
Gundy-Burlet, Karen; Krishnakumar, K.; Limes, Greg; Bryant, Don
This paper examines the feasibility, potential benefits and implementation issues associated with retrofitting a neural-adaptive flight control system (NFCS) to existing transport aircraft, including both cable/hydraulic and fly-by-wire configurations. NFCS uses a neural network based direct adaptive control approach for applying alternate sources of control authority in the presence of damage or failures in order to achieve desired flight control performance. Neural networks are used to provide consistent handling qualities across flight conditions, adapt to changes in aircraft dynamics and to make the controller easy to apply when implemented on different aircraft. Full-motion piloted simulation studies were performed on two different transport models: the Boeing 747-400 and the Boeing C-17. Subjects included NASA, Air Force and commercial airline pilots. Results demonstrate the potential for improving handing qualities and significantly increased survivability rates under various simulated failure conditions.
YAO Jianyong; JIAO Zongxia; YAO Bin; SHANG Yaoxing; DONG Wenbin
This paper deals with the high performance force control of hydraulic load samulator.Many prevtous works for hydraultc force control are based on their linearization equations,but hydraulic inherent nonlinear properties and uncertainties make the conventional feedback proportional-integral-derivative control not yield to high-performance requirements.In this paper,a nonlinear system model is derived and linear parameterization is made for adaptive control.Then a discontinuous projection-based nonlinear adaptive robust force controller is developed for hydraulic load simulator.The proposed controller constructs an asymptotically stable adaptive controller and adaptation laws,which can compensate for the system nonlinearities and uncertain parameters.Meanwhile a well-designed robust controller is also developed to cope with the hydraulic system uncertain nonlinearities.The controller achieves a guaranteed transient performance and final tracking accuracy in the presence of both parametric uncertainties and uncertain nonlinearities; in the absence of uncertain nonlinearities,the scheme also achieves asymptotic tracking performance.Simulation and experiment comparative results are obtained to verify the high-performance nature of the proposed control strategy and the tracking accuracy is greatly improved.
The study of the behavior of a nuclear reactor is of great importance as it allows to know a priori the conditions at which a reactor is submitted. In the sareactor are the design and simulation of control algorithms based on the theories of modern control with the objective of improving improving the performance criterions as well as to guarantee the the stability of the retrofitting system. (author)
Kárný, Miroslav; Böhm, Josef; Guy, Tatiana Valentine; Nedoma, Petr
Roč. 17, č. 2 (2003), s. 119-132. ISSN 0890-6327 R&D Projects: GA ČR GA102/02/0204; GA ČR GA102/00/P045 Grant ostatní: ProDaCTool(XE) IST-1999-12058 Institutional research plan: CEZ:AV0Z1075907 Keywords : Bayesian identification * fully probabilistic control * finite mixtures Subject RIV: BC - Control Systems Theory Impact factor: 0.602, year: 2003 http://library.utia.cas.cz/prace/20030048.ps
This paper proposes an adaptive neural network speed control scheme for an induction motor (IM) drive. The proposed scheme consists of an adaptive neural network identifier (ANNI) and an adaptive neural network controller (ANNC). For learning the quoted neural networks, a back propagation algorithm was used to automatically adjust the weights of the ANNI and ANNC in order to minimize the performance functions. Here, the ANNI can quickly estimate the plant parameters and the ANNC is used to provide on-line identification of the command and to produce a control force, such that the motor speed can accurately track the reference command. By combining artificial neural network techniques with fuzzy logic concept, a neural and fuzzy adaptive control scheme is developed. Fuzzy logic was used for the adaptation of the neural controller to improve the robustness of the generated command. The developed method is robust to load torque disturbance and the speed target variations when it ensures precise trajectory tracking with the prescribed dynamics. The algorithm was verified by simulation and the results obtained demonstrate the effectiveness of the IM designed controller
Full Text Available Purpose: An adaptive control system is built which controlling the cutting force and maintaining constant roughness of the surface being milled by digital adaptation of cutting parameters.Design/methodology/approach: The paper discusses the use of combining the methods of neural networks, fuzzy logic and PSO evolutionary strategy (Particle Swarm Optimization in modeling and adaptively controlling the process of end milling. An overall approach of hybrid modeling of cutting process (ANfis-system, used for working out the CNC milling simulator has been prepared. The basic control design is based on the control scheme (UNKS consisting of two neural identificators of the process dynamics and primary regulator.Findings: The experimental results show that not only does the milling system with the design controller have high robustness, and global stability but also the machining efficiency of the milling system with the adaptive controller is much higher than for traditional CNC milling system. Experiments have confirmed efficiency of the adaptive control system, which is reflected in improved surface quality and decreased tool wear.Research limitations/implications: The proposed architecture for on-line determining of optimal cutting conditions is applied to ball-end milling in this paper, but it is obvious that the system can be extended to other machines to improve cutting efficiency.Practical implications: The results of experiments demonstrate the ability of the proposed system to effectively regulate peak cutting forces for cutting conditions commonly encountered in end milling operations. The high accuracy of results within a wide range of machining parameters indicates that the system can be practically applied in industry.Originality/value: By the hybrid process modeling and feed-forward neural control scheme (UNKS the combined system for off-line optimization and adaptive adjustment of cutting parameters is built.
