Model-based designof a cone crusher adaptive control system

SummaryIn this study, we present a reinforcement learning (RL)‐based flight control system design method to improve the transient response performance of a closed‐loop reference model (CRM) adaptive control system. The methodology, known as RL‐CRM, relies on the generation of a dynamic adaption strategy by implementing RL on the variable factor in the feedback path gain matrix of the reference model. An actor‐critic RL agent is designed using the performance‐driven reward functions and tracking error observations from the environment. In the training phase, a deep deterministic policy gradient algorithm is utilized to learn the time‐varying adaptation strategy of the design parameter in the reference model feedback gain matrix. The proposed control structure provides the possibility to learn numerous adaptation strategies across a wide range of flight and vehicle conditions instead of being driven by high‐fidelity simulators or flight testing and real flight operations. The performance of the proposed system was evaluated on an identified and verified mathematical model of an agile quadrotor platform. Monte‐Carlo simulations and worst case analysis were also performed over a benchmark helicopter example model. In comparison to the classical model reference adaptive control and CRM‐adaptive control system designs, the proposed RL‐CRM adaptive flight control system design improves the transient response performance on all associated metrics and provides the capability to operate over a wide range of parametric uncertainties.

Adaptive traffic control systems continuously monitor traffic conditions on an arterial and adjust traffic signal timings to accommodate variation in traffic volume and minimize stops and delays. This paper describes currently practical adaptive control systems which have been used in the United States and worldwide, which include Adaptive Control System-Lite (ACS-Lite), Optimization Policies for Adaptive Control (OPAC), Real-Time Hierarchical Optimized Distributed and Effective System (RHODES), Sydney Coordinated Adaptive Traffic System (SCATS) and Split Cycle Offset Optimization (SCOOT). The comparisons of the benefits from past experiences, cost and hardware requirements will help the traffic engineers and decision makers a guideline to select the optimized adaptive control system based on research objectives.

A New Approach to the Design of an Adaptive Control System

Intelligent electrical discharge machining (EDM) molybdenum‑titanium‑zirconium alloy by an extended adaptive control system

In glutamate fermentation, intermittent feeding is the most widely used glucose feed strategy. This feeding strategy causes severe fluctuations of glucose concentration and osmotic pressure in fermentation broth, which deteriorates the viability of the cell and reduces glutamate production in turn. In order to maintain glucose concentration at stable and constant levels, an on-line prediction and feedback control system based an empiric mass balance model was developed. However, the control system did not work properly and sometimes glucose concentration could even decline to 0 level (glucose exhaustion), as the model parameter varies in different runs. As a result, a novel model-based adaptive feedback control system incoporating with an artificial neural network (ANN) based pattern reconition unit for on-line diagnosizing the fault of glucose exhaustion was proposed and applied for glutamate fermentation. This adaptive control system could accurately detect glucose exhaustion when it occurs, and then immediately updates the control parameter based on some pre-defined rule. With the proposed control system, glucose was automatically fed, and its concentration could be maintained at desired levels constantly. As a result, glutamate concentration was 17 ~ 30% higher than that of the traditional fermentations using the intermittent glucose feed strategy.

Inertial stabilization systems are designed to maintain the angular orientation of an optical system or other device in inertial space. Applications include surveillance, target tracking, flight control, weapon pointing, navigation, communication and others. Typically, some variation of a closed loop control system is employed which uses feedback from a gyro. The object of this paper is to consider the potential benefits and some approaches to adaptive control algorithms. Ideally, an adaptive control system would adjust itself to achieve "optimal performance" with respect to some criteria in the presence of changing plant characteristics, changing noise characteristics and a changing disturbance environment. Potentially, such a design could provide robust control for a variety of system configurations, mission conditions and applications resulting in significant reductions in both development and production costs as well as improved performance. First, the general stabilization problem and some conventional control system designs are briefly reviewed. Then a variety of adaptive techniques are surveyed. Finally, the current status and results of a joint research project between Texas Instruments and the University of Texas at Arlington whose goal is to develop an adaptive stabilization control system is discussed.

