State Dependent Parameter control applied to construction robots
and other nonlinear systems
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The work investigates a novel State Dependent Parameter (SDP) approach for the control of nonlinear systems, with particular emphasis on construction robots. It utilizes two practical demonstrators to evaluate and refine the control algorithms developed: a 1/5th scale laboratory representation of the Lancaster University Computerised Intelligent Excavator (LUCIE); and a full scale commercial vibro-lance system used for ground improvement on construction sites. In addition to these practical examples, the work also considers a benchmark simulation model, namely the multivariable, nonlinear ALST...
The work investigates a novel State Dependent Parameter (SDP) approach for the control of nonlinear systems, with particular emphasis on construction robots. It utilizes two practical demonstrators to evaluate and refine the control algorithms developed: a 1/5th scale laboratory representation of the Lancaster University Computerised Intelligent Excavator (LUCIE); and a full scale commercial vibro-lance system used for ground improvement on construction sites. In addition to these practical examples, the work also considers a benchmark simulation model, namely the multivariable, nonlinear ALSTOM gasifier system. The control methodology is based on the representation of the nonlinear dynamical system in a quasi-linear State Dependent Parameter (SDP) form, in which the parameters vary as functions of the state variables. Here, the states are typically defined as lagged input and output variables. The linear-like structure of the SDP model means that, at each sampling instant, it can be considered as a 'frozen' linear system. This formulation is subsequently used to design a Proportional-Integral-Plus (PIP) control law using linear system design strategies.
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