4 892pulse/rot 0Hz 50Hz 2 00Hz 300Hz 2 CPU PID 6) 4, 7) 8) , 2) 2 M M θm + D M θm + f M sgn( θ M ) = τ N G [K G (N G θ M θ L ) + D G (N G θm
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1 シリアル 2 リンク 2 慣性系の同定と状態フィードバック制御 大明 準治 株 東芝 研究開発センター 足立 修一 慶應義塾大学 Identification and State Feedback Control of Serial Two-link-two-inertia System Junji OAKI (Toshiba Corporate R & D Center) and Shuichi ADACHI (Keio University) Abstract In this paper, we propose an identification method for a SCARA-type planer two link robot arm with elastic reduction gears, which is treated as a serial two-link-two-inertia system. In the identification method, we utilize not only motor encoders, but also rate gyros and accelerometers on each link of the arm. The identification method consists of three steps. The first step is the rigid model identification using a well-known procedure. The second is the elastic model identification using a multi-input multi-output state space model technique in which the interaction forces between two links are decoupled. The third is the physical parameter identification using the state space model. We also show experimental results of full state feedback control schemes including low pass filters designed by using the identified model parameters. Key Words: Robot arm, Rate gyro, Accelerometer, Mechanical resonance, Elastic joint, Harmonic drive はじめに 精密組立やマテリアルハンドリングなどで用いられ る産業用 SCARA スカラ 型ロボットは 水平旋回 する第 2 関節の減速機の弾性に起因した振動を抑 制しながら高速 高精度に動作することが要求される 従来のモーションコントロールにおける振動抑制は 2 多 慣性系の制御問題として扱われてきた その基本 的な考え方は 入出力系 外乱抑制制御であり スカ ラ型ロボットのようにシリアルに 2 慣性系が連なった 非線形の多入出力連成振動系には効果的な制御方法と は言えなかった 弾性関節を持つロボットに対して効果的と考えられ る例としては 西田ら ) や島田ら 2, 3) による 各軸を 駆動するモータに内蔵されたエンコーダだけの情報を 用いた状態空間表現での外乱オブザーバベースの巧妙 な制御方法が挙げられる これらは現状のセミクロー ズドループ制御方式のスカラ型ロボットに適用でき魅 力的ではあるが 制御系の実装は複雑であり 関節弾 性まで考慮に入れたモデル化のための物理パラメータ 同定も容易ではない また ロボットのダイナミクス を遅い剛体モードと速い振動モードに分けて考える特 異摂動法に基づくアプローチ 4, 5) についても同様な問 題を抱えている 本稿では モータ内蔵エンコーダに加えて 近年入 手容易になったレートジャイロや加速度センサをスカ ラ型ロボットの各リンクに搭載することを前提として シリアル 2 リンク 2 慣性系の干渉構造を利用した多入 出力状態空間同定法を提案し 水平旋回型 2 リンクアー ムの実機で検証する 提案法では 第 関節と第 2 関 節を非干渉化し 2 つの リンク 2 慣性系の同定問題に 帰着させているところがポイントである さらに こ の同定結果を用いて シリアル 2 リンク 2 慣性系の運 動方程式モデル 8 次 をシミュレーションするのに便 利なように 各関節の慣性や摩擦 バネ定数を求める 方法にも言及する これは 弾性関節を持つロボット の時系列データから剛体モデルの物理パラメータだけ でなく 弾性モデルの物理パラメータまで同定しよう という試みであるが 従来 ほとんど手がつけられて いなかった研究課題である 第7回制御部門大会 2007年3月6日 8日 調布 リンク搭載センサを利用すれば シリアル 2 