Human-simulated Intelligent Control Research Articles

Intelligent Control Emotion Mechanism Based on Artificial Life

The emotion mechanism being introduced to Human-Simulated Intelligent Control algorithm, a fresh Intelligent Control algorithm is proposed, to solve the parameters design and tuning difficulty of the original algorithm. The verification of proposed control algorithm is completed on the car-inverted pendulum simulation platform. After the simulation results of the original and its improved algorithm is compared with, the new control algorithm can be found to obtain better control results with less design parameters. Thus, the suggested idea confirms its feasibility and effectiveness preliminarily.

Human-Simulated Intelligent Control Technique for Incineration Treatment of Municipal Solid Waste

Human-Simulated Intelligent Control Technique for Incineration Treatment of Municipal Solid Waste

Research the Steering Model by Human-Simulated Intelligence Based on Vision-AGV

This paper presents a multi-mode intelligent controller based on the schema theory by analyzing AGV steering control strategy, and selects the corresponding control algorithm through the characteristic identification results. The steering control model of V-AGV is built by Human-simulated Intelligent Control based on the sensory-motor schema. The simulation and experiment results show that the AGV runs well in the structure environment, and the model is open and universal application in the unstructured environment.

HSIC Algorithm of Process Control

Process control objects mathematical model is difficult to establish. Based on humans thinking mode, control experience, action and intuitional reasoning, Human simulation intelligent control (HSIC) avoids all kinds of difficult problems that we are faced with as seeking the answer of complicated model or establishing brain model, and so there are some advantages for HSIC on process control. In this paper, a detailed algorithm is described for process control by using the method of HSIC. Finally, the results of practical application have proved that HSIC is feasible and effect for process control.

The Research on Human Simulating Intelligent Control of the Inverted Pendulum Based on Feedback Linearization

In this paper, the partial feedback linearization was made for the non-linear model of the triple inverted pendulum, by means of the differential geometry. Then the simulation and analysis of tracking control and interference control were made, which combined with the human simulating intelligent control and LQR control in the system. The results show that the human simulating intelligent control can achieve better control results than the LQR control, it not only can effectively improve the stability of the system, but also the anti-interference ability is better than LQR control, it meets the control requirements of the triple inverted pendulum.

Magnetorheological elastomer and its application on impact buffer

In this study, a new magnetorheological elastomer (MRE) based buffer is proposed and its vibration isolation performance is investigated. The MRE buffer with a compact structure is first designed in order to accomplish the maximization of the variable stiffness range. The working characteristics of the MRE buffer are then measured and the model of MRE is established. On the basis of the experimental data, the control model of the MRE buffer is also formulated. A two-degree-of-freedom dynamic model with an MRE buffer is then developed. An intelligent control strategy, human simulated intelligent control (HSIC), is proposed to reduce the impact during the drop crash. Finally, the proposed MRE buffer and controller are validated numerically and experimentally. The results show that the proposed MRE buffer and the control strategy can reduce the impact acceleration effectively.

Vibration Attenuation of Magnetorheological Landing Gear System with Human Simulated Intelligent Control

Due to the short duration of impulsive impact of an aircraft during touchdown, a traditional landing gear can only achieve limited performance. In this study, a magnetorheological (MR) absorber is incorporated into a landing gear system; an intelligent control algorithm, a human simulated intelligent control (HSIC), is proposed to adaptively tune the MR absorber. First, a two degree-of-freedom (DOF) dynamic model of a landing gear system featuring an MR absorber is constructed. The control model of an MR damper is also developed. After analyzing the impact characteristic during touchdown, an HSIC is then formulated. A genetic algorithm is adopted to optimize the control parameters of HSIC. Finally, a numerical simulation is performed to validate the proposed damper and the controller considering the varieties of sink velocities and sprung masses. The simulations under different scenarios show that the landing gear system based on the MR absorber can greatly reduce the peak impact load of sprung mass within the stroke. The biggest improvement of the proposed controller is over 40% compared to that of skyhook controller. Furthermore, HSIC exhibits better adaptive ability and strong robustness than skyhook controller under various payloads and sink velocities.

Semi-active control of magneto-rheological variable stiffness and damping seat suspension with human-body model

The potential benefits of an MR seat suspension in improving ride quality are investigated. Two magneto-rheological (MR) dampers are devised and manufactured to realise the variable damping and equivalent stiffness capacities of a seat suspension, respectively. After evaluating fi eld-dependent damping characteristics of the MR seat damper, the equation of equivalent variable stiffness is also shown. A seat suspension model with a four-DOF human body model is then formulated. A Human Simulated Intelligent Controller (HSIC) is proposed to attenuate the unwanted vibration of the variable stiffness and damping seat suspension. To validate the control performance of the proposed seat suspension and the control scheme, a numerical simulation is performed under the bump, random and chirp excitations. The result indicates that the proposed seat suspension system with HSIC can significantly improve the driver’s ride quality compared to the passive one.

