Robot kollarının gürbüz kontrolü
Robust control of robot arms
- Tez No: 39745
- Danışmanlar: PROF.DR. M. KEMAL SARIOĞLU
- Tez Türü: Yüksek Lisans
- Konular: Bilgisayar Mühendisliği Bilimleri-Bilgisayar ve Kontrol, Computer Engineering and Computer Science and Control
- Anahtar Kelimeler: Belirtilmemiş.
- Yıl: 1994
- Dil: Türkçe
- Üniversite: İstanbul Teknik Üniversitesi
- Enstitü: Fen Bilimleri Enstitüsü
- Ana Bilim Dalı: Belirtilmemiş.
- Bilim Dalı: Belirtilmemiş.
- Sayfa Sayısı: 118
Özet
A = A-BK where is Hurwitz and Step 2: We find a continuous function p (e,t) which is bounded in t, satisfying the inequalities |Av« < p(ej) hi < P(e,t) (S.19) Step 3: Since A is Hurwitz, choose a 2nx2n symmetric, positive definite matrix Q and let P be the unique positive definite symmetric solution to the Lyapunov equation A* P + PA + Q = 0 (S.20) Step 4: Choose the outer loop control Av according to Av = -P(e,t) BTP \BTPe\\*Q \B TP e « ' 0, \\BTPe\\=Q (S.21) XIV
Özet (Çeviri)
SUMMARY ROBUST CONTROL OF ROBOT ARMS Early work leading to today's industrial robots can be traced to the period immediately following World War II [1]. During the late 1940's research programs were stated at USA to develop remotely controlled mechanical manipulators for handling radioactive materials. These systems were of the“master-slave”type, designed to reproduce faithfully hand and arm motions made by a human operatör. Today, we view robotics as a much broader fîeld of work than we did just a few year ago, dealing with research and development in a number of interdisciplinary areas, including kinematics, dynamics, planning systems, control, sensing, programming languages, and machine intelligence. The control problem for robot manipulators is the problem of determining the time history of joint inputs recjuired to cause the end- effector to execute commanded motion. The joint inputs may be joint forces and torques, ör they may be inputs to the actuators, for example, voltage inputs to the motors, depending on the model used for controller design. The commanded motion is typically specified either as a sequence of end- efîector positions and orientations, ör as a continuous path. The fîrst serious studies on robot control were made at early 70's. At the years following 80's, suggested robot control methods have been generally adaptive ör robust. Although this methods are fairly succesive, the applications of these methods at industry are highly limited. At the industrial applications, PID controllers are mostly used. viiA = A-BK where is Hurwitz and Step 2: We find a continuous function p (e,t) which is bounded in t, satisfying the inequalities |Av« < p(ej) hi < P(e,t) (S.19) Step 3: Since A is Hurwitz, choose a 2nx2n symmetric, positive definite matrix Q and let P be the unique positive definite symmetric solution to the Lyapunov equation A* P + PA + Q = 0 (S.20) Step 4: Choose the outer loop control Av according to Av = -P(e,t) BTP \BTPe\\*Q \B TP e « ' 0, \\BTPe\\=Q (S.21) XIVSUMMARY ROBUST CONTROL OF ROBOT ARMS Early work leading to today's industrial robots can be traced to the period immediately following World War II [1]. During the late 1940's research programs were stated at USA to develop remotely controlled mechanical manipulators for handling radioactive materials. These systems were of the“master-slave”type, designed to reproduce faithfully hand and arm motions made by a human operatör. Today, we view robotics as a much broader fîeld of work than we did just a few year ago, dealing with research and development in a number of interdisciplinary areas, including kinematics, dynamics, planning systems, control, sensing, programming languages, and machine intelligence. The control problem for robot manipulators is the problem of determining the time history of joint inputs recjuired to cause the end- effector to execute commanded motion. The joint inputs may be joint forces and torques, ör they may be inputs to the actuators, for example, voltage inputs to the motors, depending on the model used for