• Journal of Mechanical Science and Technology
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• 제17권10호
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• pp.1466-1474
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• 2003

This paper presents a system modeling, controller design and implementation for a rotational inverted pendulum system (RIPS), which is an under-actuated system and has the problem of unattainable velocity state. Two control strategies are applied to the RIPS. One is a sliding mode control method using the parameterization of both the hyperplane and the compensator for output feedback. The other is the disturbance observer which estimates disturbance and some modeling errors of RIPS with less computational effort. Some simulations and various kinds of experiments are performed in order to verify that the proposed controller has the ability to control RIPS whose velocity is assumed to be unavailable. The results of the simulations and experiments show that the proposed control system has superior performance for disturbance rejection and regulation at certain initial conditions as well as the robustness to model uncertainties.

• 제어로봇시스템학회논문지
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• 제10권12호
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• pp.1210-1216
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• 2004

This paper deals with a human-like gait generation of a biped robot with a balancing weight of an inverted pendulum type by using genetic algorithm. The ZMP (Zero Moment Point) is the most important index in a biped robot's dynamic walking stability. To perform a stable walking of a biped robot, a balancing motion is required according to legs' trajectories and a desired ZMP trajectory. A dynamic equation of the balancing motion is nonlinear due to an inverted pendulum type's balancing weight. To solve the nonlinear equation by the FDM (Finite Difference Method), a linearized model of equation is proposed. And GA (Genetic Algorithm) is applied to optimize a human-like balancing motion of a biped robot. By genetic algorithm, the index of the balancing motion is efficiently optimized, and a dynamic walking stability is verified by the ZMP verification equation. These balancing motion are simulated and experimented with a real biped robot IWR-IV. This human-like gait generation will be applied to a humanoid robot, at future work.

• 대한기계학회논문집A
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• 제35권7호
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• pp.767-772
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• 2011

궤적생성은 로봇보행의 안정성, 연속성 그리고 보행특성을 결정하는 가장 중요한 일이다. 보통 궤적생성법으로 LIPM을 많이 쓰지만 그것은 그것의 선형화 기법 때문에 수직방향으로의 동작생성을 할 수 없다는 단점이 있다. 이 논문에서는 ELIPM이라는 새로운 궤적생성법을 제안한다. 이 궤적생성법은 전진방향의 동작은 물론이고 수직방향의 동작을 간단하게 생성할 수 있다.

• 한국정밀공학회지
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• 제22권7호
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• pp.112-121
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• 2005

This paper is concerned with smooth trajectory generation of biped robot which has inverted pendulum type balancing weight. Genetic algorithm is used to generate the trajectory of the leg and balancing weight. Balancing trajectory can be determined by solving the second order differential equation under the condition that the reference ZMP (Zero moment point) is settled. Reference ZMP effect on gait pattern absolutely but the problem is how to determine the reference ZMP. Genetic algorithm can find optimal solution under the high order nonlinear situation. Optimal trajectory is generated when use genetic algorithm which has some genes and a fitness function. In this paper, minimization of balancing joints motion is used for the fitness function and set the weight factor of the two balancing joints at the fitness function. Inverted pendulum type balancing weight is very similar with human and this model can be used fur humanoid robot. Simulation results show ZMP trajectory and the walking experiment made on the real biped robot IWR-IV.

• 한국컴퓨터정보학회논문지
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• 제15권5호
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• pp.13-21
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• 2010

도립진자 시스템에서 칼만 필터링 최적의 결과를 얻기 위해서는 잡음 공분산 행열 Q, 측정잡음 공분산 행열 R과 초기 에러 공분산 행열 $P_0$와 같은 인자가 필요하다. 이러한 인자는 실제 상황에서 근사화된 값을 사용하거나 정확한 값을 알 수 없기 때문에 칼만 필터의 최적화에 영향을 미치지 않거나 이러한 공분산 행열의 스칼라 이득변화에 덜 민감한 경우를 연구의 대상으로 하고 있다. 또한 상태 측정시 에러를 예측하는 방법으로 구해진 에러 공분산 행열은 상태측정 값 보다는 공분산 행열의 이득과 연관성을 가지게 된다. 따라서 3가지 공분산 행열과 칼만 이득 그리고 에러 공분산 행열 간의 상관관계가 잡음인자인 스칼라 이득과의 연관성을 해석하고자 하였다. 본 연구는 3절에서 도립진자 시스템 모델을 간략하게 정리를 하였고 4절에서는 이러한 모델을 기반으로 하여 컴퓨터 시뮬레이션을 위한 도립진자 시스템에 대한 수학적 동적모델을 구성하고 5절에서는 이러한 인자와 스칼라 이득 값을 이용한 다양한 시뮬레이션 결과를 통하여 잡음인자의 연관성을 해석하였다.