This paper analyzes the advisability of using the adaptive system on the CTX gamma 2000 TC multi-operation machine to improve the processing efficiency. Since modern multi-operation machines are very expensive, it influences on the cost of machining. Therefore, it is of practical interest to develop and study adaptive control systems that improve the accuracy and productivity of machining. The combined effect of all the elementary errors of the system arising during processing is taken into account. The process of setting the cutting tool to a size is described, the expressions for the optimal tuning size are generalized. To solve the problem of minimizing the influence of these errors on the machining process, a system of adaptive control of limiting regulation was proposed. The principle of the system operation has been described and the structural scheme of the system has been given. As a regulation parameter, the cutting power was used; it being the key factor in the processing efficiency. Due to the adaptive control system, both the efficiency and accuracy of machining were improved through a decrease in depreciation deductions from the machine. The economic feasibility of using such a system was established. In the same way, a method for calculating the adjustment size has been developed, based on the accuracy of machining balance. Thus, the improvement of machine tools due to adaptive control systems of limiting regulation is an actual problem of domestic engineering. In this paper, an adaptive diagram has been drawn up, which makes it possible to compile a universal general equation of the accuracy balance of a technological operation, and to determine the calculated control system for the CTX gamma 2000 TC machine

Nowadays, control systems for stepper motors are well defined by using microcontrollers. The stepper motors are very good in positioning tasks and measurement tasks. Now there are some FPGA based developments for stepper motor controlling systems because of the complexity of the controlling system. But the new FPGA systems don't use the whole functionality and benefits of the FPGAs like the parallelism of computing tasks or the right structured Hardware-, Software-Co-Design. In this paper we want to show, that there are many possibilities to use the FPGA benefits for the development of stepper motor control systems and we show also an outlook to new developments and systems. Like an adaptive control system, which controls the parameters of the stepper motor and inspects them for aging.

This paper presents an adaptive learning control system for the F-8 DFBW aircraft. The purpose of the control system is to learn plant parameter curves that affect the flight of the aircraft. These parameter curves are used to adjust the gain schedule of the aircraft in a prescribed manner to account for changing aircraft characteristics. The learning control system is an adjustable blend of a gain scheduling system and an adaptive control system in the sense that it takes the best of these two systems and eliminates the undesirable features of each.

Abstract. To meet the needs of drilling rescue, a variable structure detection robot for underground rescue was designed for the motion requirements of a small crawler robot in underground unstructured environments. The robot can improve the stability and anti-overturning ability of the system through its own configuration changes. The existing stability criteria are computationally complex and cannot meet the requirements of real-time control. Therefore, a stability criterion based on the contact force between the robot and the ground is proposed, and a robot adaptive stability control system was established based on back propagation (BP) neural network. The system can change the robot configuration in real time to ensure the overturning stability. The criterion is analyzed and compared with the existing stability methods, and the influence of the control system on the dynamic stability of the robot in three typical terrains is discussed. The robot simulation test model is established to simulate the robot's driving process on unstructured road and the process of adjusting the arm configuration on the slope. Finally, the stability control processes of the robot on a longitudinal slope and a transverse slope are experimentally analyzed. The analysis results show that the stability criterion is accurate and efficient, and the adaptive control system can improve the stability of the robot.

A direct adaptive control system for nonparametric plants in the presence of disturbances is proposed. This adaptive control system has robust performance and several desirable features. Since both the proposed controller structure and the frequency-domain adaptation algorithm have parallel architectures, the proposed total adaptive control system is suitable for parallel processing procedures. The effectiveness of the proposed adaptive control system is confirmed by numerical simulations. >