リンク 2 慣性系モデルの範囲では 全状態フィードバック制御 が可能になる しかし リンク搭載センサが検出する 高次成分に起因するスピルオーバが問題となる そこ で本稿では 簡易なロバスト制御方法であるローパス フィルタ包含型状態フィードバック制御則について検 討する 最後に 状態フィードバックを用いてロボッ トを軌道制御する際に偏差を少なくするために必要な リンク角速度目標値軌道を 時間区分多項式ベースで 生成したモータ角速度目標値軌道から変換するための 目標値フィルタの同定についても述べる 2 対象とするシステム 本稿で制御対象とするのは Fig. に示すような水 平旋回型の 2 リンクアーム 各リンクの長さ m である 各関節を駆動する DC モータ 第 軸 500 W 第 2 軸 300 W は各リンク上に配置され バネ要素とし て振る舞うハーモニックドライブ減速機 減速比 /50 が直結されている これは 平行リンクを用いてない スカラ型ロボットの第 2 関節を模擬しており リ ンク 2 慣性系が直列に 2 つ配置されているので シリ アル 2 リンク 2 慣性系と呼ぶことにする 第 2 関節 の駆動系は全く同じ構造をしているが 第 2 関節は並 進運動をするので 並進運動しない第 関節とは異な る複雑な振動特性を示すのが特徴である 2nd Encoder st Rate Gyro 2nd Motor st Accelerometer 2nd Rate Gyro st Motor,Encoder, Harmonic Drive 2nd Harmonic Drive 2nd Accelerometer Fig. : Planer two link arm with elastic joints SY0003/07/ (c) 2007 SICE
2 4 892pulse/rot 0Hz 50Hz 2 00Hz 300Hz 2 CPU PID 6) 4, 7) 8) , 2) 2 M M θm + D M θm + f M sgn( θ M ) = τ N G [K G (N G θ M θ L ) + D G (N G θm θ L )] () M L (θ L ) θ L + c L ( θ L, θ L ) + D L θl = K G (N G θ M θ L ) + D G (N G θm θ L ) (2) θ M = [θ M, θ M2 ] T 2 θ L = [θ L, θ L2 ] T M L (θ L ) R 2 2 c L ( θ L, θ L ) R 2 M M = diag(m M, m M2 ) D M = diag(d M, d M2 ) D L = diag(d L, d L2 ) K G = diag(k G, k G2 ) D G = diag(d G, d G2 ) N G = diag(n G, n G2 )n G, n G2 f M = [f M, f M2 ] T τ = [τ, τ 2 ] T α, β, γ 9) [ ] α + β + 2γ cos(θl2 ) β + γ cos(θ M L (θ L ) = L2 ) β + γ cos(θ L2 ) β (3) [ c L ( θ γ(2 θl θl2 + L, θ L ) = θ L2 2 ) sin(θ ] L2) γ θ L 2 sin(θ (4) L2) cos(θ L2 ) sin(θ L2 ) θ L2 = n G2 θ M2 ()(2) β, γ () (2) θ M = N G θ L M(θ L ) θ L + c L ( θ L, θ L ) + D θ L + f M sgn( θ M )/N G = τ /N G (5) 9) M(θ L ), D (6)(7) M(θ L ) = [ ] α + β + 2γ cos(θl2 ) + m M /n 2 G β + γ cos(θ L2 ) β + γ cos(θ L2 ) β + m M2 /n 2 G2 (6) D = diag(d L + d M /n 2 G, d L2 + d M2 /n 2 G2) (7) 2) ω ω 2 θ L = ω (8) θ L2 = ω 2 ω (9) 2 a a 2 d d 2 θ L = a (0) d θ L2 = a 2 a a cos(n G2 θ M2 ) d 2 d d 2 d d 2 θ2 L sin(n G2 θ M2 ) () 0) 0Hz 50Hz 0Hz 2
3 G L (s) G H (s) = G L (s) T V θ Li(wide) = + T V s θ Li + T V s + T V s θ Li s = + T V s ( θ Li + T V θli ) (i =, 2) (2) (2) θ Li(wide) θ Li T P θ Li + T P s n Gθ Mi + T P s + T P s θ Li s = + T P s (n Giθ Mi + T F θli ) (i =, 2) (3) (5) 2 9) β, γ 5..2 ()(2) ()(2) ẋ = Ax + B (β + γ cos(θ L2 )) θ L2 (4) γ(2 θ L θl2 + θ L2 2 ) sin(θ L2) y = [ θ M θl ] T = Cx (5) τ (3) (,) (5) 6 ()(2) (4)(5) θ M (s) =G (s) τ + G 2 (s) (β + γ cos(θ L2 )) θ L2 G 3 (s) γ(2 θ L θl2 + θ 2 L2) sin(θ L2 ) (6) G (s) 2 2/3 ) G (s) = b 0 + b s + b 2 s 2 a 0 + a s + a 2 s 2 + a 3 s 3 (7) a 0 = d M + n 2 Gd L a = m M + n 2 Gm L + (n 2 Gd G d L + d M d L + d M d G )/k G a 2 = (m M d L + m M d G + m L d M + n 2 Gm L d G )/k G a 3 = m M m L /k G b 0 = b = (d L + d G )/k G b 2 = m L /k G (3) (,) m L = α + β + 2γ k G (7) 6 (4)(5) 2 G 2 (s) / Fig. M msM ms Hz d = 8 2ms 50Hz 00Hz 5Hz Fig. 2 M 0.3 Fig. 3 2 Fig. 4 Fig. 5 2
4 Fig. 2: M sequence input and its decimated data for st link identification (First 0.3s of 2.046s) cos (4) MATLAB TM pem 2) 3 pem (n4sid) Fig. 6 θ M 2/3 θ L /3 2 M Fig. 7 ()(2) SIMULINK TM 2 2 PID 3) Fig. FF-I-P Fig. 9, 0 pem 0 Fig. 6 2 Fig (3) (2) 2 2 Fig. 3: 2nd link acceleration data for st link identification Fig. 4: Motor and link velocity data for st link identification β, γ 4) ) Fig. Fig. 5: st link angle and cosine of 2nd link angle data during st link identification
5 (a) τ θ M (a) τ 2 θ M2 (b) τ θ L Fig. 6: Identified frequency responses (st link) 0.25ms 5.4 3) G R (s) 2 G R2 (s) (4)(5) θ M G (s)2/3 θ L G 2 (s)/3 G R (s) = G 2 (s)/g (s) (8) /2 G R2 (s) ) (b) τ 2 θ L2 Fig. 7: Identified frequency responses (2nd link) Fig. 8: Velocity step responses comparison (st link) Left: Real arm, Right: Simulation ) 2, 2-3, 466/47(994) 2), 4-5,
6 (a) τ θ M (a) τ 2 θ M2 (b) τ θ L Fig. 9: Identified frequency responses (st link) Single input case 466/472(2005) 3), 42-2, 39/46(2006) 4) M.C.Readman: Flexible Joint Robots, CRC Press (994) 5) C.C.de Wit, B.Siciliano and G.Bastin (Eds): Theory of Robot Control, 79/27, Springer (996) 6) G.Hirzinger, N.Sporer, A.Albu-Schäffer, M.Hähnle, R.Krenn, A.Pascucci and M.Schedl: DLR s torquecontrolled light weight robot III are we reaching the technological limits now?, Proc IEEE International Conference on Robotics and Automation, 70/76(2002) 7), , 944/95(99) 8), 23-2, 49/55(2003) 9) 62/80, (997) 0), 238/239, (989) ), 84/85, (999) 2) L.Ljung: System Identification Toolbox For Use with MATLAB (Version 6.2), The MathWorks(2006) (b) τ 2 θ L2 Fig. 0: Identified frequency responses (2nd link) Single input case Fig. : Velocity step responses comparison (st link) Left: State feedback, Right: State feedback with filter 3), 9-, 55/64(99) 4), 2/5, (2006) 5), 08/23, (2003) 6) MATLAB, 26/25, (2003)
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