• 제어로봇시스템학회논문지
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• 제15권9호
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• pp.929-938
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• 2009

This paper presents a novel control methodology for communication network based nonlinear systems with time delay nature. We construct a nominal nonlinear control law for representing a linear model and a reset control system which is aimed for corrective control strategy to compensate system error due to uncertain time delay through wireless communication network. Next, online neural control approach is proposed for overcoming nonstationary statistical nature in the network topology. Additionally, DBN (Dynamic Bayesian Network) technique is accomplished for modeling of its dynamics in terms of casuality, which is then utilized for estimating prediction of system output. We evaluate superiority and reliability of the proposed control approach through numerical simulation example in which a nonlinear inverted pendulum model is employed as a networked control system.

• 제어로봇시스템학회논문지
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• 제13권4호
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• pp.279-285
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• 2007

The objective of the research is two fold. The first is to design and propose a stable and robust learning control algorithm. The controller is CMAC Learning Controller which consists of a model-based controller, such as LQR or PID, as a reference control and a CMAC. The second objective is to implement a reference control and CMAC at two different sampling rates. Generally, a conventional controller is designed based on a mathematical plant model. However, increasing complexity of the plant and accuracy requirement on mathematical models nearly prohibits the application of the conventional controller design approach. To avoid inherent complexity and unavoidable uncertainty in modeling, biology mimetic methods have been developed. One of such attempts is Cerebellar Model Articulation Computer(CMAC) developed by Albus. CMAC has two main disadvantages. The first disadvantage of CMAC is increasing memory requirement with increasing number of input variables and with increasing accuracy demand. The memory needs can be solved with cheap memories due to recent development of new memory technology. The second disadvantage is a demand for processing powers which could be an obstacle especially when CMAC should be implemented in real-time. To overcome the disadvantages of CMAC, we propose CMAC learning controller with multiple sampling rates. With this approach a conventional controller which is a reference to CMAC at high enough sampling rate but CMAC runs at the processor's unoccupied time. To show efficiency of the proposed method, an inverted pendulum controller is designed and implemented. We also demonstrate it's possibility as an industrial control solution and robustness against a modeling uncertainty.

• 한국정보통신학회논문지
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• 제6권1호
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• pp.6-13
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• 2002

본 논문은 선형 행렬 부등식 (LMI) 기법을 이용하여, 도립진자 시스템의 안정화 조절 제어 및 추종 제어 특성을 만족하는 다목적 제어기를 선계하기 위하여, 도립진자의 모델을 복수개의 모델을 원소로 가진 폴리토프 모델(polytopic model)로 표현하고, 극점 배치 Η$_2$/Η$_{\infty}$ 제어기를 설계하는 과정을 예시한 것이다. 도립진자의 진폭이 비교적 큰 경우, 하나의 동작점에서 구한 선형 시불변 모델의 오차를 불확실성으로 고려하여 설계한 제어기가 가지기 쉬운 보수성(conservativeness)을 극복하기 위하여, 도립진자 시스템에 대하여 다수의 경사 각도를 선형화의 동작점으로 취하여 복수개의 선형시불변 모델로써 이루어진 하나의 폴리토프 모델(polytopic model)을 구성하였다. 이 모델에 대하여, 볼록 최적화(convex optimization) 알고리즘을 사용하는 LMI 소프트웨어를 사용하여 다목적 성능을 만족하는 제어기를 설계하였다. 폴리토프 모델에 대하여 설계된 제어기로써 제어된 도립 진자는, 비교적 큰 경사 각도의 초기치에 대한 실험에서, 안정하게 연직 위치로 복원되는 제어 효과를 관찰할 수 있었다.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1996년도 하계학술대회 논문집 B
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• pp.1104-1106
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• 1996

In this paper, a hierarchical fuzzy controller is proposed for the stabilization control of the inverted pendulum system. The design of controller for that system is difficult because of its complicated nonlinear mathematical model with unknown parameters. Conventional fuzzy control strategy based only on dynamics of pendulum made have failed to stabilize. However, proposed control strategies are to swing pendulum from natural stable up equilibrium point to an unstable equilibrium point and are to transport a cart from an arbitrary position toward a center of rail. Thus, the proposed fuzzy stabilization controller have a hierarchical fuzzy inference structure; that is, the lower level is for inference interface for the virtual equilibrium point and the higher level one for the position control of cart according to the firstly inferred virtual equilibrium point.

• 로봇학회논문지
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• 제12권2호
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• pp.239-247
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• 2017

The purpose of this study is to develop a motion generation technique based on a double inverted pendulum model (DIPM) that learns and reproduces humanoid robot (or virtual human) motions while keeping its balance in a pattern similar to a human. DIPM consists of a cart and two inverted pendulums, connected in a serial. Although the structure resembles human upper- and lower-body, the balancing motion in DIPM is different from the motion that human does. To do this, we use the motion capture data to obtain the reference motion to keep the balance in the existence of external force. By an optimization technique minimizing the difference between the motion of DIPM and the reference motion, control parameters of the proposed method were learned in advance. The learned control parameters are re-used for the control signal of DIPM as input of linear quadratic regulator that generates a similar motion pattern as the reference. In order to verify this, we use virtual human experiments were conducted to generate the motion that naturally balanced.