Gunne J. Hegglid
Full Text Available This paper describes an adaptive multivariable control system for hydroelectric generating units. The system is based on a detailed mathematical model of the synchronous generator, the water turbine, the exiter system and turbine control servo. The models of the water penstock and the connected power system are static. These assumptions are not considered crucial. The system uses a Kalman filter for optimal estimation of the state variables and the parameters of the electric grid equivalent. The multivariable control law is computed from a Riccatti equation and is made adaptive to the generators running condition by means of a least square technique.
Wu, N. Eva; Nikulin, Vladimir; Heimes, Felix; Shormin, Victor
This paper briefly reports some results of our study on the application of a decentralized adaptive control approach to a 6 DOF nonlinear aircraft model. The simulation results showed the potential of using this approach to achieve fault tolerant control. Based on this observation and some analysis, the paper proposes a multiple channel adaptive control scheme that makes use of the functionally redundant actuating and sensing capabilities in the model, and explains how to implement the scheme to tolerate actuator and sensor failures. The conditions, under which the scheme is applicable, are stated in the paper.
Saito, Asaki; Konishi, Keiji
We demonstrate the dynamical characteristics of adaptive delayed-feedback control systems, exploiting a discrete-time adaptive control method derived for carrying out detailed analysis. In particular, the systems exhibit singularities such as power-law decay of the distribution of transient times and almost zero finite-time Lyapunov exponents. We can explain these results by characterizing such systems as having (1) a Jacobian matrix with unity eigenvalue in the whole phase space, and (2) parameters approaching a stability boundary proven to be identical with that of (nonadaptive) delayed-feedback control. PMID:22060398
Yang, Bong-Jun; Calise, Anthony J.; Craig, James I.; Whorton, Mark S.
Neural network-based adaptive control is considered for active control of a highly flexible truss structure which may be used to support solar sail membranes. The objective is to suppress unwanted vibrations in SAFE (Solar Array Flight Experiment) boom, a test-bed located at NASA. Compared to previous tests that restrained truss structures in planar motion, full three dimensional motions are tested. Experimental results illustrate the potential of adaptive control in compensating for nonlinear actuation and modeling error, and in rejecting external disturbances.
Full Text Available An adaptive landing gear is a landing gear (LG capable of active adaptation to particular landing conditions by means of controlled hydraulic force. The objective of the adaptive control is to mitigate the peak force transferred to the aircraft structure during touch-down, and thus to limit the structural fatigue factor. This paper investigates the ultimate limits for improvement due to various strategies of active control. Five strategies are proposed and investigated numerically using a~validated model of a real, passive landing gear as a reference. Potential for improvement is estimated statistically in terms of the mean and median (significant peak strut forces as well as in terms of the extended safe sinking velocity range. Three control strategies are verified experimentally using a laboratory test stand.
Alejandro Carrasco Elizalde
Full Text Available The collective behaviour of swarms produces smarter actions than those achieved by a single individual. Colonies of ants, flocks of birds and fish schools are examples of swarms interacting with their environment to achieve a common goal. This cooperative biological intelligence is the inspiration for an adaptive fuzzy controller developed in this paper. Swarm intelligence is used to adjust the parameters of the membership functions used in the adaptive fuzzy controller. The rules of the controller are designed using a computing-with-words approach called Fuzzy-Lyapunov synthesis to improve the stability and robustness of an adaptive fuzzy controller. Computing-with-words provides a powerful tool to manipulate numbers and symbols, like words in a natural language.
Carlos A. Saldarriaga-Cortés
Full Text Available This paper presents a methodology to implement an adaptive control of the inverted pendulum system; which uses the recursive square minimum method for the identification of a dynamic digital model of the plant and then, with its estimated parameters, tune in real time a pole placement control. The plant to be used is an unstable and nonlinear system. This fact, combined with the adaptive controller characteristics, allows the obtained results to be extended to a great variety of systems. The results show that the above methodology was implemented satisfactorily in terms of estimation, stability and control of such a system. It was established that adaptive techniques have a proper performance even in systems with complex features such as nonlinearity and instability.