Research and Application of Human-Simulated Intelligent Controller

The principle of human-simulated intelligent controller (HSIC) and the application in industrial control have been discussed. The improved HSIC compensates and consumes the system according to different conditions combined by error and error change rate. Because the parameter tuning of HSIC is completed in programmable logic controller, the control strategy of HSIC is simple than that of PID algorithm and the system response speed is more quickly. The author suggests that the parameters of HSIC should be optimized to decrease the complex degree of parameter tuning process and to reduce system overshoot dramatically.

Fulfillment of Arbitrary Movement Transfer Control between Equilibrium States for a Double Pendulum Robot

摘要: 双摆机器人两摆杆具有一个自稳定(Down-down)和三个自不稳定(Down-up, up-down, up-up)的平衡状态, 4个平衡状态之间可以构成12个相互转换的运动动作和8个自旋动作. 本文运用基于动觉智能图式的仿人智能控制理论, 设计具有基于特征辨识多控制模态结构的控制器; 采用``类等效''的系统建模方法和改进型遗传算法, 实现双摆机器人模型的精确辨识和其多模态控制器多参数的整定与优化, 并解决了多控制模态之间的平滑切换, 以及从仿真研究到实时控制成功的快速过渡等关键问题. 以(Down-up)向(Up-down)状态的转换为例, 说明了如何实现四个平衡状态之间的任意相互转换的运动控制, 并介绍了仿人智能控制器设计的详细过程. 仿真与实时控制的实例证明了设计理论与方法的有效性. 关键词: 双摆机器人 / 平衡态转换 / 多模态控制 / ``类等效''建模 / 改进型遗传算法

Dynamic Anti-Saturation Integral Controller Used in Time-Varying Delay System

Systems with large variable delay, traditional control methods can’t performance well. In this paper, a controller combined with the human-simulated intelligent controller (HSIC) and newly dynamic anti-saturation integral controller, is used in the time-varying delay motor speed control. Simulation studies show, there is no chatter in this controller which is always in norm variable structure controller and this method reaches good performance in the time-varying delay system.

Research of DD2UD with Human Simulating Intelligent Control for a Double Inverted Pendulum

A double pendulum has four equilibrium points (Down-Down, Down-Up, Up-Down, Up-Up). With those equilibrium points, many transfer actions from one equilibrium point to another can be formed. Using the Human Simulated Intelligent Control (HSIC) method based on Sensor-Motor Intelligent Schema, an intelligent control system for the double inverted pendulum which has the structure of multi controller and multi control mode is designed. With this controller, the transfer action of Down-Down to Up-Down (DD2UD) is achieved. The design process of HSIC controller is discussed. The real-time experiment result testified the validation of proposed method.

Optimized control for dynamical performance of the polishing robot in unstructured environment

In this paper, the dynamical performance of polishing robot working in unstructured environment is investigated. Structure mechanism and operating principle of a polishing robot are introduced firstly, and its dynamical model is esta blished. Then, a S-shaped acceleration-deceleration path planning method and a human-simulated intelligent control (HSIC) strategy are proposed. The S-shaped acceleration-deceleration path planning method is to switch the magnitude and direction of the abrupt velocities between motion sections in order to improve the work efficiency, the smoothness of movement and the processin g accuracy. The HSIC control strategy is built based on the unstructured environment information measured by ultrasonic sensors, in which the appropriate programs prepared in advance are determined according to the size and sign of both the control error and its change rate. Simulation results show that the intell igent control strategy combining with optimum path planning method are effective to reduce the structure vibration, to improve the stability and the control accuracy of the polishing robo t system.

Optimized Control for Dynamical Performance of the Polishing Robot in Unstructured Environment

In this paper, the dynamical performance of polishing robot working in unstructured environment is investigated. Structure mechanism and operating principle of a polishing robot are introduced firstly, and its dynamical model is established. Then, a S-shaped acceleration-deceleration path planning method and a human-simulated intelligent control (HSIC) strategy are proposed. The S-shaped acceleration-deceleration path planning method is to switch the magnitude and direction of the abrupt velocities between motion sections in order to improve the work efficiency, the smoothness of movement and the processing accuracy. The HSIC control strategy is built based on the unstructured environment information measured by ultrasonic sensors, in which the appropriate programs prepared in advance are determined according to the size and sign of both the control error and its change rate. Simulation results show that the intelligent control strategy combining with optimum path planning method are effective to reduce the structure vibration, to improve the stability and the control accuracy of the polishing robot system.