controller design. The commanded motion is typically specified either as a sequence of end- efîector positions and orientations, ör as a continuous path. The fîrst serious studies on robot control were made at early 70's. At the years following 80's, suggested robot control methods have been generally adaptive ör robust. Although this methods are fairly succesive, the applications of these methods at industry are highly limited. At the industrial applications, PID controllers are mostly used. viiA = A-BK where is Hurwitz and Step 2: We find a continuous function p (e,t) which is bounded in t, satisfying the inequalities |Av« < p(ej) hi < P(e,t) (S.19) Step 3: Since A is Hurwitz, choose a 2nx2n symmetric, positive definite matrix Q and let P be the unique positive definite symmetric solution to the Lyapunov equation A* P + PA + Q = 0 (S.20) Step 4: Choose the outer loop control Av according to Av = -P(e,t) BTP \BTPe\\*Q \B TP e « ' 0, \\BTPe\\=Q (S.21) XIVSUMMARY ROBUST CONTROL OF ROBOT ARMS Early work leading to today's industrial robots can be traced to the period immediately following World War II [1]. During the late 1940's research programs were stated at USA to develop remotely controlled mechanical manipulators for handling radioactive materials. These systems were of the“master-slave”type, designed to reproduce faithfully hand and arm motions made by a human operatör. Today, we view robotics as a much broader fîeld of work than we did just a few year ago, dealing with research and development in a number of interdisciplinary areas, including kinematics, dynamics, planning systems, control, sensing, programming languages, and machine intelligence. The control problem for robot manipulators is the problem of determining the time history of joint inputs recjuired to cause the end- effector to execute commanded motion. The joint inputs may be joint forces and torques, ör they may be inputs to the actuators, for example, voltage inputs to the motors, depending on the model used for controller design. The commanded motion is typically specified either as a sequence of end- efîector positions and orientations, ör as a continuous path. The fîrst serious studies on robot control were made at early 70's. At the years following 80's, suggested robot control methods have been generally adaptive ör robust. Although this methods are fairly succesive, the applications of these methods at industry are highly limited. At the industrial applications, PID controllers are mostly used. viiA = A-BK where is Hurwitz and Step 2: We find a continuous function p (e,t) which is bounded in t, satisfying the inequalities |Av« < p(ej) hi < P(e,t) (S.19) Step 3: Since A is Hurwitz, choose a 2nx2n symmetric, positive definite matrix Q and let P be the unique positive definite symmetric solution to the Lyapunov equation A* P + PA + Q = 0 (S.20) Step 4: Choose the outer loop control Av according to Av = -P(e,t) BTP \BTPe\\*Q \B TP e « ' 0, \\BTPe\\=Q (S.21) XIVSUMMARY ROBUST CONTROL OF ROBOT ARMS Early work leading to today's industrial robots can be traced to the period immediately following World War II [1]. During the late 1940's research programs were stated at USA to develop remotely controlled mechanical manipulators for handling radioactive materials. These systems were of the“master-slave”type, designed to reproduce faithfully hand and arm motions made by a human operatör. Today, we view robotics as a much broader fîeld of work than we did just a few year ago, dealing with research and development in a number of interdisciplinary areas, including kinematics, dynamics, planning systems, control, sensing, programming languages, and machine intelligence. The control problem for robot manipulators is the problem of determining the time history of joint inputs recjuired to cause the end- effector to execute commanded motion. The joint inputs may be joint forces and torques, ör they may be inputs to the actuators, for example, voltage inputs to the motors, depending on the model used for controller design. The commanded motion is typically specified either as a sequence of end- efîector positions and orientations, ör as a continuous path. The fîrst serious studies on robot control were made at early 70's. At the years following 80's, suggested robot control methods have been generally adaptive ör robust. Although this methods are fairly succesive, the applications of these methods at industry are highly limited. At the industrial applications, PID controllers are mostly used. viiA = A-BK where is Hurwitz and Step 2: We find a continuous function p (e,t) which is bounded in t, satisfying the inequalities |Av« < p(ej) hi < P(e,t) (S.19) Step 3: Since A is Hurwitz, choose a 2nx2n symmetric, positive definite matrix Q and let P be the unique positive definite symmetric solution to the Lyapunov equation A* P + PA + Q = 0 (S.20) Step 4: Choose the outer loop control Av according to Av = -P(e,t) BTP \BTPe\\*Q \B TP e « ' 0, \\BTPe\\=Q (S.21) XIVSUMMARY ROBUST CONTROL OF ROBOT ARMS Early work leading to today's industrial robots can be traced to the period immediately following World War II [1]. During the late 1940's research programs were stated at USA to develop remotely controlled mechanical manipulators for handling radioactive materials. These systems were of the“master-slave”type, designed to reproduce faithfully hand and arm motions made by a human operatör. Today, we view robotics as a much broader fîeld of work than we did just a few year ago, dealing with research and development in a number of interdisciplinary areas, including kinematics, dynamics, planning systems, control, sensing, programming languages, and machine intelligence. The control problem for robot manipulators is the problem of determining the time history of joint inputs recjuired to cause the end- effector to execute commanded motion. The joint inputs may be joint forces and torques, ör they may be inputs to the actuators, for example, voltage inputs to the motors, depending on the model used for controller design. The commanded motion is typically specified either as a sequence of end- efîector positions and orientations, ör as a continuous path. The fîrst serious studies on robot control were made at early 70's. At the years following 80's, suggested robot control methods have been generally adaptive ör robust. Although this methods are fairly succesive, the applications of these methods at industry are highly limited. At the industrial applications, PID controllers are mostly used. vii
Benzer Tezler
- Robot kollarının adaptif kontrolü
Adaptive control of robot arms
K.FATİH DİLAVER
Yüksek Lisans
Türkçe
1994
Bilgisayar Mühendisliği Bilimleri-Bilgisayar ve Kontrolİstanbul Teknik ÜniversitesiPROF.DR. M. KEMAL SARIOĞLU
- Neuro-Fuzzy variable structure control of robotic manipulators
Robot kollarının bulanık yapay sinir ağları ile değişken yapılı kontrolu
HASAN PALAZ
Doktora
İngilizce
2000
Bilgisayar Mühendisliği Bilimleri-Bilgisayar ve Kontrolİstanbul Teknik ÜniversitesiPROF.DR. M. KEMAL SARIOĞLU
- Control of redundant robot manipulators with telerobotic applications
Artık eklemli robot kollarının kontrolü ve telerobotik uygulamaları
KAMİL ÇETİN
Doktora
İngilizce
2016
Elektrik ve Elektronik Mühendisliğiİzmir Yüksek Teknoloji EnstitüsüElektronik ve Haberleşme Mühendisliği Ana Bilim Dalı
DOÇ. DR. ENVER TATLICIOĞLU
- Robot kollarının görev uzayında, eyleyici dinamikleri dikkate alınarak denetimi
Robot manipulator control including actuator dynamics in task space
ŞÜKRÜ ÜNVER
Doktora
Türkçe
2024
Elektrik ve Elektronik MühendisliğiEge ÜniversitesiElektrik-Elektronik Mühendisliği Ana Bilim Dalı
PROF. DR. MUSA ALCI
- Robust variable structure controllers design for robot manipulators with parameter perturbations
Parametre sarsımları bulunan robot kolları için gürbüz değişken yapılı denetleyici tasarımı
MEHMET NUR ALPASLAN PARKLAKÇI
Doktora
İngilizce
2003
Elektrik ve Elektronik MühendisliğiBoğaziçi ÜniversitesiElektrik-Elektronik Mühendisliği Ana Bilim Dalı
PROF. DR. YORGO İSTEFANOPULOS
PROF. DR. ELBRUS JAFAROV