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This master's thesis presents the development of a collision handling function for Motoman industrial robots and investigates further use of the developed software. When a collision occurs the arm is to be retracted to a safe home location and the job is to be restarted to resume the production. The retraction can be done manually, which demands that the operator has to have good knowledge in robot handling and it might be a time consuming task. To minimise the time for restarting the job after a collision and allowing employees that have limited knowledge in robot handling to retract and restart the job, Motoman provides an automatical retraction function. However, the retraction function may cause further collisions when used and therefor a new function for retracting the arm is needed. The new function is based on that the motion of the robot is recorded by sampling the servo values, which are then stored in a buffer. A job file is automatically created and loaded into the control system, and the position variables of the job file are updated using the contents of the buffer. This will ensure a safe retraction of the arm as long as the environment surrounding the robot remains the same. The developed software made it possible to control the robot in real-time by changing the buffer information, which has lead to a cognitive system called the Pathfinder. By initiating the Pathfinder function with at least a start and an end point, the function generates a collision free path between the start point and the end point. A pilot-study has also been made concerning integration of a vision system with the Pathfinder to increase the decision handling for the function.

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In many processes it is important to have automatic control in the modern life. For example, PLC systems are using for machine control, water pressure and flow are able to be controlled by DDC program, even a car can be driven by computer. In this article, author will turn our focus on the control system for fermentation tank. The fermentation tank that produces methane is considered as clean and recycle energy source. It is widely used in house, electronic power machine and vehicle around the world. However, its reaction temperature and output concentration control are usually hard to detect without automation system. In this study, the problem is focused to combine fermentation tank and automatic control system in laboratory testing.   In this paper, author will be able to use PIC (Peripheral Interface Controller) microcontroller to solve this problem and automatically control the methane tank output methane gas with certain concentration, which could be used as energy source. The temperature and concentration sensors that are chosen as input data of the controller and corresponding algorithm were performed on the PIC. They will be used to realize the composition and thermal state measurement. With those information, the valves of material and water control can be controlled in methane tank.   Limited by the experiment equipment and methane reaction tank system, the controller was just tested in the laboratory environment instead of practical application. The test result shows that the controller has its capability to automatically control the stable output of methane gas. In the test, water and material valves are controlled automatically open or close after monitoring temperature and concentration information of the gas in the tank.

Two direct algorithms are suggested for the computation of the linear state feedback for multi-input systems such that the resultant closed-loop system matrix has specified eigenvalues. The extra freedom can be used in different ways, for example to decrease some norm of the feedback matrix or to improve the condition of some of the eigenvalues of the closed-loop matrix. The algorithms appear to be more efficient than the techniques already in existence and have several desirable numerical properties. They use unitary transformations for numerical reliability, and are based on ideas from the QR algorithm for solving the eigenproblem. / The above algorithms have been developed jointly with Chris Paige.

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