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 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 118