Nowadays actual scientific problem of renewable energy is the problem of developing control systems, that ensure the generation of stable voltage in a changing environment. This paper presents a structure and methods of synthesis of control system development, which allow to decide the indicated problem. An electric subsystem of wind power plant is a well-known structure with well-known advantages, consisting mainly of double-fed induction generator (DFIG) and power converter in the circuit of rotor. Operation of the control system based on the original nonlinear mathematical model of DFIG in rotational dq coordinates, taking into account the nonlinear external and internal DFIG disturbances, such as inductances of coil winding, changes of coil winding resistances from temperature, etc. The study received mathematical model, adaptive control algorithms and its computer simulation of the wind turbine with DFIG. Introduction An increasing requirement in energy resources at unstable oil prices stimulate to search the alternative decisions of power problems. One of the most successfully developed types of alternative energy is wind power. Its rapid growth observed in the world, proofing an attractiveness of this technology. It is expressed in the purity, reliability and input speed. So, according to Global Wind Energy Council (GWEC), to the end of 2015 global wind power capacity will reach 609 GW, compared to 237. 4 gigawatts at the end of 2011. The three leading world markets remain the China, U. S. and Europe. In recent years, the rapid growth of installed wind power capacity turned out to be possible through the development and implementation of new technological solutions, one of which is DFIG used as generator in wind power plants(WPP). Such DFIG are widely used in powerful WPP, as they allow to convert the available wind energy more efficiently, especially in periods of weak winds. It is known that the parameters of the generated voltage depends on terms of environment. At the same time, the necessity of quality stable voltage generation sets the problem of technological decisions development, allowing to minimize influence of different factors on output voltage quality. Such a technological solution is adaptive control system (CS) of a WPP with DFIG , permitting high speed reaction to wind speed changes and the rate of the connected electrical load, thus maintaining the stability of the generator output voltage. Synthesizing an adaptive high-speed CS and using the structure of WPP with DFIG it becomes possible to design and build these types of wind turbines. Synthesis of nonlinear CS Nonlinear CS control law. The solution of the indicated problem, offered in this paper, is based on the nonlinear model of DFIG in rotational dq coordinates, as in the conditions of different disturbances, linearizing appears uneffective [1]. Because, coming from the structure of WPP, control circuit is a rotor circuit, then primary control objective is feed on it control voltage of some parameters, at that DFIG output voltage remains unchanging and corresponds to set, without depending on influences. As it applies to a model, it is necessary to get the control values of voltages International Conference on Advances in Energy, Environment and Chemical Engineering (AEECE-2015) © 2015. The authors Published by Atlantis Press 1 on the dq rotor axes dr V and qr V , at the well-known required stator voltages ref ds V and ref qs V . The classic mathematical model of DFIG does not take into account the nonlinear changes of its parameters, such as winding inductances, changes of winding resistances from temperatures etc., accepting their permanent, that is not quite right. Meantime, in real DFIG such changes have an influence on control quality, so the synthesis of control system, which is taking into account such nonlinear disturbances, is an actual task. The disturbances arising up from nonlinear character of the control object are difficult to mathematical description, however valuation of these disturbances with the subsequent bringing of adjustments in work of CS on the basis of such estimation is a fully solvable task. For this purpose, in the standard mathematical model of DFIG we will add some functions of immeasurable disturbances, and (Eq.1), accordingly for the stator d and q axes currents, and next we synthesize control laws.

An adaptive control system with good following characteristics is designed for the electro-hydraulic servo system which are strongly coupled and seriously nonlinear. The model of position servo system on air rudder is discussed with the uncertain system equivalent to the one with parametric variable double input and single output to establish a Popov-MRAC (Model Reference Adaptive Control) system. The simulation results show that the Popov MRAC system has good following characteristics, precision and robustness.

Adaptive control systems are designed to achieve desired control performance when plant parameters gains are unknown, or possibly slowly changing. Highly calculation technology is developed, more important discrete-time adaptive control structure is. Because the relative degree condition for strict positive realness (SPR) of the discrete-time error transfer function is different from the condition of the continuous time case, it is hard to prove the stability of the discretized continuous-time adaptive control systems. The main contribution of this paper is the extension of an immersion and invariance (I&I)-based adaptive control algorithm from continuous to discrete time. The theoretical stability of the proposed discrete time I&I-based adaptive control system is proved. In order to show the effectiveness of the proposed method, numerical simulations are shown.

In order to address the difficult problem of hardware implementation of complex communication algorithm, this paper takes digital phase modulation as an example, and uses model-based design approach to quickly complete the algorithm modeling, simulation and automatic generation of HDL code. Model-based design is a fast and effective design process for algorithm modeling, simulation, testing and automatic code generation. The simulation results show that the model-based design method cannot only quickly accomplish the modeling and testing of the algorithm, but also improve the design accuracy.