A large number of design strategies exist for multivariable control situations. Many of' the methods require a linear time-invariant process characterisation in the form of a state space model or transfer function matrix description. Quite often this is not available and could be evpensive to realise. If this latter route is pursued there needs to be considerable benefits in the quality of the resulting closed-loop performance, especially when compared to those methods which only require minimal system information. The main aim of this paper is to compare a range of multivariable design strategies using a commercial multivariable coupled tank experimental rig as the uncompensated plant,
Astrom, K.J., and Hagglund, T.1984. 'Automatic tuning of simple regulators with specification on phase and amplitude margins.', Automatica20, 645-651.
2.
Billington, A.J. et al. 1991. 'Optimal PIP control of scalar and multivariable processes', lEE Int Conf Pub No 332, Vol 1, 574-579.
3.
Edmunds, J.M.1979. 'Control system design and analysis using closed loop Nyquist and Bode arrays'. Int J of Control, 30(5), 773-802.
4.
Heckenthaler, T., and Engell, S.1994. 'Approximately time optimal fuzzy control of a two-tank system'. IEEE Control Systems Journal, June, 24-30.
5.
Jones, A.H., and Porter, B.1987. 'Design of adaptive digital setpoint tracking PID controllers incorporating recursive step response matrix identifiers for multivariable plants', IEEE Trans Auto Control, AC-32(5), 459-462.
6.
King, P.J., and Mamdani, E.H.1977. 'The application of fuzzy control systems to industrial processes, Automatica, 13, 235-242.
7.
Loh, Ai P. et al. 1993. 'Autotuning of multiloop PI controllers using relay feedback'. Ind Eng Chem Res, 32, June, 1102-1107.
8.
MacFarlane, A.G.J., and Belletrutti, J.J.1973. 'Characteristic locus design method', Automatica, 9, 575-588.
Owens, D.H., and Chotai, A.1982. 'High performance controllers for unknown multivariable systems', Automatica, 18(5), 583--587.
11.
Penttinen, J., and Koivo, H.N.1980. 'Multivariable tuning regulators for unknown systems', Automatica, 16(4), 393-398.
12.
Rusenbrock, H.H.1974. Computer aided control system design, Academic Press, London.
13.
Tong, R.M.1977. 'A control engineering review of fuzzy systems'. Automatica, 13, 559-569.
14.
Wilson, I., and French, I.G.1995. 'Genetically tuned time optimal fuzzy control'. Advances in Process ControlIV, I Chem E. 27-28 September, York.
15.
Young, P.C., Behzadi, M.A., Wang, C.L., and Chotai, W.A.1987. 'Direct digital and adaptive control by input output state variable feedback pole assignment', Int J of Control, 46(6), 1867-1881.