Error analysis of robot detecting system with laser sensors in unknown environment

Based on the extremely complicated circumstances of the unknown working environment of robots, and the uncertainty and continuous non-conductivity of the contact surface, a new detecting method is presented, based on the combination of a swing laser rangefinder sensor and an operating robot system. The detecting system model of robots is set up and the theoretical analysis is also made, which shows that the detecting error of the detecting system based on the laser sensor mainly comes from the laser rangefinder measure error caused by itself, the error related with the detected environment surface, the error caused by the dynamic measurement and the error caused by the outside environment. Furthermore, in order to control the complex system, a human-simulation intelligent control method of contact force is presented. The basic principle of the intelligent control method is that it can choose the appropriate programs prepared in advance according to the size and sign of the force error and change rate of t...

Overview of human-simulated intelligent control method and its application

The current development of human-simulated intelligent control (HSIC) is introduced and the basic concepts, ideology and features are summarised. Then, examples are taken for the prototype algorithm of HSIC; the static characteristics, dynamic characteristics and stability of HSIC are analysed. The basic design steps of HSIC are further cleared. Finally, the application of HSIC in the trajectory tracking control for robot system is studied. In fact, HSIC is for choosing the appropriate control strategy according to the sign of the characteristic variables of the control system. The experimental results show that the HSIC method improves the control precision greatly.

Parameter optimisation of human-simulated intelligent controller for a cart-double pendulum system

Using a hierarchical and multi-mode control structure, a human-simulated intelligent controller (HSIC) successfully realises the swing-up and stabilisation control for a cart-double pendulum system. In order to effectively optimise several parameters in control laws and advance the further application space of HSIC, a hybrid simplex-genetic algorithm (HSGA) is proposed in this paper. By analysing the procedure of swing-up and stabilisation control, the paper discusses how we determine the solution space of parameters and select the fitness function suited to this optimisation problem. The two different strategies, which are HSGA strategy and manual adjustment method, are performed the simulation experiments, respectively. The simulation results show that it has the better response of HSIC obtained by the proposed HSGA strategy. So it is proved that the proposed HSGA is effective to implement parameter optimisation of HSIC.

Study on System Design and Control Methods of Polishing Robot System

A design method is presented for a polishing robot in unstructured working environment. Setting up a structure model of the polishing system, and the operation principle and control method are described. The human-simulated intelligent control method is applied to the control of contact force in unstructured environment, because of the uncertainty, variability and unstructured of the environment. The basic idea of the intelligent control method is based on the size of error and change direction of control variables. The conditions of the control rules and control decision are inferred by forward reasoning. The HSIC controlling function is achieved, which can strengthen people energy to revise and control the interaction force and position of the end-effector.

A Comparison of Suitable Control Methods for Full Vehicle with Four MR Dampers Part II Controller Synthesis and Road Test Validation

The significant non-linearity and uncertainty in the behavior of magnetorheological (MR) suspension systems has been one of the main challenges in the application of this technology in the development of appropriate control algorithms. Here, four model-free control algorithms studied theoretically in prior work are applied to a full vehicle featuring four MR dampers and evaluated through road test to identify the most suitable control algorithm. The four model-free control algorithms include the well-known skyhook control, the hybrid control, the fuzzy logic control, and a newly proposed intelligent control algorithm, the human simulated intelligent control (HSIC). As the first step, four MR dampers (two for the front parts and two for the rear parts) are designed and manufactured based on the damping-force levels and mechanical dimensions of stock dampers of the test vehicle. After experimentally measuring the magnetic-field-dependent force property and controllability, a precise inverse model of MR damper is formulated. Subsequently, four controllers are developed and implemented using the rapid control prototyping technology. Then the road test with different control schemes is undertaken under various road conditions and vehicle speeds. For comparison purposes, the road test of the passive suspension system with four stock dampers is also carried out under the same conditions as that of the MR suspension system. Finally, the control responses for ride comfort and stability are evaluated in both time and frequency domains. The results support the conclusion made in the prior numerical analysis that the semi-active suspension system with each control algorithm can improve ride comfort and stability in some indexes, but HSIC algorithm is found to be the most suitable one with four MR dampers in the MR suspension system.

Method of inequalities-based multiobjective genetic algorithm for optimizing a cart-double-pendulum system

This article presents a multiobjective approach to the design of the controller for the swing-up and handstand control of a general cart-double-pendulum system (CDPS). The designed controller, which is based on the human-simulated intelligent control (HSIC) method, builds up different control modes to monitor and control the CDPS during four kinetic phases consisting of an initial oscillation phase, a swing-up phase, a posture adjustment phase, and a balance control phase. For the approach, the original method of inequalities-based (MoI) multiobjective genetic algorithm (MMGA) is extended and applied to the case study which uses a set of performance indices that includes the cart displacement over the rail boundary, the number of swings, the settling time, the overshoot of the total energy, and the control effort. The simulation results show good responses of the CDPS with the controllers obtained by the proposed approach.